Agronomy

Article

20 pages, 1075 KiB

Open AccessEditor’s ChoiceArticle

Uncaria tomentosa-Loaded Chitosan Oligomers–Hydroxyapatite–Carbon Nitride Nanocarriers for Postharvest Fruit Protection

by Alberto Santiago-Aliste, Eva Sánchez-Hernández, Laura Buzón-Durán, José Luis Marcos-Robles, Jesús Martín-Gil and Pablo Martín-Ramos

Agronomy 2023, 13(9), 2189; https://doi.org/10.3390/agronomy13092189 - 22 Aug 2023

Cited by 2 | Viewed by 1670

Abstract

Given the risks associated with synthetic fungicides, it is crucial to explore safe and sustainable alternatives. One potential solution is using bioactive natural products (BNPs). However, BNPs face challenges like lability, solubility, and lack of specificity. These issues can be addressed through nanoencapsulation. [...] Read more.

Given the risks associated with synthetic fungicides, it is crucial to explore safe and sustainable alternatives. One potential solution is using bioactive natural products (BNPs). However, BNPs face challenges like lability, solubility, and lack of specificity. These issues can be addressed through nanoencapsulation. This study focuses on the evaluation of novel chitosan oligomers–hydroxyapatite–carbon nitride (COS–HAp–g-C₃N₄) nanocarriers (NCs) for encapsulating BNPs, specifically an extract from Uncaria tomentosa bark. The NCs were characterized by transmission electron microscopy, energy-dispersive X-ray spectroscopy, and infrared spectroscopy. The NCs were monodisperse, with a mean diameter of 250 nm, and showed an encapsulation efficiency of 82%. The suitability of the loaded NCs (COS–HAp–g-C₃N₄–BNP, in a 2:1:0.5:1 weight ratio) for postharvest fruit protection was investigated in vitro and ex situ at a laboratory scale. Results regarding their efficacy against Botrytis cinerea on strawberries, Colletotrichum gloeosporioides on mangoes, Penicillium expansum on apples, Monilinia laxa on peaches, and Sclerotinia sclerotiorum on kiwifruit are presented. Minimum inhibitory concentrations of 250, 375, 375, 250, and 187.5 μg·mL⁻¹ were found in vitro, respectively, while higher doses (500, 750, 750, 250, and 375 μg·mL⁻¹, respectively) were needed to achieve effective control in postharvest tests on artificially inoculated fruit. These findings suggest that NCs containing extracts from U. tomentosa bark show promise as biorational agents and as alternatives to conventional fungicides for managing postharvest phytopathogens. Full article

(This article belongs to the Special Issue Cutting Edge Research of Nanoparticles Application in Agriculture)

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17 pages, 4320 KiB

Open AccessEditor’s ChoiceArticle

Classification of Monofloral Honeys by Measuring a Low-Cost Electronic Nose Prototype Based on Resistive Metal Oxide Sensors

by Eduardo González María, Antonio Madueño Luna, Agustín Conesa Celdrán, Gemma Martínez Muñoz, Martin John Oates and Antonio Ruiz-Canales

Agronomy 2023, 13(8), 2183; https://doi.org/10.3390/agronomy13082183 - 21 Aug 2023

Cited by 4 | Viewed by 1447

Abstract

In this article a case study of characterisation of type of honey based on floral origin is presented. It is intended to discriminate Iberian honeys from local beekeepers located in the Community of Madrid (Spain), by means of a low-cost electronic nose prototype, [...] Read more.

In this article a case study of characterisation of type of honey based on floral origin is presented. It is intended to discriminate Iberian honeys from local beekeepers located in the Community of Madrid (Spain), by means of a low-cost electronic nose prototype, composed of a matrix of nonspecific resistive sensors of MQ-type metal oxides. The measurements of the honeys made with an electronic nose prototype were contrasted with physicochemical analyzes and pollen content. The experiment was carried out in two trials. A first preliminary study in which six samples of honey from different sources were used (three Blueweed, one rapeseed, one lavender and one commercial honey) and in which eight repetitions were made for each of the six samples analyzed. Due to the small sample size, conclusive results were not obtained, although the sensors did show a clear response in those that presented a higher pollen content, above 57%, however, the honey samples that reflected pollen values lower than 50% they showed no perceptible reaction on the sensors. In the second study, in which the sample size was increased to a total of 16 samples (four lavender honeys, four oak honeys, four rosemary honeys, and four chestnut honeys), a total of 10 repetitions per sample were carried out with a total of repetitions out of 160. These last data were analyzed with the principal component technique (PCA), the results of which were inconclusive. However, when applying the data analysis through the use of Support Vector Machines (SVM), it is possible to obtain a model with 87.5% accuracy in the classification. In this case, the Lavender and Chestnut honeys were the ones that achieved a precision of 90% and 100% respectively. Full article

(This article belongs to the Section Precision and Digital Agriculture)

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17 pages, 7611 KiB

Open AccessEditor’s ChoiceArticle

Genome-Wide Identification, Characterization, and Expression Profiling of TaDUF668 Gene Family in Triticum aestivum

by Xiaohui Yin, Yi Yuan, Xiaowen Han, Shuo Han, Yiting Li, Dongfang Ma, Zhengwu Fang, Shuangjun Gong and Junliang Yin

Agronomy 2023, 13(8), 2178; https://doi.org/10.3390/agronomy13082178 - 20 Aug 2023

Cited by 7 | Viewed by 1842

Abstract

DUF668s, a plant-specific gene family, encode proteins containing domain of unknown function (DUF) domains. Despite their essential functions, there is a lack of insight into Triticum aestivum TaDUF668s. Here, 31 TaDUF668s were identified from the wheat genome; according to phylogenetic relationships, they [...] Read more.

DUF668s, a plant-specific gene family, encode proteins containing domain of unknown function (DUF) domains. Despite their essential functions, there is a lack of insight into Triticum aestivum TaDUF668s. Here, 31 TaDUF668s were identified from the wheat genome; according to phylogenetic relationships, they were named TaDUF668-01 to TaDUF668-31. All TaDUF668s were hydrophilic and unstable proteins. There were 22 TaDUF668s that showed subcellular localization in nucleus. Evolutionary analysis demonstrated that TaDUF668s had undergone strong purifying selection, and fragment duplication plays major role in TaDUF668 family expansion. Cis-element prediction displayed that over 90% of TaDUF668 promoter regions contain the growth and abiotic responsiveness element. Consistently, expression profiling showed that TaDUF668s were highly induced in five wheat growth and development stages, seven main different tissues, five abiotic stresses, and five pathogenic stresses. In total, 12 TaDUF668s were targeted by 20 miRNAs through the inhibition of translation and cleavage patterns. RT-qPCR results confirmed that the expression of six TaDUF668s was significantly regulated by NaCl, PEG, F. graminearum, and P. striiformis; nevertheless, the regulation patterns were different. In summary, through systematic identification, characterization, evolutionary analysis, and expression profiling, a comprehensive understanding of TaDUF668 has been obtained, which lays a foundation for further functional studies of TaDUF668. Full article

(This article belongs to the Special Issue Advances in Wheat Molecular Genetics and Genomics)

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20 pages, 34357 KiB

Open AccessEditor’s ChoiceArticle

Efficiency of Strawberry Cultivation under the Effect of Different Types of Plants in a Soilless System in the High-Altitude Regions of Southern Brazil

by Mário C. Palombini, Pedro Palencia, Jessé Marques S. J. Pavão and José L. T. Chiomento

Agronomy 2023, 13(8), 2179; https://doi.org/10.3390/agronomy13082179 - 20 Aug 2023

Cited by 1 | Viewed by 1926

Abstract

By analyzing the growth and development of different types of strawberry plants, the researchers were able to evaluate the interference with the horticultural potential of the cultivar ‘Albion’. The five treatments that have been studied corresponded to different types of strawberry plants: mini [...] Read more.

By analyzing the growth and development of different types of strawberry plants, the researchers were able to evaluate the interference with the horticultural potential of the cultivar ‘Albion’. The five treatments that have been studied corresponded to different types of strawberry plants: mini plants in trays with young roots, plants in trays with mature roots and an initial reduction of fertigation, plants in trays with mature roots, plants with bare roots, and plants in trays with mature roots preserved by the cold. In bags containing coconut fiber, the experiment was laid out in a randomized block design with three replications. The attributes evaluated were the total yield per plant, the total yield per plant with fruits above 10 g, the total yield per hectare, the total yield per hectare with fruits above 10 g, the average plant diameter, the average number of buds per plant, and the average number of stolons per plant. There were no significant effects among the plant types concerning yield production. Plants in cold-preserved trays with mature roots showed a higher number of buds than plants in trays with mature roots. Cold-preserved tray plants with mature roots produced the highest number of stolons, followed by bare-root plants. It is concluded that the types of strawberry seedlings did not influence the productive performance of the strawberry ‘Albion’ cultivar. However, cold-preserved tray plants with mature roots showed better vegetative performance, with a yield of a higher number of buds and stolons. However, the results were influenced by the agroclimatic conditions of the producing region; due to climatic interference in the behaviour of the plants about the factors studied, it is recommended to repeat the experiment for a better understanding of the objectives. Full article

(This article belongs to the Section Horticultural and Floricultural Crops)

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19 pages, 3862 KiB

Open AccessEditor’s ChoiceArticle

Phosphorus Mobility in Heavily Manured and Waterlogged Soil Cultivated with Ryegrass (Lolium multiflorum)

by Thidarat Rupngam, Aimé J. Messiga and Antoine Karam

Agronomy 2023, 13(8), 2168; https://doi.org/10.3390/agronomy13082168 - 18 Aug 2023

Cited by 5 | Viewed by 1641

Abstract

Extended waterlogging (WL) conditions in heavily manured soils can change soil phosphorus (P) dynamics. We assessed the effects of soil moisture regimes (field capacity (FC) and WL) and P rates on (i) dry matter (DM) yield and P offtake of ryegrass, (ii) changes [...] Read more.

Extended waterlogging (WL) conditions in heavily manured soils can change soil phosphorus (P) dynamics. We assessed the effects of soil moisture regimes (field capacity (FC) and WL) and P rates on (i) dry matter (DM) yield and P offtake of ryegrass, (ii) changes in soil Fe³⁺, Fe²⁺, and soil P, and (iii) risk of P leaching. The treatments were tested in a four-month greenhouse experiment using intact soil columns and annual ryegrass (Lolium multiflorum). The DM yield and P offtake were lower under WL compared with FC. The concentration of Fe³⁺ was 1984 mg kg⁻¹ (0–30 cm) under FC, but 1213 mg kg⁻¹ at 0–5 cm and 2024 mg kg⁻¹ at 25–30 cm depth under WL. The concentration of Fe²⁺ was 244 mg kg⁻¹ (0–30 cm) under FC, but 2897 at 0–5 cm and 687 mg kg⁻¹ at 25–30 cm under WL. The water extractable P (Pw) was 12.7 mg kg⁻¹ at 0–5 cm and 9.5 mg kg⁻¹ at 25–30 cm under FC, but 8.6 mg kg⁻¹ at 0–5 cm and 10.5 mg kg⁻¹ at 25–30 cm under WL. The P saturation index (PSI) was 27.2% at 0–5 cm and 17.4% at 25–30 cm under FC, but averaged 11.9% at 0–30 cm under WL. We can conclude that extended WL associated with flooding creates reducing conditions in the soil, thus decreasing the concentration of Fe³⁺, but increasing the concentrations of Fe²⁺ and the solubility of P which can exacerbate the risk of P loss with runoff and leaching. Full article

(This article belongs to the Section Soil and Plant Nutrition)

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17 pages, 2226 KiB

Open AccessEditor’s ChoiceArticle

Effects of Sowing Dates and Genotypes of Castor (Ricinus communis L.) on Seed Yield and Oil Content in the South Mediterranean Basin

by Valeria Cafaro, Silvio Calcagno, Cristina Patanè, Salvatore Luciano Cosentino and Giorgio Testa

Agronomy 2023, 13(8), 2167; https://doi.org/10.3390/agronomy13082167 - 18 Aug 2023

Cited by 1 | Viewed by 1244

Abstract

To evaluate the performance of dwarf castor hybrids (‘C1012’, ‘C857’, ‘C856’), compared to a local selected genotype, in four subsequent sowing dates (SW1, SW2, SW3, SW4), a trial was conducted at the experimental farm of the University of Catania (Sicily, Italy). The length [...] Read more.

To evaluate the performance of dwarf castor hybrids (‘C1012’, ‘C857’, ‘C856’), compared to a local selected genotype, in four subsequent sowing dates (SW1, SW2, SW3, SW4), a trial was conducted at the experimental farm of the University of Catania (Sicily, Italy). The length of the growing season decreased with the increase of the sowing date in the average genotypes from 160 to 94 days, respectively, for the first and the last sowing date. According to the RED—Renewable Energy Directive, the genotype ‘C856’ was the earliest (112 days), resulting in suitability as a catch crop for biomass production. The results showed that early spring sowings negatively impact dwarf hybrid production (1.2 and 1.5 Mg ha⁻¹ in SW1 and SW2, in the average of the three hybrids), which reached the highest yield in the third sowing date (2.0 Mg ha⁻¹), preferring warmer temperatures for the germination of seeds. On the contrary, the ‘Local’ genotype reached the highest yield (1.6 Mg ha⁻¹) in the first sowing date and linearly decreased in the subsequent ones. Nonetheless, the third sowing date positively influenced the oil content and the oil yield in all dwarf genotypes except the ‘Local’ genotype, which showed the highest oil yield in the first sowing date. Full article

(This article belongs to the Special Issue Agricultural Biomass for Bioenergy and Bioproducts)

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18 pages, 1949 KiB

Open AccessEditor’s ChoiceArticle

Characterization of Bioactive Phenolic Compounds in Seeds of Chilean Quinoa (Chenopodium quinoa Willd.) Germplasm

by Archis Pandya, Björn Thiele, Stephan Köppchen, Andres Zurita-Silva, Björn Usadel and Fabio Fiorani

Agronomy 2023, 13(8), 2170; https://doi.org/10.3390/agronomy13082170 - 18 Aug 2023

Cited by 4 | Viewed by 1338

Abstract

In recent years, quinoa (Chenopodium quinoa Willd.), an ancient Andean region crop, has received increased research attention because it is an excellent source of nutrients and also of bioactive phenolic compounds, which are potentially beneficial for human health. However, variation in the [...] Read more.

