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Agronomy, Volume 14, Issue 7 (July 2024) – 259 articles

Cover Story (view full-size image): Thirty-six fungicides were sprayed on single colonies of Podosphaera aphanis on the leaves of strawberry seedlings. Asexual conidia were collected from single P. aphanis colonies on the leaves spray-treated with fungicides using an electrostatic spore collector. Using the electrostatic technique, we confirmed that P. aphanis developed resistance to both thiophanate-methyl and azoxystrobin, as has previously been established. Thus, this methodological assessment analyzing the colony development and number of conidia released from single colonies will be helpful information for screening effective fungicides. View this paper
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12 pages, 1848 KiB  
Article
Genome-Wide Identification of Height-Related Genes Using Three Maize Dwarfs and RNA-Seq
by Yang Gao, Haojie Ren, Ruiyu Wang, Danyang Cheng, Yinglu Song, Xin Wen, Zheng Zhang and Jianzhong Chang
Agronomy 2024, 14(7), 1598; https://doi.org/10.3390/agronomy14071598 - 22 Jul 2024
Viewed by 295
Abstract
Plant height is an important grain yield-associated trait in maize. To date, few genes related to plant height have been characterized in maize. To better understand the genetic mechanisms of plant height in maize, we revealed the transcriptional changes of three dwarf mutants [...] Read more.
Plant height is an important grain yield-associated trait in maize. To date, few genes related to plant height have been characterized in maize. To better understand the genetic mechanisms of plant height in maize, we revealed the transcriptional changes of three dwarf mutants compared to the wild type. By ethyl methane sulfonate treatment of the wild-type maize cultivar PH6WC, we obtained three dwarfs—PH6WCdwarf1 (pd1), PH6WCdwarf2 (pd2), and PH6WCdwarf3 (pd3)—and their plant heights were reduced by 42%, 38%, and 24%, respectively. RNA-Seq data suggested that 1641 differentially expressed genes (DEGs) overlapped with each other among the three dwarfs at the seedling stage. Further analysis showed that the DEGs were divided into four groups with different expression patterns. Functional analysis revealed that these DEGs were commonly enriched in 47 GO terms mainly involved in cytokinesis, hormone, and energy metabolism pathways. Among them, An1, involved in the GA biosynthesis pathway, and mutations in An1 result in reduced plant height. EREB182 encodes ethylene-responsive element binding protein 2, which is critical for internode elongation. Microtubule-related genes Zmtub2, Zmtub3, Zmtub5, Zmtub6, and TUBG2 were commonly enriched among the three comparisons. Previous studies have shown that mutations in microtubule-associated genes cause the dwarf phenotype. However, nearly half of the common DEGs had no functional information, such as Zm00001d000107, Zm00001d000279, etc., implying their novel and specific functions in maize. Overall, this study identifies several potential plant height-related genes and contributes to linking genetic resources with maize breeding. Full article
(This article belongs to the Section Crop Breeding and Genetics)
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14 pages, 5132 KiB  
Article
Gibberellins Regulate Expression of Cyclins to Control Leaf Width in Rice
by Ruifeng Zou, Xiaoyuan Guo, Siyao Shan and Quan Wang
Agronomy 2024, 14(7), 1597; https://doi.org/10.3390/agronomy14071597 - 22 Jul 2024
Viewed by 236
Abstract
Leaves are the nutritive organs of rice. Leaf shape influences rice photosynthesis, subsequently impacting yield. Gibberellins, GAs, are important hormones, but the way in which GAs regulate leaf width is largely unknown. This study focuses on the d18 mutant with broader leaves due [...] Read more.
Leaves are the nutritive organs of rice. Leaf shape influences rice photosynthesis, subsequently impacting yield. Gibberellins, GAs, are important hormones, but the way in which GAs regulate leaf width is largely unknown. This study focuses on the d18 mutant with broader leaves due to defective GA biosynthesis. Statistical analysis indicates broader leaves in the d18 mutant compared to the wild-type group. An examination of leaf cell morphology shows a higher count of secondary vascular bundles in d18 than in the wild-type group. RNA-seq analysis demonstrates significantly higher expression of CYCB (CYCLIN B) and H4 (HISTONE H4) in d18 compared to wild type. In summary, the leaf width of d18 may due to a higher activity of cell division at leaf margin. Full article
(This article belongs to the Section Plant-Crop Biology and Biochemistry)
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19 pages, 6102 KiB  
Article
Comparative Transcriptomic Analysis Reveals Transcriptional Differences in the Response of Quinoa to Salt and Alkali Stress Responses
by Qinghan Bao, Yang Wu, Yang Wang and Yongping Zhang
Agronomy 2024, 14(7), 1596; https://doi.org/10.3390/agronomy14071596 - 22 Jul 2024
Viewed by 186
Abstract
Soil salinization is a global agro-ecological problem and a major factor impeding agricultural development. Planting salt-tolerant plants to improve saline soils offers both ecological and economic benefits. Currently, there are few studies addressing the combined effects of salt and alkali stress. Quinoa is [...] Read more.