In recent years, quinoa (Chenopodium quinoa Willd.), an ancient Andean region crop, has received increased research attention because it is an excellent source of nutrients and also of bioactive phenolic compounds, which are potentially beneficial for human health. However, variation in the content and type of these metabolites in quinoa genetic resources remains, to a large extent, unexplored. We evaluated the composition of free and bound phenolic forms in the seeds of 111 Chilean quinoa accessions by using LC-DAD-MS/MS. The relative phenolic content ranged from 35.51 mg/100 g to 93.23 mg/100 g of seed dry weight. The free phenolic fraction accounted for 72% of the total phenolic content, while the bound fraction represented the remaining 28% of the total phenolic content. Our study also revealed a significant degree of variation in terms of individual phenolic compounds such as rutin, vanillic acid, quercetin, and their derivatives, which can have important implications for quinoa’s nutritional and functional properties. We conclude that our data reveal a significant phenotypic variation of bioactive phenolic content in the examined germplasm, which could be exploited in current and future genetic improvement programs in quinoa. Full article

(This article belongs to the Section Plant-Crop Biology and Biochemistry)

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14 pages, 2198 KiB

Open AccessEditor’s ChoiceArticle

Optimization of Protoplast Preparation System from Leaves and Establishment of a Transient Transformation System in Apium graveolens

by Jiageng Du, Huitao Zhang, Weilong Li, Xiaoyan Li, Zhuo Wang, Ying Zhang, Aisheng Xiong and Mengyao Li

Agronomy 2023, 13(8), 2154; https://doi.org/10.3390/agronomy13082154 - 17 Aug 2023

Cited by 5 | Viewed by 2041

Abstract

Protoplast culture and transformation technology offer a novel method for developing new plant varieties. Nonetheless, the effective preparation of protoplasts and transformation technology specific to celery has yet to be achieved. This study utilized celery seedling leaves as the primary materials to examine [...] Read more.

Protoplast culture and transformation technology offer a novel method for developing new plant varieties. Nonetheless, the effective preparation of protoplasts and transformation technology specific to celery has yet to be achieved. This study utilized celery seedling leaves as the primary materials to examine the key factors influencing protoplast isolation. The aim was to prepare leaf protoplasts with a high yield and of high quality and subsequently conduct transient gene transformation and expression. The findings indicated that the most effective procedure for isolating and purifying protoplasts was enzymatic digestion using an enzyme solution consisting of 2.0% cellulase, 0.1% pectolase, and 0.6 M mannitol for a duration of 8 h. Subsequently, the protoplasts were filtered through a 400-mesh sieve and purified through centrifugation at 200× g. Within this system, the overall protoplast yield was exceptionally high, reaching a viability rate of up to 95%. The transient transformation system yielded a maximum transformation efficiency of approximately 53%, as evaluated using the green fluorescent protein (GFP) as a reporter gene. The parameters of the transient transformation system were as follows: a protoplast concentration of 5 × 10⁵ cells·mL⁻¹, exogenous DNA concentration of 500 μg·mL⁻¹, final concentration of PEG4000 at 40%, and transformation duration of 15 min. The transient transformation system was also utilized to further analyze the protein localization characteristics of the celery transcription factor AgMYB80. The findings indicated that AgMYB80 predominantly localizes in the nucleus, thereby confirming the reliability and effectiveness of the transient transformation system. This study successfully established an efficient system for isolating, purifying, and transforming celery protoplasts, and will serve as a basis for future studies on molecular biology and gene function. Full article

(This article belongs to the Special Issue Recognition and Utilization of Natural Genetic Resources for Advances in Plant Biology through Genomics and Biotechnology—2nd Edition)

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11 pages, 2063 KiB

Open AccessEditor’s ChoiceArticle

Modified Storage Atmosphere Prevents the Degradation of Key Grain Quality Traits in Lentil

by Bhawana Bhattarai, Cassandra K. Walker, Ashley J. Wallace, James G. Nuttall, Graham Hepworth, Joe F. Panozzo, Debra L. Partington and Glenn J. Fitzgerald

Agronomy 2023, 13(8), 2160; https://doi.org/10.3390/agronomy13082160 - 17 Aug 2023

Cited by 2 | Viewed by 2142

Abstract

Lentil seed coat colour influences market value, whilst germination is associated with crop establishment and hydration capacity with optimal processing outcomes. Storing lentil grain assists growers in managing price fluctuations; however, exposure to oxygen at higher temperatures during extended storage degrades seed coat [...] Read more.

Lentil seed coat colour influences market value, whilst germination is associated with crop establishment and hydration capacity with optimal processing outcomes. Storing lentil grain assists growers in managing price fluctuations; however, exposure to oxygen at higher temperatures during extended storage degrades seed coat colour, germination, and hydration capacity. Depleting oxygen prevents such degradation in other crops; however, studies in lentil are limited. This study examined the effects of oxygen-depleted modified atmospheres and temperatures on seed coat colour, germination, and hydration capacity in two red lentil cultivars, PBA Hallmark and PBA Jumbo2, stored for 360 days. Small volumes of lentil grain were placed in aluminium laminated bags filled with nitrogen (N₂), carbon dioxide (CO₂), or air and stored at either 15 or 35 °C. At 35 °C in an air atmosphere, the lentil’s seed coat significantly (p = 0.05) darkened after 30 days of storage, whereas germination and hydration capacities decreased after 60 days regardless of cultivar. In contrast, N₂ and CO₂ atmospheres maintained initial seed coat colour, germination, and hydration capacities in both cultivars throughout the study period regardless of temperature. Storing lentil grain in an oxygen-depleted modified atmosphere may assist to maximise returns to grower and maintain key quality traits. Full article

(This article belongs to the Section Horticultural and Floricultural Crops)

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26 pages, 6310 KiB

Open AccessEditor’s ChoiceArticle

Real-Time Localization and Colorful Three-Dimensional Mapping of Orchards Based on Multi-Sensor Fusion Using Extended Kalman Filter

by Yibo Zhang, Hao Sun, Fanhang Zhang, Baohua Zhang, Shutian Tao, Haitao Li, Kaijie Qi, Shaoling Zhang, Seishi Ninomiya and Yue Mu

Agronomy 2023, 13(8), 2158; https://doi.org/10.3390/agronomy13082158 - 17 Aug 2023

Cited by 8 | Viewed by 2039

Abstract

To realize autonomous navigation and intelligent management in orchards, vehicles require real-time positioning and globally consistent mapping of surroundings with sufficient information. However, the unstructured and unstable characteristics of orchards present challenges for accurate and stable localization and mapping. This study proposes a [...] Read more.

To realize autonomous navigation and intelligent management in orchards, vehicles require real-time positioning and globally consistent mapping of surroundings with sufficient information. However, the unstructured and unstable characteristics of orchards present challenges for accurate and stable localization and mapping. This study proposes a framework fusing LiDAR, visual, and inertial data by using the extended Kalman filter (EKF) to achieve real-time localization and colorful LiDAR point-cloud mapping in orchards. First, the multi-sensor data were integrated into a loosely-coupled framework based on the EKF to improve the pose estimation, with the pose estimation from LiDAR and gyroscope acting as the predictions, while that from visual-inertial odometry acting as the observations. Then, the Loam_Livox algorithm was enhanced by incorporating color from the image into the LiDAR point cloud, enabling the real-time construction of a three-dimensional colorful map of the orchard. The method demonstrates a high accuracy for localization in different motion trajectories (average RMSE: 0.3436) and different scenarios (average RMSE: 0.1230) and clear and efficient construction of three-dimensional colorful mapping, taking only 75.01 ms in localization and mapping for a frame of LiDAR point cloud. This indicates the proposed method has a great potential for the autonomous navigation of agricultural vehicles. Full article

(This article belongs to the Section Precision and Digital Agriculture)

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18 pages, 7238 KiB

Open AccessEditor’s ChoiceArticle

Research on Insect Pest Identification in Rice Canopy Based on GA-Mask R-CNN

by Sitao Liu, Shenghui Fu, Anrui Hu, Pan Ma, Xianliang Hu, Xinyu Tian, Hongjian Zhang and Shuangxi Liu

Agronomy 2023, 13(8), 2155; https://doi.org/10.3390/agronomy13082155 - 17 Aug 2023

Cited by 6 | Viewed by 1706

Abstract

Aiming at difficult image acquisition and low recognition accuracy of two rice canopy pests, rice stem borer and rice leaf roller, we constructed a GA-Mask R-CNN (Generative Adversarial Based Mask Region Convolutional Neural Network) intelligent recognition model for rice stem borer and rice [...] Read more.

Aiming at difficult image acquisition and low recognition accuracy of two rice canopy pests, rice stem borer and rice leaf roller, we constructed a GA-Mask R-CNN (Generative Adversarial Based Mask Region Convolutional Neural Network) intelligent recognition model for rice stem borer and rice leaf roller, and we combined it with field monitoring equipment for them. Firstly, based on the biological habits of rice canopy pests, a variety of rice pest collection methods were used to obtain the images of rice stem borer and rice leaf roller pests. Based on different segmentation algorithms, the rice pest images were segmented to extract single pest samples. Secondly, the bug generator based on a generative adversarial network strategy improves the sensitivity of the classification network to the bug information, generates the pest information images in the real environment, and obtains the sample dataset for deep learning through multi-way augmentation. Then, through adding channel attention ECA module in Mask R-CNN and improving the connection of residual blocks in the backbone network ResNet101, the recognition accuracy of the model is improved. Finally, the GA-Mask R-CNN model was tested on a multi-source dataset with an average precision (AP) of 92.71%, recall (R) of 89.28% and a balanced score F1 of 90.96%. The average precision, recall, and balanced score F1 are improved by 7.07, 7.65, and 8.83%, respectively, compared to the original Mask R-CNN. The results show that the GA-Mask R-CNN model performance indexes are all better than the Mask R-CNN, the Faster R-CNN, the SSD, the YOLOv5, and other network models, which can provide technical support for remote intelligent monitoring of rice pests. Full article

(This article belongs to the Special Issue In-Field Detection and Monitoring Technology in Precision Agriculture)

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23 pages, 3966 KiB

Open AccessEditor’s ChoiceArticle

Effects of Pedoclimate and Agronomical Management on Yield and Quality of Common Wheat Varieties (Triticum aestivum L.) in Afghanistan

by Qudratullah Soofizada, Antonio Pescatore, Simone Orlandini and Marco Napoli

Agronomy 2023, 13(8), 2152; https://doi.org/10.3390/agronomy13082152 - 16 Aug 2023

Cited by 1 | Viewed by 2091

Abstract

The lower common wheat productivity and quality are major constraints in Afghanistan. The objectives of this study were to (1) quantify the effect of soil and climatic parameters on the yield and quality of common wheat and (2) investigate the response of different [...] Read more.

The lower common wheat productivity and quality are major constraints in Afghanistan. The objectives of this study were to (1) quantify the effect of soil and climatic parameters on the yield and quality of common wheat and (2) investigate the response of different wheat varieties to different N and P fertilization rates, to improve the yield and quality of common wheat. Three wheat varieties (DLN7, ZRDN, and KBL13), three phosphorus levels (PL) at 60, 90, and 120 kg P₂O₅ ha⁻¹, and three nitrogen ratios (NP) at 1:1, 1.25:1, and 1.5:1, respectively, in four locations (L), were evaluated. The higher average grain yield (GY), straw yield (SY), and starch yield (STY) were obtained with DLN7, followed by KBL13 and ZRDN, for all locations. As PL increased, GY, SY, protein yield (PY), and STY significantly increased in all locations. The PL significantly affected protein content (PC), gluten content (GC), and dough strength (W). The NP significantly improved PC, GC, and PY. Starch (ST), STY, and amylopectin (AP) increased significantly with increasing PL. The amylose to AP ratio increased significantly with increasing NP ratios. The findings show that at NP1/PL120, GY, SY, ST, and AP improved significantly, while at NP1.5:1/PL120, PC and GC improved significantly. Full article

(This article belongs to the Section Farming Sustainability)

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13 pages, 5906 KiB

Open AccessEditor’s ChoiceArticle

Design of an Agrivoltaic System with Building Integrated Photovoltaics

by Sojung Kim and Sumin Kim

Agronomy 2023, 13(8), 2140; https://doi.org/10.3390/agronomy13082140 - 16 Aug 2023

Cited by 4 | Viewed by 1875

Abstract

Building integrated photovoltaics (BIPVs) are becoming popular as building elements such as windows, roofs, and outer walls. Because BIPVs have both a construction material function and an electricity generation function, they are a promising alternative to sustainable buildings. This study aims to propose [...] Read more.

Building integrated photovoltaics (BIPVs) are becoming popular as building elements such as windows, roofs, and outer walls. Because BIPVs have both a construction material function and an electricity generation function, they are a promising alternative to sustainable buildings. This study aims to propose a novel agrivoltaic system design that produces crops underneath photovoltaic (PV) modules. Regarding the fact that crop growth is significantly influenced by shading from PV modules, roof BIPVs with different shading ratios can lead to increased crop productivity. Thus, BIPV design should be investigated based on the performance estimation and feasibility evaluation of different shading ratios in an agrivoltaic system. To this end, electricity generation and crop production models are devised by polynomial regression (PR) based on field experiment data collected from the agrivoltaic system at the Agricultural Research Service Center in Naju-si, South Korea. The experiment shows that a shading ratio of 30% allows for the maximization of the profitability of electricity and soybean production in an agrivoltaic system equipped with BIPVs. As a result, this research will contribute to implementing an agrivoltaic system with various BIPVs. Full article

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11 pages, 4325 KiB

Open AccessEditor’s ChoiceArticle

Long-Term Increases in Continuous Cotton Yield and Soil Fertility following the Application of Cotton Straw and Organic Manure

by Xiaojing Chen, Kaipeng Xi, Zhiping Yang, Jinjing Lu, Qiang Zhang, Bin Wang, Ke Wang and Jundong Shi

Agronomy 2023, 13(8), 2133; https://doi.org/10.3390/agronomy13082133 - 15 Aug 2023

Cited by 5 | Viewed by 1470

Abstract

Long-term continuous cotton cropping results in a significant decrease in soil quality and soil organic carbon, threatening cotton yield. The application of organic amendments is considered an effective management practice for the sustainability of soil productivity and often increases yield. However, the sustainable [...] Read more.

Long-term continuous cotton cropping results in a significant decrease in soil quality and soil organic carbon, threatening cotton yield. The application of organic amendments is considered an effective management practice for the sustainability of soil productivity and often increases yield. However, the sustainable improvement in the cotton yield, stability, and soil fertility over time resulting from organic amendments with cotton straw and organic manure still need to be confirmed with research, especially under a continuous cotton cropping system. This study evaluated the effect of 12 years of consecutive application of cotton straw and organic manure on continuous cotton yield, soil quality, and soil organic carbon. Four treatments, i.e., chemical N and P fertilizers (NP, control), NP plus cotton straw (NPS), NP plus manure (NPM), and NP plus cotton straw and manure (NPSM), were carried out. The results indicated that the addition of cotton straw and organic manure improved the temporal stability and sustainability of cotton yield. The combination of cotton straw and organic manure resulted in the greatest improvement, increasing the average annual cotton yield by 32.28% compared with the control (NP). A correlation analysis revealed that cotton yield was closely related to soil quality and soil organic carbon. The application of cotton straw and organic manure increased cotton yield by enhancing soil fertility, especially the quantity and quality of soil organic carbon, which improved the supply and cycling of soil nutrients and benefited the stability and sustainability of the cotton yield. Reusing cotton straw and organic manure could improve the sustainable productivity of cotton soil and provide additional environmental value as well as having great potential for cleaner and sustainable cotton production. Full article

(This article belongs to the Section Soil and Plant Nutrition)

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17 pages, 3668 KiB

Open AccessEditor’s ChoiceArticle

Organic Material Addition Optimizes Soil Structure by Enhancing Copiotrophic Bacterial Abundances of Nitrogen Cycling Microorganisms in Northeast China

by Yang Yue, Xiangwei Gong, Yongzhao Zheng, Ping Tian, Ying Jiang, Hongyu Zhang and Hua Qi

Agronomy 2023, 13(8), 2108; https://doi.org/10.3390/agronomy13082108 - 11 Aug 2023

Cited by 2 | Viewed by 1255

Abstract

Using organic fertilizer and maize straw as friendly amendment measures is effective for altering soil nitrogen (N) cycling in farmlands. However, the synthetical effects of organic fertilizer combined with straw returning on soil quality remain unknown, especially in response to soil nitrification and [...] Read more.

Using organic fertilizer and maize straw as friendly amendment measures is effective for altering soil nitrogen (N) cycling in farmlands. However, the synthetical effects of organic fertilizer combined with straw returning on soil quality remain unknown, especially in response to soil nitrification and denitrification microorganisms. We set up an experiment in brunisolic soil from Northeast China, mainly including four treatments: CK (no addition without traditional chemical fertilizer), O (organic fertilizer application), S (straw returning), and OS (organic fertilizer combined with straw returning). The soil nitrification and denitrification microorganisms were further investigated using high-throughput sequencing. Our results show that, compared to CK, the soil water content, field capacity, macroaggregates with a diameter > 0.25 mm, mean weight diameter, total carbon, total nitrogen, ammonium, nitrate, microbial biomass carbon, and microbial biomass nitrogen were significantly improved, and penetration resistance was reduced in a 0–20 cm soil layer under O, S, and OS treatments. Moreover, OS treatment effectively increased the available potassium and available phosphorus content and decreased the three-phase R-value. The application of organic fertilizer and straw effectively optimized the soil structure, especially the OS treatment. Compared to CK, O, S, and OS treatments had a higher abundance of ammonia-oxidizing archaea (AOA) and further enhanced the alpha diversity and lower abundance of ammonia-oxidizing bacteria (AOB) and nirK-, nirS-, and nosZ-type denitrifying microbes. AOA and nirK were the key drivers of the ammonia oxidation process and nitrite reduction process, respectively. Meanwhile, the application of organic fertilizer and straw regulated the relative abundance of Nitrososphaeria (AOA), Gammaproteobacteria (nirK and nirS), Alphaproteobacteria (nirK), and Betaproteobacteria (nirS) in the soil. Organic fertilizer and straw returning regulated the soil structure by enhancing the abundance of Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria in the nitrifying and denitrifying microorganism communities. Taken together, OS treatment was a suitable straw-returning practice for optimizing the nutrient balance of the farmland ecosystem in Northeast China. However, this study did not determine how to reduce traditional nitrogen fertilizer applications under organic fertilizer application and straw returning; therefore, we aim to carry out related research in future works. Full article

(This article belongs to the Section Farming Sustainability)

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24 pages, 8774 KiB

Open AccessEditor’s ChoiceArticle

A Lightweight Cherry Tomato Maturity Real-Time Detection Algorithm Based on Improved YOLOV5n

by Congyue Wang, Chaofeng Wang, Lele Wang, Jing Wang, Jiapeng Liao, Yuanhong Li and Yubin Lan

Agronomy 2023, 13(8), 2106; https://doi.org/10.3390/agronomy13082106 - 11 Aug 2023

Cited by 12 | Viewed by 2674

Abstract

To enhance the efficiency of mechanical automatic picking of cherry tomatoes in a precision agriculture environment, this study proposes an improved target detection algorithm based on YOLOv5n. The improvement steps are as follows: First, the K-means++ clustering algorithm is utilized to update the [...] Read more.

To enhance the efficiency of mechanical automatic picking of cherry tomatoes in a precision agriculture environment, this study proposes an improved target detection algorithm based on YOLOv5n. The improvement steps are as follows: First, the K-means++ clustering algorithm is utilized to update the scale and aspect ratio of the anchor box, adapting it to the shape characteristics of cherry tomatoes. Secondly, the coordinate attention (CA) mechanism is introduced to expand the receptive field range and reduce interference from branches, dead leaves, and other backgrounds in the recognition of cherry tomato maturity. Next, the traditional loss function is replaced by the bounding box regression loss with dynamic focusing mechanism (WIoU) loss function. The outlier degree and dynamic nonmonotonic focusing mechanism are introduced to address the boundary box regression balance problem between high-quality and low-quality data. This research employs a self-built cherry tomato dataset to train the target detection algorithms before and after the improvements. Comparative experiments are conducted with YOLO series algorithms. The experimental results indicate that the improved model has achieved a 1.4% increase in both precision and recall compared to the previous model. It achieves an average accuracy mAP of 95.2%, an average detection time of 5.3 ms, and a weight file size of only 4.4 MB. These results demonstrate that the model fulfills the requirements for real-time detection and lightweight applications. It is highly suitable for deployment in embedded systems and mobile devices. The improved model presented in this paper enables real-time target recognition and maturity detection for cherry tomatoes. It provides rapid and accurate target recognition guidance for achieving mechanical automatic picking of cherry tomatoes. Full article

(This article belongs to the Special Issue Applications of Deep Learning in Smart Agriculture—Volume II)

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13 pages, 1537 KiB

Open AccessEditor’s ChoiceArticle

The Impact of Data Envelopment Analysis on Effective Management of Inputs: The Case of Farms Located in the Regional Unit of Pieria

by Asimina Kouriati, Anna Tafidou, Evgenia Lialia, Angelos Prentzas, Christina Moulogianni, Eleni Dimitriadou and Thomas Bournaris

Agronomy 2023, 13(8), 2109; https://doi.org/10.3390/agronomy13082109 - 11 Aug 2023

Cited by 1 | Viewed by 1727

Abstract

Technical efficiency is considered a useful advisory tool for managers whose main goal is to maximize profit and minimize costs. Data envelopment analysis is a widely accepted methodology for technical efficiency estimation in the sector of agriculture. For that reason and with the [...] Read more.

Technical efficiency is considered a useful advisory tool for managers whose main goal is to maximize profit and minimize costs. Data envelopment analysis is a widely accepted methodology for technical efficiency estimation in the sector of agriculture. For that reason and with the view to extract useful conclusions regarding farmers’ effective management of inputs, this study aims to present the DEA method through its implementation in a set of farms located in the regional unit of Pieria. To conduct this analysis, relevant data were collected through a survey in which 40 farms participated. The output variable was chosen to be each farm’s total amount of sales, while the inputs were selected in a way to represent the main factors of production, such as (1) land in acres, (2) labor in hours, and (3) variable costs in EUR. The results showed that the examined farms need to reduce the inputs used by 34.6% to operate more efficiently from the point of view of the CRS model. Therefore, farmers should be motivated to reduce the inputs used, something that can be done through the provision of specialized advisory services. This will, of course, be helped by both the local authorities and the policies of the country in which the rational use of inputs seems to be necessary. This study may contribute to the relevant literature, agriculture, and the area since management suggestions are formulated for the farmers of Pieria’s regional unit. Full article

(This article belongs to the Special Issue Design and Statistical Analysis in Agricultural, Biological and Environmental Sciences)

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33 pages, 6258 KiB

Open AccessEditor’s ChoiceArticle

Determination of Characteristics and Establishment of Discrete Element Model for Whole Rice Plant

by Changsu Xu, Fudong Xu, Han Tang and Jinwu Wang

Agronomy 2023, 13(8), 2098; https://doi.org/10.3390/agronomy13082098 - 10 Aug 2023

Cited by 3 | Viewed by 1809

Abstract

In order to accurately establish a discrete element model for the whole plant flexibility of upright rice during the harvesting period, several physical characteristics, such as geometric features, moisture content, and density, of the entire rice plant were measured, along with frictional properties, [...] Read more.

In order to accurately establish a discrete element model for the whole plant flexibility of upright rice during the harvesting period, several physical characteristics, such as geometric features, moisture content, and density, of the entire rice plant were measured, along with frictional properties, such as the static and rolling friction coefficients, and mechanical properties, including the elastic modulus and restitution coefficient. A flexible and upright discrete element model of the rice plant was established using the DEM method based on the Hertz–Mindlin (no slip) and Hertz–Mindlin with bonding mechanical models. The parameters were optimized through Plackett–Burman screening experiments, steepest ascent experiments, and Box–Behnken optimization experiments to accurately determine the discrete element model parameters of each component of the rice plant. The calibration process of the contact parameters between rice grains and steel was analyzed in detail as an example, resulting in a calibration error of 0.68% for the natural repose angle. Taking the calibration of the contact parameters between the main stem and steel as an example, a detailed analysis of the calibration process was conducted. The calibration resulted in a calibration error of 2.76% for the natural repose angle and 2.33% for deflection. This study lays the foundation for understanding the mechanical response of rice and machinery when they are coupled together. Additionally, it provides valuable references for establishing discrete element models of plant species other than rice. Full article

(This article belongs to the Special Issue Agricultural Equipment and Mechanization in Crop Production)

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17 pages, 3708 KiB

Open AccessEditor’s ChoiceArticle

Genome-Wide Association Analysis Reveals the Gene Loci of Yield Traits under Drought Stress at the Rice Reproductive Stage

by Nansheng Wang, Zhiyuan Gao, Wanyang Zhang, Yingzhi Qian, Di Bai, Xueyu Zhao, Yaling Bao, Zhenzhen Zheng, Xingmeng Wang, Jianfeng Li, Wensheng Wang and Yingyao Shi

Agronomy 2023, 13(8), 2096; https://doi.org/10.3390/agronomy13082096 - 10 Aug 2023

Cited by 3 | Viewed by 1576

Abstract

Drought is an important factor limiting the growth and development of rice and thereby seriously affects rice yield. The problem may be effectively solved by dissecting the drought-resistance mechanism of rice, creating excellent drought-resistant germplasm, and mining new drought-resistant genes. In this study, [...] Read more.

Drought is an important factor limiting the growth and development of rice and thereby seriously affects rice yield. The problem may be effectively solved by dissecting the drought-resistance mechanism of rice, creating excellent drought-resistant germplasm, and mining new drought-resistant genes. In this study, 305 accessions (189 Xian, 104 Geng, 5 Aus, and 7 Basmati) were used to identify drought-related phenotypes such as grain yield per plant (GYP), grain number per panicle (GNP), panicle number per plant (PNP), and plant height (PH) under two-year drought stress. The 2017 GYP and 2018 GNP were Xian max, 2018 GYP, 2017 GNP, 2017 and 2018 PNP, and 2018 PH were Basmati max, and only the 2017 PH was Geng max. The population genetic diversity and population structure were analyzed by combining 404,388 single nucleotide polymorphism (SNP) markers distributed on 12 chromosomes. A total of 42 QTLs with significant correlations was identified, among which 10 were adjacent to the loci reported to be associated with drought resistance. Four candidate genes, LOC_Os03g48890, LOC_Os04g35114, LOC_Os11g45924, and LOC_Os06g38950, were identified by functional annotation and haplotype analysis. The R² of qGYP3.1 was 11.53%, the R² of qGNP4.2 was 12.09%, the R² of qPNP11.1 was 10.01%, and the R² of qPH6.1 was 13.06%. The results have an important theoretical significance and practical application value for the improvement of drought resistance in rice. Full article

(This article belongs to the Special Issue Crop Biology and Breeding under Environmental Stress)

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16 pages, 722 KiB

Open AccessEditor’s ChoiceArticle

Brewer’s Spent Grain with Yeast Amendment Shows Potential for Anaerobic Soil Disinfestation of Weeds and Pythium irregulare

by Danyang Liu, Jayesh Samtani, Charles Johnson, Xuemei Zhang, David M. Butler and Jeffrey Derr

Agronomy 2023, 13(8), 2081; https://doi.org/10.3390/agronomy13082081 - 8 Aug 2023

Cited by 1 | Viewed by 1822

Abstract

Anaerobic soil disinfestation (ASD) is a promising alternative to chemical fumigation for controlling soilborne plant pathogens and weeds. This study investigated the impact of brewer’s spent grain (BSG), a locally available carbon source, on various weed species and the oomycete pathogen Pythium irregulare [...] Read more.

Anaerobic soil disinfestation (ASD) is a promising alternative to chemical fumigation for controlling soilborne plant pathogens and weeds. This study investigated the impact of brewer’s spent grain (BSG), a locally available carbon source, on various weed species and the oomycete pathogen Pythium irregulare in ASD. Two greenhouse studies were conducted using BSG and yeast at full and reduced rates in a completely randomized design with four replicates and two runs per study. In both studies, ASD treatments significantly decreased the seed viability of all weed species and the Pythium irregulare inoculum, while promoting higher cumulative anaerobicity compared to the non-treated control. The addition of yeast had a notable effect when combined with BSG but not with rice bran. When used in reduced carbon rates, yeast supplementation enhanced the efficacy of BSG, providing comparable control to the full rate for most weed species, including redroot pigweed, white clover, and yellow nutsedge. Interestingly, no ASD treatment affected the soil temperature. Furthermore, BSG treatments caused higher concentrations of volatile fatty acids compared to ASD with rice bran and the non-treated control. This finding suggests that the inclusion of yeast in ASD shows potential for reducing the carbon input required for effective soil disinfestation. Full article

(This article belongs to the Special Issue Anaerobic Soil Disinfestation: A Tool for Non-Fumigant-Based Integrated Soil-Borne Disease and Pest Management)

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19 pages, 6205 KiB

Open AccessEditor’s ChoiceArticle

The Study of the Impact of Complex Foliar Fertilization on the Yield and Quality of Sunflower Seeds (Helianhtus annuus L.) by Principal Component Analysis

by Florin Crista, Isidora Radulov, Florinel Imbrea, Dan Nicolae Manea, Marius Boldea, Iosif Gergen, Anișoara Aurelia Ienciu and Ioan Bănățean Dunea

Agronomy 2023, 13(8), 2074; https://doi.org/10.3390/agronomy13082074 - 7 Aug 2023

Cited by 3 | Viewed by 2174

Abstract

The aim of the paper is to assess the impact of Foliar Fertilizations (FF) on the yield and quality of sunflower seeds. This research was carried out in the agricultural years of 2019–2021 in the experimental field of the university. The method of [...] Read more.

The aim of the paper is to assess the impact of Foliar Fertilizations (FF) on the yield and quality of sunflower seeds. This research was carried out in the agricultural years of 2019–2021 in the experimental field of the university. The method of planting in the field was carried out in subdivided plots with three repetitions and six fertilization options. The experimental variants were as follows: Control (Mt), V1—FF 10:10:10+ME (microelements), V2—FF 8:10:0+8B (Boron)+ME, V3—FF 15:0:0+2S (Sulfur)+1B+ME, V4—FF 15:0:0+4B+ME, and V5—FF 8:8:8+ME. FF treatments were carried out in the vegetation phases specific to the sunflower crop. These varied from 2–6 L ha⁻¹, depending on the chemical composition of the product. The application of treatments with FF to the sunflower culture positively influenced both production and its quality expressed by specific quality indices, namely the content of proteins, lipids, carbohydrates, fibers, and minerals. The results were discussed not only in view of classical statistics but also using the Principal Components Analysis (PCA), which allows a more complex evaluation of the effects of foliar treatments on the production and quality of sunflower seeds. Full article

(This article belongs to the Special Issue The Role of Macro‐ and Micronutrient in Plant Growth and Development)

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24 pages, 17026 KiB

Open AccessEditor’s ChoiceArticle

Hyperspectral Estimation of Chlorophyll Content in Apple Tree Leaf Based on Feature Band Selection and the CatBoost Model

by Yu Zhang, Qingrui Chang, Yi Chen, Yanfu Liu, Danyao Jiang and Zijuan Zhang

Agronomy 2023, 13(8), 2075; https://doi.org/10.3390/agronomy13082075 - 7 Aug 2023

Cited by 11 | Viewed by 2081

Abstract

Leaf chlorophyll content (LCC) is a crucial indicator of nutrition in apple trees and can be applied to assess their growth status. Hyperspectral data can provide an important means for detecting the LCC in apple trees. In this study, hyperspectral data and the [...] Read more.

Leaf chlorophyll content (LCC) is a crucial indicator of nutrition in apple trees and can be applied to assess their growth status. Hyperspectral data can provide an important means for detecting the LCC in apple trees. In this study, hyperspectral data and the measured LCC were obtained. The original spectrum (OR) was pretreated using some spectral transformations. Feature bands were selected based on the competitive adaptive reweighted sampling (CARS) algorithm, random frog (RF) algorithm, elastic net (EN) algorithm, and the EN-RF and EN-CARS algorithms. Partial least squares regression (PLSR), random forest regression (RFR), and the CatBoost algorithm were used before and after grid search parameter optimization to estimate the LCC. The results revealed the following: (1) The spectrum after second derivative (SD) transformation had the highest correlation with LCC (–0.929); moreover, the SD-based model produced the highest accuracy, making SD an effective spectrum pretreatment method for apple tree LCC estimation. (2) Compared with the single band selection algorithm, the EN-RF algorithm had a better dimension reduction effect, and the modeling accuracy was generally higher. (3) CatBoost after grid search optimization had the best estimation effect, and the validation set of the SD-EN-CARS-CatBoost model after parameter optimization had the highest estimation accuracy, with the determination coefficient (R²), root mean square error (RMSE), and relative prediction deviation (RPD) reaching 0.923, 2.472, and 3.64, respectively. As such, the optimized SD-EN-CARS-CatBoost model, with its high accuracy and reliability, can be used to monitor the growth of apple trees, support the intelligent management of apple orchards, and facilitate the economic development of the fruit industry. Full article

(This article belongs to the Special Issue Art of Spectra: At the Crossroad of Agriculture and Remote Sensing Disciplines)

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18 pages, 2835 KiB

Open AccessEditor’s ChoiceArticle

Optimizing Controlled Environmental Agriculture for Strawberry Cultivation Using RL-Informer Model

by Yuze Lu, Mali Gong, Jing Li and Jianshe Ma

Agronomy 2023, 13(8), 2057; https://doi.org/10.3390/agronomy13082057 - 3 Aug 2023

Cited by 4 | Viewed by 1821

Abstract

Controlled Environmental Agriculture (CEA) has gained a lot of attention in recent years, mainly because of its ability to overcome extreme weather problems and ensure food safety. CEA can meet the full growth state monitoring of the crop period; however, the optimization of [...] Read more.

Controlled Environmental Agriculture (CEA) has gained a lot of attention in recent years, mainly because of its ability to overcome extreme weather problems and ensure food safety. CEA can meet the full growth state monitoring of the crop period; however, the optimization of the growing environment is still limited by the algorithm defects. In this article, we present an optimization method of growing environment based on reinforcement learning, Q-learning and the time-series prediction model Informer. This approach is demonstrated for the first time as far as we know. By employing Informer, we predicted the growth of strawberries based on current environmental variables and plant status. The prediction results served as a reward to motivate Q-learning, guiding it to make optimal modifications to the environment in real-time. This approach aimed to achieve the optimal cultivation environment continuously. Two groups of validation experiments were conducted based on different cultivation objectives: “obtaining the most stolons” and “obtaining the highest fruit count”. Compared to the empirically planted groups, the experimental groups using the RL-Informer model achieved yield increases of 17.81% and 20.78%, respectively. These experiments highlight the outstanding performance of the proposed RL-Informer model in real-time prediction and modification of environmental variables. Full article

(This article belongs to the Section Precision and Digital Agriculture)

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15 pages, 2789 KiB

Open AccessEditor’s ChoiceArticle

Regulatory Effect of Light and Rhizobial Inoculation on the Root Architecture and Plant Performance of Pasture Legumes

by Irene Ariadna De Lara-Del Rey and María A. Pérez-Fernández

Agronomy 2023, 13(8), 2058; https://doi.org/10.3390/agronomy13082058 - 3 Aug 2023

Cited by 2 | Viewed by 1068

Abstract

Rhizobial associations with leguminous plants are some of the most important symbioses on Earth, and they have economic relevance in agriculture. Because their interactions are positive and have advantages for both partners, nitrogen-fixing rhizobia also demand significant carbohydrate allocation in exchange for key [...] Read more.

Rhizobial associations with leguminous plants are some of the most important symbioses on Earth, and they have economic relevance in agriculture. Because their interactions are positive and have advantages for both partners, nitrogen-fixing rhizobia also demand significant carbohydrate allocation in exchange for key nutrients, and this demand is reflected in the anatomy of roots. In the current scenario of climate change, rhizobia–legume interactions can be affected, and plants may need to compensate for carbon loss when light availability is not correct. Under such conditions, roots can modify their anatomy to accommodate symbionts’ needs, and the outcome of an interaction can switch from mutualism to parasitism, resulting in changes in root allocation. We experimented with two legume species originating from well-irradiated environments (Coronilla juncea L. and Ornithopus compressus L.) and two species from shaded environments (Trifolium repens L. and Vicia sativa L.). We applied high radiation, intermediate radiation, and low radiation to two treatments of microbial inoculation (inoculation and control). After an incubation period of 105 days, we quantified the root area, size, and complexity, as well as the nodule production and mass, plant relative growth, and below-ground allocation. For plants originating in shaded environments, nodulation, root complexity, and below-ground allocation were enhanced in inoculated plants when they were transferred to conditions of high irradiance. Strikingly, plants from environments exposed to high light radiation were less plastic when exposed to changing light availability, and the symbionts were less beneficial than expected in stress-free environments. Our study proved that the stress imposed on plants due to high irradiance is overcome when plants are inoculated, and the positive effect is more evident in plants that are usually grown in shaded environments (e.g., Trifolium repens and Vicia sativa). Full article

(This article belongs to the Special Issue The Effects of Inoculation with Microorganisms on Plant Nutrition, Yield and Quality)

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20 pages, 8031 KiB

Open AccessEditor’s ChoiceArticle

Citrus Tree Canopy Segmentation of Orchard Spraying Robot Based on RGB-D Image and the Improved DeepLabv3+

by Xiuyun Xue, Qin Luo, Maofeng Bu, Zhen Li, Shilei Lyu and Shuran Song

Agronomy 2023, 13(8), 2059; https://doi.org/10.3390/agronomy13082059 - 3 Aug 2023

Cited by 7 | Viewed by 1804

Abstract

The accurate and rapid acquisition of fruit tree canopy parameters is fundamental for achieving precision operations in orchard robotics, including accurate spraying and precise fertilization. In response to the issue of inaccurate citrus tree canopy segmentation in complex orchard backgrounds, this paper proposes [...] Read more.

The accurate and rapid acquisition of fruit tree canopy parameters is fundamental for achieving precision operations in orchard robotics, including accurate spraying and precise fertilization. In response to the issue of inaccurate citrus tree canopy segmentation in complex orchard backgrounds, this paper proposes an improved DeepLabv3+ model for fruit tree canopy segmentation, facilitating canopy parameter calculation. The model takes the RGB-D (Red, Green, Blue, Depth) image segmented canopy foreground as input, introducing Dilated Spatial Convolution in Atrous Spatial Pyramid Pooling to reduce computational load and integrating Convolutional Block Attention Module and Coordinate Attention for enhanced edge feature extraction. MobileNetV3-Small is utilized as the backbone network, making the model suitable for embedded platforms. A citrus tree canopy image dataset was collected from two orchards in distinct regions. Data from Orchard A was divided into training, validation, and test set A, while data from Orchard B was designated as test set B, collectively employed for model training and testing. The model achieves a detection speed of 32.69 FPS on Jetson Xavier NX, which is six times faster than the traditional DeepLabv3+. On test set A, the mIoU is 95.62%, and on test set B, the mIoU is 92.29%, showing a 1.12% improvement over the traditional DeepLabv3+. These results demonstrate the outstanding performance of the improved DeepLabv3+ model in segmenting fruit tree canopies under different conditions, thus enabling precise spraying by orchard spraying robots. Full article

(This article belongs to the Special Issue Precision Operation Technology and Intelligent Equipment in Farmland)

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14 pages, 3528 KiB

Open AccessEditor’s ChoiceArticle

Contribution of Glutathione Transferases in the Selective and Light-Dependent Effect of Flumioxazin on Winter Wheat (Triticum aestivum L.) and Its Typical Weed Common Poppy (Papaver rhoeas L.)

by Ágnes Gallé, Máté Farkas, Alina Pelsőczi, Zalán Czékus, András Kukri, Zita Dorner, Attila Ördög, Jolán Csiszár, Krisztina Bela and Péter Poór

Agronomy 2023, 13(8), 2053; https://doi.org/10.3390/agronomy13082053 - 2 Aug 2023

Cited by 2 | Viewed by 1217

Abstract

Glutathione transferases (GSTs) are enzymes that catalyse modifications and conjugations of a range of organic and often cytotoxic compounds. GST enzymes with many functions—such as their conjugation activity against herbicides and their metabolites—can be induced and show light and circadian determination. The enzyme [...] Read more.

Glutathione transferases (GSTs) are enzymes that catalyse modifications and conjugations of a range of organic and often cytotoxic compounds. GST enzymes with many functions—such as their conjugation activity against herbicides and their metabolites—can be induced and show light and circadian determination. The enzyme family, which is widespread in its function, also shows great diversity in its structure, which has been linked to its enzyme kinetic characteristics and physiological role at many points. In this study, we aimed to find out the role of different glutathione transferases in the herbicide responses to flumioxazin, as well as to determine how the antioxidant and detoxification response to herbicide treatment changes in the presence and absence of light. One of the herbicide treatments was carried out during the light period in the morning (9:00 a.m.), and the other before the end of the dark period (4:00 a.m.). The decrease in the maximal quantum efficiency of PS II and the reduction in the chlorophyll concentration supported the effect of the herbicide on Papaver rhoeas. In the guaiacol peroxidase POD and GST activity, there were large differences between the cultivated plants and the weed; both enzyme activities were much higher in the case of wheat. According to the activity of the antioxidant defence enzymes and GST gene expression data, the application of the photosynthesis inhibitor herbicide, flumioxazin, in the dark could allow the wheat antioxidant defence to switch on before the herbicide effect could appear in the light period. Phi and tau group GSTs were transcriptionally upregulated by the treatments in wheat plants (especially TaGSTU1B), while fewer changes were detectable in poppy weed (PrGSTU4). Based on our results, in the background of the greater and more successful response to flumioxazin may be—among other things—the higher degree of variability of the GSTU genes of wheat compared to poppies. Full article

(This article belongs to the Special Issue Crop Tolerance under Biotic and Abiotic Stresses)

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14 pages, 1206 KiB

Open AccessEditor’s ChoiceArticle

Soybean Response to N Fertilization Compared with Co-Inoculation of Bradyrhizobium japonicum and Azospirillum brasilense

by Jose Bais, Hans Kandel, Thomas DeSutter, Edward Deckard and Clair Keene

Agronomy 2023, 13(8), 2022; https://doi.org/10.3390/agronomy13082022 - 30 Jul 2023

Cited by 5 | Viewed by 1426

Abstract

The soybean [Glycine max (L.) Merrill] relationship with the bacteria Bradyrhizobium japonicum is responsible for providing around 60% of the nitrogen (N) required for the crop and the remaining N comes from the soil or supplemental fertilization. To investigate if higher yields [...] Read more.

The soybean [Glycine max (L.) Merrill] relationship with the bacteria Bradyrhizobium japonicum is responsible for providing around 60% of the nitrogen (N) required for the crop and the remaining N comes from the soil or supplemental fertilization. To investigate if higher yields are possible, supplemental N studies and co-inoculation of Rhizobium with Azospirillum are necessary. This N rate (0, 30, 56, 112, 336 kg N ha⁻¹) and inoculation study was conducted across eight environments in eastern North Dakota, USA, in 2021 and 2022. Also, the effect of supplemental N and co-inoculation on nodulation was evaluated. When N was applied at 112 kg N ha⁻¹, nodulation was significantly inhibited. Co-inoculation increased the number of large nodules and the volume of nodules; however, the yield was not different from inoculation with B. japonicum. Nitrogen at 112 and 336 kg ha⁻¹ increased grain yield, protein yield, and seed weight; however, the higher N rate decreased plant population. There were significant positive relationships between yield and protein content and seed weight, and negative relationships between oil and protein content, and yield and oil content. Based on a polynomial relationship, the highest yield (3711 kg ha⁻¹) would be achieved at 273 kg N ha⁻¹. The application of N resulted in a yield increase but using current prices may not be an economical choice. Additional research is necessary to verify if co-inoculation with efficient strains can improve biological N fixation. Full article

(This article belongs to the Section Soil and Plant Nutrition)

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24 pages, 3319 KiB

Open AccessEditor’s ChoiceArticle

Phylogeny and Biogeography of Morus (Moraceae)

by Chen-Xuan Yang, Shui-Yin Liu, Nyree J. C. Zerega, Gregory W. Stull, Elliot M. Gardner, Qin Tian, Wei Gu, Qing Lu, Ryan A. Folk, Heather R. Kates, Robert P. Guralnick, Douglas E. Soltis, Pamela S. Soltis, Yue-Hua Wang and Ting-Shuang Yi

Agronomy 2023, 13(8), 2021; https://doi.org/10.3390/agronomy13082021 - 30 Jul 2023

Cited by 6 | Viewed by 2706

Abstract

The mulberry genus, Morus L. (Moraceae), has long been taxonomically difficult, and its species circumscription has only been defined recently. This genus comprises ca. 16 species distributed across Asia and the Americas, yet its biogeographic history remains poorly understood. In this study, we [...] Read more.

The mulberry genus, Morus L. (Moraceae), has long been taxonomically difficult, and its species circumscription has only been defined recently. This genus comprises ca. 16 species distributed across Asia and the Americas, yet its biogeographic history remains poorly understood. In this study, we reconstructed the phylogeny and explored the biogeographic history of Morus using a combination of newly generated and previously published Hyb-Seq data. Our nuclear phylogeny recovered three well-supported geographic clades of Morus and showed that M. notabilis (China) is sister to the American clade plus the Asian clade. Multiple reticulation events among species of Morus and extensive incomplete lineage sorting (ILS) likely explain the difficulties in inferring phylogenetic relationships within the genus. Divergence time estimation indicated that Morus originated at the Eocene–Oligocene boundary, and current lineages started to diverge during the early Miocene, there is ambiguity surrounding the ancestral area with the two most likely regions being Sino-Himalaya or the Americas. Biogeographic inference and the fossil record suggest that Morus might have experienced extensive local extinction events during the Tertiary. Morus has expanded its distributional range through two dispersals from the Sino-Himalayan and Sino-Japanese regions to Southeast Asia. In summary, our new phylogenetic scheme and the biogeographic history presented here provide an essential foundation for understanding species relationships and the evolutionary history of Morus. Full article

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16 pages, 6657 KiB

Open AccessEditor’s ChoiceArticle

DCF-Yolov8: An Improved Algorithm for Aggregating Low-Level Features to Detect Agricultural Pests and Diseases

by Lijuan Zhang, Gongcheng Ding, Chaoran Li and Dongming Li

Agronomy 2023, 13(8), 2012; https://doi.org/10.3390/agronomy13082012 - 29 Jul 2023

Cited by 18 | Viewed by 3915

Abstract

The invasion of agricultural diseases and insect pests is a huge difficulty for the growth of crops. The detection of diseases and pests is a very challenging task. The diversity of diseases and pests in terms of shapes, colors, and sizes, as well [...] Read more.

The invasion of agricultural diseases and insect pests is a huge difficulty for the growth of crops. The detection of diseases and pests is a very challenging task. The diversity of diseases and pests in terms of shapes, colors, and sizes, as well as changes in the lighting environment, have a massive impact on the accuracy of the detection results. We improved the C2F module based on DenseBlock and proposed DCF to extract low-level features such as the edge texture of pests and diseases. Through the sensitivity of low-level features to the diversity of pests and diseases, the DCF module can better cope with complex detection tasks and improve the accuracy and robustness of the detection. The complex background environment of pests and diseases and different lighting conditions make the IP102 data set have strong nonlinear characteristics. The Mish activation function is selected to replace the CBS module with the CBM, which can better learn the nonlinear characteristics of the data and effectively solve the problems of gradient disappearance in the algorithm training process. Experiments show that the advanced Yolov8 algorithm has improved. Comparing with Yolov8, our algorithm improves the MAP50 index, Precision index, and Recall index by 2%, 1.3%, and 3.7%. The model in this paper has higher accuracy and versatility. Full article

(This article belongs to the Special Issue AI, Sensors and Robotics for Smart Agriculture)

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18 pages, 4374 KiB

Open AccessEditor’s ChoiceArticle

Influence of Different Nitrogen, Phosphorus, and Potassium Fertilizer Ratios on the Agronomic and Quality Traits of Foxtail Millet

by Guofang Xing, Junwei Ma, Xiaojie Liu, Biao Lei, Guo Wang, Siyu Hou and Yuanhuai Han

Agronomy 2023, 13(8), 2005; https://doi.org/10.3390/agronomy13082005 - 28 Jul 2023

Cited by 4 | Viewed by 2065

Abstract

Foxtail millet is highly valued in China; however, its optimal fertilization parameters are unknown. This study investigated the effects of nitrogen (N), phosphorus (P), and potassium (K) fertilizer combinations on foxtail millet agronomic traits, photosynthetic characteristics, yield, and quality to promote rational fertilizer [...] Read more.

Foxtail millet is highly valued in China; however, its optimal fertilization parameters are unknown. This study investigated the effects of nitrogen (N), phosphorus (P), and potassium (K) fertilizer combinations on foxtail millet agronomic traits, photosynthetic characteristics, yield, and quality to promote rational fertilizer application. Pot experiments were conducted using the “3414” fertilizer effect scheme and the representative crop variety was JG21, containing four NPK levels and 20 replicates per treatment, individually. The effects of N, P, and K levels on agronomic traits were analyzed during the jointing, heading, and filling stages. JG21 performed optimally under treatment with N₁₆₀P₉₀K₁₅₀ (T₆); the yield and fat content increased by 49.32% and 13% compared to the control. Correlation analysis revealed that N was significantly positively (negatively) correlated with the protein (amylose) content. P was significantly positively correlated with the fat and moisture content and K was correlated with the moisture, fat, and protein content, but was negatively with the amylose content. Overall, rational ratios of NPK fertilization improved foxtail millet yield and quality. Based on fuzzy comprehensive evaluation, the T₆ treatment (N₁₆₀P₉₀K₁₅₀) demonstrated the highest comprehensive effect among 13 NPK fertilizer combinations. Rational application of NPK in foxtail millet may improve agronomic performance by enhancing leaf photosynthetic efficiency and aboveground biomass accumulation. Full article

(This article belongs to the Section Soil and Plant Nutrition)

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19 pages, 1530 KiB

Open AccessEditor’s ChoiceArticle

Interaction of ZnO Nanoparticles with Metribuzin in a Soil–Plant System: Ecotoxicological Effects and Changes in the Distribution Pattern of Zn and Metribuzin

by Concepción García-Gómez, Rosa Ana Pérez, Beatriz Albero, Ana Obrador, Patricia Almendros and María Dolores Fernández

Agronomy 2023, 13(8), 2004; https://doi.org/10.3390/agronomy13082004 - 28 Jul 2023

Cited by 4 | Viewed by 1410

Abstract

The use of zinc oxide nanoparticles (ZnO NPs), applied as a possible micronutrient source, in conjunction with organic pesticides in agricultural soils has the potential to alter the environmental behavior and toxicity of these chemicals to soil biota. This research examines the joint [...] Read more.

The use of zinc oxide nanoparticles (ZnO NPs), applied as a possible micronutrient source, in conjunction with organic pesticides in agricultural soils has the potential to alter the environmental behavior and toxicity of these chemicals to soil biota. This research examines the joint effects of ZnO NPs and the herbicide metribuzin (MTZ) on phytotoxicity to plants, toxicity to soil microorganisms, and the accumulation of Zn and MTZ in plants. After 23 days, effects on growth, photosynthetic pigment content, and oxidative stress biomarkers in bean plants (Phaseolus vulgaris) and soil enzymatic activities were evaluated. Additionally, the amounts of Zn and MTZ (and the latter’s main metabolites) in soil and plant tissues were quantified. ZnO NPs reduced ammonium oxidase activity and growth among MTZ-stressed plants while reducing photosynthetic pigment levels and enhancing antioxidant enzymatic activities. MTZ had a marginal impact on the availability and accumulation of Zn in plant tissues, although significant effects were observed in some specific cases. In turn, ZnO NPs drastically affected MTZ degradation in soil and influenced MTZ accumulation/metabolization in the bean plants. Our findings indicate that the indirect effects of ZnO NPs, through their interaction with commonly used organic pesticides, may be relevant and should be taken into account in agricultural soils. Full article

(This article belongs to the Special Issue Importance of Zn Fertilization: Biofortification of Food Crops and Soil Zn Status)

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17 pages, 25331 KiB

Open AccessEditor’s ChoiceArticle

A Grape Dataset for Instance Segmentation and Maturity Estimation

by Achilleas Blekos, Konstantinos Chatzis, Martha Kotaidou, Theocharis Chatzis, Vassilios Solachidis, Dimitrios Konstantinidis and Kosmas Dimitropoulos

Agronomy 2023, 13(8), 1995; https://doi.org/10.3390/agronomy13081995 - 27 Jul 2023

Cited by 7 | Viewed by 2745

Abstract

Grape maturity estimation is vital in precise agriculture as it enables informed decision making for disease control, harvest timing, grape quality, and quantity assurance. Despite its importance, there are few large publicly available datasets that can be used to train accurate and robust [...] Read more.

Grape maturity estimation is vital in precise agriculture as it enables informed decision making for disease control, harvest timing, grape quality, and quantity assurance. Despite its importance, there are few large publicly available datasets that can be used to train accurate and robust grape segmentation and maturity estimation algorithms. To this end, this work proposes the CERTH grape dataset, a new sizeable dataset that is designed explicitly for evaluating deep learning algorithms in grape segmentation and maturity estimation. The proposed dataset is one of the largest currently available grape datasets in the literature, consisting of around 2500 images and almost 10 k grape bunches, annotated with masks and maturity levels. The images in the dataset were captured under various illumination conditions and viewing angles and with significant occlusions between grape bunches and leaves, making it a valuable resource for the research community. Thorough experiments were conducted using a plethora of general object detection methods to provide a baseline for the future development of accurate and robust grape segmentation and maturity estimation algorithms that can significantly advance research in the field of viticulture. Full article

(This article belongs to the Special Issue Computer Vision for Intelligent Crop Identification and Crop Protection)

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16 pages, 10041 KiB

Open AccessEditor’s ChoiceArticle

Pseudomonas fluorescens RB5 as a Biocontrol Strain for Controlling Wheat Sheath Blight Caused by Rhizoctonia cerealis

by Yanjie Yi, Zhipeng Hou, Yu Shi, Changfu Zhang, Lijuan Zhu, Xinge Sun, Rumeng Zhang and Zichao Wang

Agronomy 2023, 13(8), 1986; https://doi.org/10.3390/agronomy13081986 - 27 Jul 2023

Cited by 3 | Viewed by 1180

Abstract

Wheat sheath blight is a soil-borne fungal disease caused by Rhizoctonia cerealis and is a serious threat to wheat worldwide. A microbial fungicide is a promising alternative to a chemical fungicide for wheat disease control. In this study, strain RB5 against R. cerealis [...] Read more.

Wheat sheath blight is a soil-borne fungal disease caused by Rhizoctonia cerealis and is a serious threat to wheat worldwide. A microbial fungicide is a promising alternative to a chemical fungicide for wheat disease control. In this study, strain RB5 against R. cerealis was isolated from wheat rhizosphere soil, which was identified as Pseudomonas fluorescens according to physiological, biochemical, and 16S rRNA gene sequence analyses. For improving the antifungal activity of RB5, the response surface methodology (RSM) was used to optimize the culture conditions for strain RB5, and the optimal culture conditions are 8.7 g/L of cassava, 5.2 g/L of soybean meal, pH 6.8, a 218 r/min speed, a 31.5 °C temperature, and 54 h of culture time. The inhibition rate of the culture filtrate obtained under this culture condition was up to 79.06%. The investigation of action mechanism showed strain RB5 could produce protease, chitinase, and siderophore, and its culture filtrate disrupted the mycelial morphology and inhibited the activities of three cell-wall-degrading enzymes of R. cerealis. Furthermore, the pot experiment exhibited that RB5 significantly controlled the wheat sheath blight with an efficacy of 71.22%. The evaluation of toxicological safety on an animal indicated that the culture filtrate was safe on mice. Overall, the culture filtrate of RB5 is a very promising microbial fungicide for the control of wheat sheath blight. Full article

(This article belongs to the Special Issue Phytoalexins, Resistance Inducers, and Sustainable Control Measures in Crop Protection Strategies)

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20 pages, 7716 KiB

Open AccessEditor’s ChoiceArticle

Optimizing Nitrogen Regime Improves Dry Matter and Nitrogen Accumulation during Grain Filling to Increase Rice Yield

by Shenqi Zhou, Kun Liu, Xinxin Zhuo, Weilu Wang, Weiyang Zhang, Hao Zhang, Junfei Gu, Jianchang Yang and Lijun Liu

Agronomy 2023, 13(8), 1983; https://doi.org/10.3390/agronomy13081983 - 27 Jul 2023

Cited by 5 | Viewed by 1163

Abstract

Nitrogen (N) fertilizer is a critical element that affects rice yield. However, its effects on dry matter accumulation (DMA), N accumulation, and their physiological mechanisms with grain yield and N utilization efficiency still lack in-depth study. Three large-scale japonica rice varieties—Jinxiangyu 1, Nanjing [...] Read more.

Nitrogen (N) fertilizer is a critical element that affects rice yield. However, its effects on dry matter accumulation (DMA), N accumulation, and their physiological mechanisms with grain yield and N utilization efficiency still lack in-depth study. Three large-scale japonica rice varieties—Jinxiangyu 1, Nanjing 46, and Huaidao 5—were used in two field experiments with varying N fertilizer application rates to examine grain yield and N utilization efficiency. The results showed that: (1) In the range of 0~360 kg ha⁻¹ total N application rate (TNAR), the rice yields of the three cultivars were maximum under the TNAR at 270 kg ha⁻¹. The optimal TNAR for the highest yield of Jinxiangyu 1, Nanjing 46, and Huaidao 5 were calculated based on quadratic regressions with values of 305.5 kg ha⁻¹, 307.6 kg ha⁻¹, and 298.0 kg ha⁻¹, and the corresponding yields were 10.3 t ha⁻¹, 10.6 t ha⁻¹ and 10.2 t ha⁻¹, respectively. The N utilization efficiency decreased gradually with the increase in TNAR, and the recovery efficiency decreased from 35.7~38.19% to 29.61~31.59%. (2) The yield was significantly positively correlated with DMA and N accumulation from the heading stage (HD) to the maturity stage (MA). The DMA and N accumulation of HD-MA were significantly positively correlated with leaf photosynthetic rate, non-structural carbohydrate (NSC) accumulation in stems, root oxidation activity, zeatin (Z) + zeatin riboside (ZR) contents in roots, and nitrate reductase (NR) and glutamate synthase (GOGAT) activity in HD. (3) In the range of 0~216 kg ha⁻¹ panicle N application rate (PNAR), the rice yield was maximum under the PNAR at 108 kg ha⁻¹. The optimal PNAR for the highest yield of Jinxiangyu 1 was calculated based on the quadratic regression with values of 139.5 kg ha⁻¹, and the highest yield was 9.72 t ha⁻¹. The leaf photosynthetic rate, NSC accumulation in stems, root oxidation activity, Z + ZR contents in roots, and NR activity in leaves in rice were higher under 108 kg ha⁻¹ PNAR. Excessive application of panicle fertilizer reduced the above physiological indicators and rice yield. The above results showed that optimizing N fertilizer could increase the leaf photosynthetic rate, NSC accumulation in stems, root oxidation activity, Z + ZR contents in roots, and NR activity from HD to MA, which was beneficial to improving DMA and N uptake during HD-MA, thus improving grain yield and N utilization efficiency in rice. Full article

(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Phenology and Nitrogen Fertilizer under Global Climate Change)

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22 pages, 9649 KiB

Open AccessEditor’s ChoiceArticle

Maize Nitrogen Grading Estimation Method Based on UAV Images and an Improved Shufflenet Network

by Weizhong Sun, Bohan Fu and Zhao Zhang

Agronomy 2023, 13(8), 1974; https://doi.org/10.3390/agronomy13081974 - 26 Jul 2023

Cited by 4 | Viewed by 1387

Abstract

Maize is a vital crop in China for both food and industry. The nitrogen content plays a crucial role in its growth and yield. Previous researchers have conducted numerous studies on the issue of the nitrogen content in single maize plants from a [...] Read more.

Maize is a vital crop in China for both food and industry. The nitrogen content plays a crucial role in its growth and yield. Previous researchers have conducted numerous studies on the issue of the nitrogen content in single maize plants from a regression perspective; however, partition management techniques of precision agriculture require plants to be divided by zones and classes. Therefore, in this study, the focus is shifted to the problems of plot classification and graded nitrogen estimation in maize plots performed based on various machine learning and deep learning methods. Firstly, the panoramic unmanned aerial vehicle (UAV) images of maize farmland are collected by UAV and preprocessed to obtain UAV images of each maize plot to construct the required datasets. The dataset includes three classes—low nitrogen, medium nitrogen, and high nitrogen, with 154, 94, and 46 sets of UAV images, respectively, in each class. The training set accounts for eighty percent of the entire dataset and the test set accounts for the other twenty percent. Then, the dataset is used to train models based on machine learning and convolutional neural network algorithms and subsequently the models are evaluated. Comparisons are made between five machine learning classifiers and four convolutional neural networks to assess their respective performances, followed by a separate assessment of the most optimal machine learning classifier and convolutional neural networks. Finally, the ShuffleNet network is enhanced by incorporating SENet and improving the kernel size of the Depthwise separable convolution. The findings demonstrate that the enhanced ShuffleNet network has the highest performance; its classification accuracy, precision, recall, and F1 scores were 96.8%, 97.0%, 97.1%, and 97.0%, respectively. The RegNet, the optimal model among deep learning models, achieved accuracy, precision, recall, and F1 scores of 96.4%, 96.9%, 96.5%, and 96.6%, respectively. In comparison, logistic regression, the optimal model among the machine learning classifiers, attained accuracy of 77.6%, precision of 79.5%, recall of 77.6%, and an F1 score of 72.6%. Notably, the logistic regression exhibited significant enhancements of 19.2% in accuracy, 17.5% in precision, 19.5% in recall, and 24.4% in the F1 score. In contrast, RegNet demonstrated modest improvements of 0.4% in accuracy, 0.1% in precision, 0.6% in recall, and 0.4% in the F1 score. Moreover, ShuffleNet-improvement boasted a substantially lower loss rate of 0.117, which was 0.039 lower than that of RegNet (0.156). The results indicated the significance of ShuffleNet-improvement in the nitrogen classification of maize plots, providing strong support for agricultural zoning management and precise fertilization. Full article

(This article belongs to the Special Issue AI, Sensors and Robotics for Smart Agriculture)

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15 pages, 11202 KiB

Open AccessEditor’s ChoiceArticle

Identification and Analysis of SOD Family Genes in Peanut (Arachis hypogaea L.) and Their Potential Roles in Stress Responses

by Shutao Yu, Chuantang Wang, Qi Wang, Quanxi Sun, Yu Zhang, Jingchao Dong, Yechao Yin, Shihang Zhang and Guoqing Yu

Agronomy 2023, 13(8), 1959; https://doi.org/10.3390/agronomy13081959 - 25 Jul 2023

Cited by 2 | Viewed by 1259

Abstract

Superoxide dismutases (SODs) are crucial in safeguarding plants against reactive oxygen species (ROS) toxicity caused by abiotic or biotic factors. Although recent research has revealed the involvement of the SOD gene family in plant biological processes, the understanding of the SOD gene family [...] Read more.

Superoxide dismutases (SODs) are crucial in safeguarding plants against reactive oxygen species (ROS) toxicity caused by abiotic or biotic factors. Although recent research has revealed the involvement of the SOD gene family in plant biological processes, the understanding of the SOD gene family in peanut remains inadequate. This study comprehensively characterizes the SOD gene family in the peanut genome. A total of 25 AhSOD genes were identified and subsequently categorized into three subfamilies: sixteen AhCSDs, six AhFSDs, and three AhMSDs according to the phylogenetic tree. A comprehensive analysis revealed that the AhSOD genes underwent segmental duplications. The majority of AhSOD genes exhibited conserved exon–intron and motif structures within the same subfamily. The examination of cis-acting elements within the promoter regions of SOD genes revealed that the expression of AhSOD was subject to regulation by plant hormones, as well as responses to defense and stress. RNA-seq analysis showed expression diversity of AhSOD genes in various tissues and cold, drought, and salt stresses. Furthermore, the regulation of AhSOD gene expression is anticipated to involve numerous transcription factors. The gene ontology annotation results validate the role of AhSOD genes in various stress stimuli, SOD activity, reactive oxygen species metabolic processes, and cellular oxidant detoxification processes. This investigation serves as the initial genome-wide analysis of the AhSOD gene family, providing a basis for comprehending the function of the AhSOD gene family and enhancing plant tolerance to cold, drought, and salt stresses. Full article

(This article belongs to the Special Issue Advances in the Industrial Crops)

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13 pages, 3836 KiB

Open AccessEditor’s ChoiceArticle

Unattended Electric Weeder (UEW): A Novel Approach to Control Floor Weeds in Orchard Nurseries

by Yoshinori Matsuda, Koji Kakutani and Hideyoshi Toyoda

Agronomy 2023, 13(7), 1954; https://doi.org/10.3390/agronomy13071954 - 24 Jul 2023

Cited by 3 | Viewed by 1114

Abstract

This study developed an unattended electric weeder (UEW) to control floor weeds in an orchard greenhouse. The UEW was a motor-driven dolly equipped with a spark exposer. The spark exposer was constructed by applying an alternating voltage (10 kV) to a conductor net [...] Read more.

This study developed an unattended electric weeder (UEW) to control floor weeds in an orchard greenhouse. The UEW was a motor-driven dolly equipped with a spark exposer. The spark exposer was constructed by applying an alternating voltage (10 kV) to a conductor net (expanded metal net). The charged conductor net (C-CN) discharged into the surrounding space. Wild oat and white clover were used as test weed species. Weed seedlings growing on the floor were grounded by the biological conductor and were subjected to a spark from the C-CN when they reached the discharge space. The spark-exposed seedlings were singed and shrunk instantaneously. In the present experiment, the UEW was remotely controlled to move on the soil-cover metal nets, which were laid on the floor to make a flat surface, in a stop-and-go manner, and to eject a spark to the weed seedlings that emerged from the floor. All of the mono- and dicotyledonous weed seedlings, which had been artificially sown on the floor, were completely eradicated using this method. Thus, this study provides an experimental basis for developing an unattended technique for controlling floor weeds in an orchard greenhouse. Full article

(This article belongs to the Special Issue New Insights into Pathogen, Insect Pest, and Weed Control in Field and Greenhouse Cropping Systems)

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16 pages, 1242 KiB

Open AccessEditor’s ChoiceArticle

Quantitative and Qualitative Traits of Duckweed (Lemna minor) Produced on Growth Media with Pig Slurry

by Marcin Sońta, Justyna Więcek, Ewa Szara, Anna Rekiel, Anna Zalewska and Martyna Batorska

Agronomy 2023, 13(7), 1951; https://doi.org/10.3390/agronomy13071951 - 24 Jul 2023

Cited by 1 | Viewed by 2715

Abstract

Duckweed is a plant with high phytoremediation abilities, which is why it is used in the process of cleaning the aquatic environment. The present study aimed to determine the effect of various concentrations of pig slurry added to the growth media used to [...] Read more.

Duckweed is a plant with high phytoremediation abilities, which is why it is used in the process of cleaning the aquatic environment. The present study aimed to determine the effect of various concentrations of pig slurry added to the growth media used to produce duckweed (Lemna minor) (laboratory Warsaw University of Life Sciences—SGGW) (experimental groups 1–9, pig slurry concentration (%): 1—2.00, 2—1.50, 3—1.00, 4—0.75, 5—0.50, 6—0.25, 7—0.12, 8—0.06, 9—0.03, control group 0—0.00). The contents of nutrients in the growth media could be classified as high (gr. 1–3), optimal (gr. 4–6), and deficient (gr. 7–9). Analyses were conducted for duckweed yield and growth medium parameters (pig slurry concentration, pH, salinity, temperature, TDS, and EC) on days 0, 10, 20, and 30 of the experiment. No growth or poor growth of duckweed were noted in groups 1, 6–9, and 0. In turn, satisfactory yields of duckweed green mass were recorded in groups 3–5, which allowed choosing them for further observations and analyses, including proximate composition (including protein content); contents of Ca, Mg, K, Na, Zn, Cu, Cd, Pb, Al, Cr, and α-tocopherol; and carotenoids—β-carotene, α-carotene, violaxanthin, zeaxanthin, lutein, amino acids, fatty acids as well as N-NH₄ and N-NO₃. The plant material had an acceptable proximate composition and nutritionally safe analyzed component contents. Appropriate, stable growth medium conditions allowed the production of satisfactory duckweed yields. The study results allowed us to conclude that it is feasible to obtain feed material meeting basic quality standards by maintaining a closed circuit of duckweed culture, and use in the agricultural environment is possible through harnessing pig slurry for its production and ensuring its optimal growth conditions. Full article

(This article belongs to the Special Issue Agricultural Waste Management in a Circular Economy Perspective)

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13 pages, 3663 KiB

Open AccessEditor’s ChoiceArticle

Evaluating Critical Nitrogen Dilution Curves for Assessing Maize Nitrogen Status across the US Midwest

by Hui Shao, Yuxin Miao, Fabián G. Fernández, Newell R. Kitchen, Curtis J. Ransom, James J. Camberato, Paul R. Carter, Richard B. Ferguson, David W. Franzen, Carrie A. M. Laboski, Emerson D. Nafziger, John E. Sawyer and John F. Shanahan

Agronomy 2023, 13(7), 1948; https://doi.org/10.3390/agronomy13071948 - 23 Jul 2023

Cited by 1 | Viewed by 1578

Abstract

Plant N concentration (PNC) has been commonly used to guide farmers in assessing maize (Zea mays L.) N status and making in-season N fertilization decisions. However, PNC varies based on the development stage. Therefore, a relationship between biomass and N concentration is [...] Read more.

Plant N concentration (PNC) has been commonly used to guide farmers in assessing maize (Zea mays L.) N status and making in-season N fertilization decisions. However, PNC varies based on the development stage. Therefore, a relationship between biomass and N concentration is needed (i.e., critical N dilution curve; CNDC) to better understand when plants are N deficient. A few CNDCs have been developed and used for plant N status diagnoses but have not been tested in the US Midwest. The objective of this study was to evaluate under highly diverse soil and weather conditions in the US Midwest the performance of CNDCs developed in France and China for assessing maize N status. Maize N rate response trials were conducted across eight US Midwest states over three years. This analysis utilized plant and soil measurements at V9 and VT development stages and final grain yield. Results showed that the French CNDC (y = 34.0x^−0.37, where y is critical PNC, and x is aboveground biomass) was better with a 91% N status classification accuracy compared to only 62% with the Chinese CNDC (y = 36.5x^−0.48). The N nutrition index (NNI), which is the quotient of the measured PNC and the calculated critical N concentration (Nc) based on the French CNDC was significantly related to soil nitrate-N content (R² = 0.38–0.56). Relative grain yield on average reached a plateau at NNI values of 1.36 at V9 and 1.21 at VT but for individual sites ranging from 0.80 to 1.41 at V9 and from 0.62 to 1.75 at VT. The NNI threshold values or ranges optimal for crop biomass production may not be optimal for grain yield production. It is concluded that the CNDC developed in France is suitable as a general diagnostic tool for assessing maize N status in US Midwest. However, the threshold values of NNI for diagnosing maize N status and guiding N applications vary significantly across the region, making it challenging to guide specific on-farm N management. More studies are needed to determine how to effectively use CNDC to make in-season N recommendations in the US Midwest. Full article

(This article belongs to the Special Issue The Importance of Soil Spatial Variability in Precision Agriculture)

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13 pages, 2391 KiB

Open AccessEditor’s ChoiceArticle

Effect of Different Ratios of Red and Blue Light on Maximum Stomatal Conductance and Response Rate of Cucumber Seedling Leaves

by Xue Li, Shiwen Zhao, Aiyu Lin, Yuanyuan Yang, Guanzhi Zhang, Peng Xu, Yongjun Wu and Zhenchao Yang

Agronomy 2023, 13(7), 1941; https://doi.org/10.3390/agronomy13071941 - 22 Jul 2023

Cited by 4 | Viewed by 1598

Abstract

Light can regulate leaf stomatal development and movement, but the effects of different red-to-blue light mass ratios on leaf stomatal morphology and openness are not fully understood. In this trial, five different red-to-blue light (R:B) ratio treatments were used to study the changes [...] Read more.

Light can regulate leaf stomatal development and movement, but the effects of different red-to-blue light mass ratios on leaf stomatal morphology and openness are not fully understood. In this trial, five different red-to-blue light (R:B) ratio treatments were used to study the changes in morphology, photosynthesis, and stomatal-related indexes of cucumber seedlings under fixed light intensity (200 μmol·m⁻²·s⁻¹). The results showed that the thickness of spongy tissue and stomatal size (SZ) of cucumber seedling leaves decreased, and the photosynthetic potential, stomatal density (SD), maximum stomatal conductance and stomatal responsiveness increased with decreasing R:B content. The experimental results showed that when R:B = is 1:9, cucumber seedlings had the greatest stomatal density and the fastest response rate, and the stomatal opening rate was accelerated with the increase in the proportion of blue light; when R:B = is 3:7, the stomatal conductance was the greatest and the net photosynthetic rate was the highest. This trial provides some implications for changing plant light quality and thus affecting stomatal development and movement. Full article

(This article belongs to the Section Horticultural and Floricultural Crops)

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15 pages, 2888 KiB

Open AccessEditor’s ChoiceArticle

A Comprehensive Approach to Assessing Yield Map Quality in Smart Agriculture: Void Detection and Spatial Error Mapping

by John Byabazaire, Gregory M. P. O’Hare, Rem Collier, Chamil Kulatunga and Declan Delaney

Agronomy 2023, 13(7), 1943; https://doi.org/10.3390/agronomy13071943 - 22 Jul 2023

Cited by 2 | Viewed by 1520

Abstract

Smart agriculture relies on accurate yield maps as a crucial tool for decision-making. Many yield maps, however, suffer from spatial errors that can compromise the quality of their data, while several approaches have been proposed to address some of these errors, detecting voids [...] Read more.

Smart agriculture relies on accurate yield maps as a crucial tool for decision-making. Many yield maps, however, suffer from spatial errors that can compromise the quality of their data, while several approaches have been proposed to address some of these errors, detecting voids or holes in the maps remains challenging. Additionally, the quality of yield datasets is typically evaluated based on root mean squared errors after interpolation. This evaluation method relies on weighbridge data, which can occasionally be inaccurate, impacting the quality of decisions made using the datasets. This paper introduces a novel algorithm designed to identify voids in yield maps. Furthermore, it maps three types of spatial errors (GPS errors, yield surges, and voids) to two standard data quality dimensions (accuracy and completeness). Doing so provides a quality score that can be utilized to assess the quality of yield datasets, eliminating the need for weighbridge data. The paper carries out three types of evaluations: (1) evaluating the algorithm’s efficacy by applying it to a dataset containing fields with and without voids; (2) assessing the benefits of integrating void detection and other spatial error identification techniques into the yield data processing chain; and (3) examining the correlation between root mean squared error and the proposed quality score before and after filtering out spatial errors. The results of the evaluations demonstrate that the proposed algorithm achieves a 100% sensitivity, 91% specificity, and 82% accuracy in identifying yield maps with voids. Additionally, there is a decrease in the root mean squared error when various spatial errors, including voids after applying the proposed data pre-processing chain. The inverse correlation observed between the root mean squared error and the proposed quality score (−0.577 and −0.793, before and after filtering spatial errors, respectively) indicates that the quality score can effectively assess the quality of yield datasets. This assessment enables seamless integration into real-time big data quality assessment solutions based on various data quality dimensions. Full article

(This article belongs to the Special Issue “Smart Agriculture” Information Technology and Agriculture Cross-Discipline Research and Development)

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17 pages, 4203 KiB

Open AccessEditor’s ChoiceArticle

Nitrogen, Phosphorus, and Potassium Uptake in Rain-Fed Corn as Affected by NPK Fertilization

by Ravinder Singh, Steven Kyle Sawatzky, Matthew Thomas, Samuel Akin, Hailin Zhang, William Raun and Daryl Brian Arnall

Agronomy 2023, 13(7), 1913; https://doi.org/10.3390/agronomy13071913 - 20 Jul 2023

Cited by 3 | Viewed by 3473

Abstract

Effective nutrient management requires understanding nutrient uptake at various growth stages and nutrient removal by the harvested portion. Information on nutrient accumulation was provided by some older literature, and a few researchers have focused on this issue in this modern period with modern [...] Read more.

Effective nutrient management requires understanding nutrient uptake at various growth stages and nutrient removal by the harvested portion. Information on nutrient accumulation was provided by some older literature, and a few researchers have focused on this issue in this modern period with modern hybrids and improved corn cultivation practices. While almost all the studies were conducted in northern states of the US, information for the Southern Great Plains is still limited. To bridge this knowledge gap, a 2-year field study was conducted in a rain-fed corn production system. The study aimed to evaluate the impact of nitrogen (N), phosphorus (P) and potassium (K) fertilization on N, P, and K contents in aboveground plants at different growth stages. Pre-plant application of N (0, 67, 133 kg N ha⁻¹), P (0 and 20 kg ha⁻¹) and K (0 and 60 kg ha⁻¹) fertilizers was done. Results from our study revealed that nutrient uptake values, pattern and dynamics depend on environmental conditions, soil type and management practices. N concentration in plants showed a linear response to N application rate while P and K concentrations were unaffected by NPK fertilization rates. Total N, P and K uptake was primarily driven by N application rate, showing a linear increase with higher N rates. Co-application of P and K with N did not significantly affect nutrient concentration and uptake. Full article

(This article belongs to the Topic Plants Nutrients)

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15 pages, 6107 KiB

Open AccessEditor’s ChoiceArticle

YOLOv5-ASFF: A Multistage Strawberry Detection Algorithm Based on Improved YOLOv5

by Yaodi Li, Jianxin Xue, Mingyue Zhang, Junyi Yin, Yang Liu, Xindan Qiao, Decong Zheng and Zezhen Li

Agronomy 2023, 13(7), 1901; https://doi.org/10.3390/agronomy13071901 - 19 Jul 2023

Cited by 8 | Viewed by 2503

Abstract

The smart farm is currently a hot topic in the agricultural industry. Due to the complex field environment, the intelligent monitoring model applicable to this environment requires high hardware performance, and there are difficulties in realizing real-time detection of ripe strawberries on a [...] Read more.

The smart farm is currently a hot topic in the agricultural industry. Due to the complex field environment, the intelligent monitoring model applicable to this environment requires high hardware performance, and there are difficulties in realizing real-time detection of ripe strawberries on a small automatic picking robot, etc. This research proposes a real-time multistage strawberry detection algorithm YOLOv5-ASFF based on improved YOLOv5. Through the introduction of the ASFF (adaptive spatial feature fusion) module into YOLOv5, the network can adaptively learn the fused spatial weights of strawberry feature maps at each scale as a way to fully obtain the image feature information of strawberries. To verify the superiority and availability of YOLOv5-ASFF, a strawberry dataset containing a variety of complex scenarios, including leaf shading, overlapping fruit, and dense fruit, was constructed in this experiment. The method achieved 91.86% and 88.03% for mAP and F1, respectively, and 98.77% for AP of mature-stage strawberries, showing strong robustness and generalization ability, better than SSD, YOLOv3, YOLOv4, and YOLOv5s. The YOLOv5-ASFF algorithm can overcome the influence of complex field environments and improve the detection of strawberries under dense distribution and shading conditions, and the method can provide technical support for monitoring yield estimation and harvest planning in intelligent strawberry field management. Full article

(This article belongs to the Special Issue AI, Sensors and Robotics for Smart Agriculture)

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16 pages, 3865 KiB

Open AccessEditor’s ChoiceArticle

Formulation of Matrine Oil-Based Suspension Concentrate for Improving the Wetting of Droplets and Spraying Performance

by Meng Li, Zhen Wang, Huanwen Meng, Baozhu Dong, Xile Deng and Hongyou Zhou

Agronomy 2023, 13(7), 1895; https://doi.org/10.3390/agronomy13071895 - 18 Jul 2023

Cited by 3 | Viewed by 2120

Abstract

Matrine is an efficient, low-toxicity, and environmentally friendly botanical pesticide; however, it is mainly applied as a soluble concentrate (SL) with a limited utilization rate that is unsuitable for ultra-low-volume spraying and unmanned aerial vehicles. Therefore, a matrine formulation (such as an oil-based [...] Read more.

Matrine is an efficient, low-toxicity, and environmentally friendly botanical pesticide; however, it is mainly applied as a soluble concentrate (SL) with a limited utilization rate that is unsuitable for ultra-low-volume spraying and unmanned aerial vehicles. Therefore, a matrine formulation (such as an oil-based suspension concentrate, OD) is more effective. In this study, matrine ODs were prepared with three kinds of emulsifiers (VO/02N, VO/03, and VO/01). The storage stability, suspensibility, viscosity, surface tension, contact angle, droplet density, fraction of coverage, maximum retention, indoor control, effect of adhesion tension, and adhesion work of matrine ODs were studied. All three types of matrine ODs had favorable stability, and the wetting and spraying performance of the matrine ODs were more effective than those of the matrine SLs. Among the three types of matrine ODs, the viscosity, wettability, spray performance, and maximum retention of the suspension made with emulsifier VO/03 were superior to those of the other two emulsifiers, and they were more effective in controlling Spodoptera frugiperda. Increasing the solution concentration improved the spreading velocity of the droplets on the solid surface and the wettability. The matrine OD prepared from emulsifier VO/03 had the most effective wettability and spraying properties, and it can be used for ultra-low-volume spraying and aerial application. This study offers new insights into the efficient use of plant-based pesticides. Full article

(This article belongs to the Special Issue Application of Nanomaterials in Pesticides: Pesticide Controlled Release Formulations)

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12 pages, 281 KiB

Open AccessEditor’s ChoiceArticle

Effect of Poultry Litter Application Method and Rainfall and Delayed Wrapping on Warm-Season Grass Baleage

by Christine C. Nieman, Wayne K. Coblentz, Philip A. Moore, Jr. and Matthew S. Akins

Agronomy 2023, 13(7), 1896; https://doi.org/10.3390/agronomy13071896 - 18 Jul 2023

Cited by 3 | Viewed by 1143

Abstract

Poultry litter is a widely available fertilizer in the southeast USA and subsurface application of litter can increase both forage production and nutritive value. Frequent rainfall events and high humidity often limit time available for hay curing; baled silage techniques can increase harvest [...] Read more.

Poultry litter is a widely available fertilizer in the southeast USA and subsurface application of litter can increase both forage production and nutritive value. Frequent rainfall events and high humidity often limit time available for hay curing; baled silage techniques can increase harvest time flexibility. Unfortunately, rainfall events can still occur without forecast during harvest events, resulting in delayed baling or wrapping. The objective of this study was to evaluate poultry litter amendment methods, subsurface (SUB) and surface (SURF), and the effect of no rain (NR) on bales with wrapping after 2 h compared with rained-on bales with 17 h delayed wrapping (RDW) on warm-season grass baleage fermentation and nutritive value. Data were analyzed as a randomized complete block design with two amendment treatments and two post-baling treatments. Crude protein (CP) was greater (p < 0.01) and neutral detergent fiber (NDF) was lower (p < 0.01) in both pre- and post-ensiled bales with subsurface-applied poultry litter. Rain and delayed wrapping resulted in lower pH (p = 0.03), starch (p < 0.01), and water-soluble carbohydrates (p < 0.01) in pre-ensiled bales, compared to those that did not receive rain and were wrapped within 2 h, while post-ensiled bales only differed in lower (p < 0.01) starch and slightly greater (p < 0.01) NDF in RDW. Lactic acid (p < 0.01), acetic acid (p < 0.01), and total acids (p = 0.03) were greater in SUB, while butyric acid tended to be greater (p = 0.09), and alcohols (p = 0.05) were greater in SURF. Bales from RDW and NR only differed by greater (p < 0.01) propionic acid concentrations in NR. Under the conditions of this experiment, subsurface application of poultry litter increased final nutritive value, while rainfall and delayed wrapping of 17 h had few effects on the final nutritive value of warm-season grass baleage. Full article

(This article belongs to the Special Issue Prospects for the Development of Silage and Green Fodder)

15 pages, 3215 KiB

Open AccessEditor’s ChoiceArticle

Frequency of Outcrossing and Isolation Distance in Faba Beans (Vicia faba L.)

by Kedar N. Adhikari, Lucy Burrows, Abdus Sadeque, Christopher Chung, Brian Cullis and Richard Trethowan

Agronomy 2023, 13(7), 1893; https://doi.org/10.3390/agronomy13071893 - 17 Jul 2023

Viewed by 1302

Abstract

Faba beans (Vicia faba L.) constitute a partially outcrossing species requiring an isolation distance to maintain genetic purity when more than one variety is grown in field conditions. This information is crucial for seed growers and faba bean breeders. A study was [...] Read more.

Faba beans (Vicia faba L.) constitute a partially outcrossing species requiring an isolation distance to maintain genetic purity when more than one variety is grown in field conditions. This information is crucial for seed growers and faba bean breeders. A study was conducted at the University of Sydney’s Plant Breeding Institute, Narrabri, over two years to examine the extent of natural outcrossing using a creamy white flower characteristic as a morphological marker, which is controlled by a single recessive gene. The white-flowered genotype (IX225c) was grown in paired rows of 150 m length in four directions from a central 480 m² plot of the normal flowered genotype PBA Warda. A beehive was placed in the central plot at the flowering time and natural pollination was allowed. At maturity, seed samples were taken from the white-flowered genotype at designated intervals along each axis and 100 seeds from each sample were grown in the glasshouse/birdcage to the 4–5 leaf stage and the proportion of plants displaying a stipule spot pigmentation (normal flower color and spotted stipule are linked) was used to determine the percentage of outcrossing. Maximum outcrossing of 2.28% occurred where both genotypes were grown side by side (0 m) and the degree of outcrossing decreased as the distance along each axis from the central plot increased. At a 6 m distance, the outcrossing was less than 1%; however, on occasion, it increased to 1% beyond a distance of 100 m, indicating the volatile and unpredictable nature of bee flights. Distance had a major effect on outcrossing but the direction and its interaction had no effect. The results suggest that to limit outcrossing to below 0.5%, a distance of more than 150 m between plots of different faba beans cultivars would be required. It also indicated that Australian faba bean genotypes are mostly self-fertile and a relatively narrow isolation distance will ensure self-fertilization in seed production and breeding programs. Full article

(This article belongs to the Section Crop Breeding and Genetics)

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12 pages, 681 KiB

Open AccessEditor’s ChoiceArticle

Effects of Phosphate Fertilizer Application on the Growth and Yield of Tartary Buckwheat under Low-Nitrogen Condition

by Qiuyue Zhou, Jingang Tang, Changmin Liu, Kaifeng Huang and Xiaoyan Huang

Agronomy 2023, 13(7), 1886; https://doi.org/10.3390/agronomy13071886 - 17 Jul 2023

Cited by 10 | Viewed by 1831

Abstract

This study aimed to clarify the effect of phosphorus fertilizer on the senescence and yield of Tartary buckwheat under low-nitrogen treatment. A two-year field experiment to investigate the characteristics was conducted on Tartary buckwheat (Qianku 5) under four phosphorus fertilizer application rates, 0(CK), [...] Read more.

This study aimed to clarify the effect of phosphorus fertilizer on the senescence and yield of Tartary buckwheat under low-nitrogen treatment. A two-year field experiment to investigate the characteristics was conducted on Tartary buckwheat (Qianku 5) under four phosphorus fertilizer application rates, 0(CK), 40(LP), 80(MP), and 120 kg·ha⁻¹ (HP), in the absence of nitrogen treatment. Compared with CK, MP treatment increased the plant height, node number of main stem, branch number of main stem, root-morphology items, root activity, enzyme activity related to root nitrogen metabolism, leaf chlorophyll content, and antioxidant enzyme activity by an average of 27.82%, 36.00%, 31.76%, 70.63%, 103.16%, 45.63%, 19.42%, and 45.48%, respectively. MP treatment significantly decreased the malondialdehyde content by 23.54% compared with that of CK. Among all treatments, the HP treatment had the highest content. The grain number per plant, grain weight per plant, and yield under MP treatment were 1.54, 1.65, and 1.53 times those of CK, respectively. In summary, the appropriate phosphate fertilizer treatment (80 kg·ha⁻¹) can delay senescence, promote the growth, and increase the yield of Tartary buckwheat at low nitrogen levels. Such treatment is recommended for use in production to jointly achieve the high yield and high nitrogen conservation of Tartary buckwheat. Full article

(This article belongs to the Section Soil and Plant Nutrition)

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15 pages, 1624 KiB

Open AccessEditor’s ChoiceArticle

Greenhouse Gas Emissions from Double-Season Rice Field under Different Tillage Practices and Fertilization Managements in Southeast China

by Tong Yang, Zhi Yang, Chunchun Xu, Fengbo Li, Fuping Fang and Jinfei Feng

Agronomy 2023, 13(7), 1887; https://doi.org/10.3390/agronomy13071887 - 17 Jul 2023

Cited by 4 | Viewed by 2275

Abstract

To better understand the effects of tillage practice and fertilization management on greenhouse gas emissions and yields, a four-year field experiment was conducted to assess the effects of tillage practices (rotary tillage (RT) and no tillage (NT)) on the emissions of methane (CH [...] Read more.

To better understand the effects of tillage practice and fertilization management on greenhouse gas emissions and yields, a four-year field experiment was conducted to assess the effects of tillage practices (rotary tillage (RT) and no tillage (NT)) on the emissions of methane (CH₄) and nitrous oxide (N₂O) and rice yield under four fertilization management strategies (no fertilizer without straw (CK), inorganic fertilizer without straw (F), inorganic fertilize with biochar (FB), and inorganic fertilizer with straw (FS)). The results showed that NT significantly reduced CH₄ emissions by 21.1% and 52.6% compared to RT in early and late rice, respectively. Conversely, NT led to a significant increase in N₂O emissions by 101.0%, 79.0%, and 220.8% during the early rice, late rice, and fallow periods. Nevertheless, global warming potential (GWP) and greenhouse gas intensity (GHGI) were significantly mitigated, respectively, by 36.4% and 35.9% in NT, compared to RT treatment. There were significant interactions between tillage practice and fertilization management. Compared with CK, the F and FB treatments significantly reduced the GWP, respectively, by 40.4% and 53.8%, as well as the GHGI, respectively, by 58.2% and 69.9% in the RT condition; however, no significant difference was found under the NT condition. In contrast, the FS treatment significantly increased GWP and GHGI in both the RT and NT conditions. Overall, FB treatment had the same significantly low GHGI rating, with a value of 0.44 kg CO₂-eq kg⁻¹ yield year⁻¹ in RT and NT. Thus, the conversion of straw to biochar and its application to rice fields is a potentially sustainable agricultural strategy for mitigating GHG emissions and increasing yields. This study provides theoretical and practical support for double-season rice production in climate-smart agriculture. Full article

(This article belongs to the Special Issue Agricultural Management for Climate Change Adaptation, Greenhouse Gas Mitigation, and Agricultural Productivity)

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11 pages, 796 KiB

Open AccessEditor’s ChoiceArticle

Looking beyond Glyphosate for Site-Specific Fallow Weed Control in Australian Grain Production

by Angus Malmo, John C. Broster and Michael J. Walsh

Agronomy 2023, 13(7), 1878; https://doi.org/10.3390/agronomy13071878 - 16 Jul 2023

Cited by 1 | Viewed by 1065

Abstract

Summer annual weed species in northern Australian summer fallows are frequently present at low densities and, increasingly, are glyphosate-resistant, creating the need for alternative herbicides for site-specific weed control. Alternative non-selective herbicide treatments are effective on problematic summer fallow weeds; however, many are [...] Read more.

Summer annual weed species in northern Australian summer fallows are frequently present at low densities and, increasingly, are glyphosate-resistant, creating the need for alternative herbicides for site-specific weed control. Alternative non-selective herbicide treatments are effective on problematic summer fallow weeds; however, many are yet to be evaluated as site-specific (spot spraying) treatments. This study aimed to identify herbicides that could be used in place of glyphosate to control larger/mature Chloris virgata and Sonchus oleraceus plants. The response of these weed species to 12 herbicide treatments was evaluated in pot experiments conducted over summer/autumn 2022. Despite herbicide treatments not being consistently effective across both species, there were instances where control was achieved by some herbicide treatments. S. oleraceus was controlled (i.e., ≤10% plant survival) by glufosinate-ammonium, paraquat and also with protoporphyrinogen-oxidase (PPO)-inhibiting herbicides saflufenacil, tiafenacil and trifludimoxazin. However, these results were not consistent in repeated studies or for C. virgata. Glyphosate was the only herbicide that controlled C. virgata. A glyphosate replacement as a spot-spraying treatment was not identified, and until further studies are more successful, alternative approaches are needed to preserve the ongoing effectiveness of this herbicide. Full article

(This article belongs to the Special Issue Herbicides and Chemical Control of Weeds)

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21 pages, 4514 KiB

Open AccessEditor’s ChoiceArticle

Effects of Bacillus subtilis HS5B5 on Maize Seed Germination and Seedling Growth under NaCl Stress Conditions

by Peng Song, Biao Zhao, Xingxin Sun, Lixiang Li, Zele Wang, Chao Ma and Jun Zhang

Agronomy 2023, 13(7), 1874; https://doi.org/10.3390/agronomy13071874 - 15 Jul 2023

Cited by 5 | Viewed by 1977

Abstract

Salinity is one of the most important factors limiting agricultural productivity. The positive effects of an inoculation with Bacillus subtilis HS5B5 on maize (Zea mays L.) seed germination and seedling growth under saline conditions were elucidated in this study. Maize plants were [...] Read more.

Salinity is one of the most important factors limiting agricultural productivity. The positive effects of an inoculation with Bacillus subtilis HS5B5 on maize (Zea mays L.) seed germination and seedling growth under saline conditions were elucidated in this study. Maize plants were treated with four NaCl concentrations (0, 100, 200, and 300 mmol·L⁻¹) under hydroponic conditions and the plants inoculated with B. subtilis HS5B5 were compared with the non-inoculated plants in terms of key morphophysiological leaf and root traits. Maize seed germination and seedling growth were inhibited by NaCl stress. The inoculation with B. subtilis HS5B5 significantly increased the germination rate, germination potential, shoot length, and root length under NaCl stress conditions. Moreover, the plant height, biomass, root to shoot weight ratio, above-ground fresh weight, and below-ground fresh weight were higher for the inoculated maize seedlings than for the non-inoculated plants under saline conditions. Additionally, B. subtilis HS5B5 alleviated the salt-induced damage to maize by increasing the chlorophyll content, altering the abundance of osmoregulatory substances, and increasing antioxidant enzyme activities, while decreasing the malondialdehyde content. After the NaCl treatment, the Na⁺ content in the leaves and roots of maize plants inoculated with B. subtilis HS5B5 decreased significantly, while the K⁺ content increased. Thus, the inhibitory effect of NaCl stress on maize seed germination and seedling growth was mitigated by B. subtilis HS5B5, suggesting the utility of this microorganism for improving crop cultivation under saline conditions. Full article

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