Soil salinization is a global agro-ecological problem and a major factor impeding agricultural development. Planting salt-tolerant plants to improve saline soils offers both ecological and economic benefits. Currently, there are few studies addressing the combined effects of salt and alkali stress. Quinoa is known for its salinity tolerance. However, research has predominantly focused on the effects of salinity stress on quinoa’s morphology and physiology, with its molecular mechanisms remaining unclear. To better understand quinoa’s response mechanisms to salinity and alkali stress, we employed RNA-seq technology to analyze transcriptomes under these conditions. We identified 1833 differentially expressed genes (DEGs) under salt stress and 2233 DEGs under alkali stress. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations revealed that quinoa responds to salt and alkali stress through similar mechanisms. Both stresses promoted sucrose synthesis, starch synthesis and catabolism, which increased the osmotic potential of quinoa leaves. Additionally, there was a regulation of the down-regulated expression of the abscisic acid receptor PYR/PYL and the up-regulated expression of the serine/threonine protein kinase (PP2C) gene in the ABA signaling pathway. Contrasting with salt tolerance, the mechanism specific to quinoa’s alkalinity tolerance involves the up-regulation of the citric acid cycle via an active γ-aminobutyric acid (GABA) branch, enhancing quinoa’s energy metabolism. In summary, our transcriptome analysis revealed key regulatory mechanisms in quinoa’s response to saline and alkaline stress. This study deepens the understanding of quinoa’s stress response mechanisms and provides theoretical references for the biological improvement of salinized soils. Full article
(This article belongs to the Special Issue Strategies for Enhancing Abiotic Stress Tolerance in Crops)
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19 pages, 2543 KiB  
Article
Biochar as an Alternative Litter Additive to Mitigate Gaseous Emissions from Broiler Housing and Subsequent Storage
by José L. S. Pereira, Filipa Martins, Gabriel Bonifácio, Carla Garcia, José Teixeira and Henrique Trindade
Agronomy 2024, 14(7), 1595; https://doi.org/10.3390/agronomy14071595 - 22 Jul 2024
Viewed by 217
Abstract
Broiler farming is a significant source of gaseous emissions. The aim of this study was to assess the effects of different litter additives on the emission of NH3, N2O, CO2, and CH4 during broiler housing and [...] Read more.
Broiler farming is a significant source of gaseous emissions. The aim of this study was to assess the effects of different litter additives on the emission of NH3, N2O, CO2, and CH4 during broiler housing and subsequent manure storage. The gaseous emissions from the housing facilities were evaluated during one fattening cycle in environmentally controlled rooms with three different additives applied to the litter material (10% w/w aluminum sulphate or biochar and 2.50 mg m−2 urease inhibitor), as well as a control. A storage experiment was conducted under laboratory conditions for 90 days to evaluate the influence of these three additives on gaseous losses. During broiler housing, the results indicated that NH3 emissions were reduced significantly (40–60%) by litter additives, while global warming potential (GWP) emissions were reduced significantly (31%) by Alum. The addition of Biochar (a 58% reduction) had the same significant effect as Alum (a 60% reduction) to mitigate these losses. The re-application of Urease (a 41% reduction) may be required to reach an equal or higher reduction. During storage, NH3 and GWP emissions were not significantly affected by the litter additives. During broiler housing and subsequent manure storage, NH3 emissions were reduced significantly (22–41%) by litter additives, whereas GWP emissions did not decrease significantly. Globally, it can be concluded that Biochar appears to be a good alternative to Alum due to its equal effectiveness in mitigating NH3 losses, without increasing the GWP potential in the housing and avoiding pollution swapping. Full article
(This article belongs to the Section Farming Sustainability)
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14 pages, 650 KiB  
Article
Influence of Spirulina Extract on Physiological, Qualitative, and Productive Traits of Four Sugarcane Genotypes
by Marwa Ghallab, Najat Bukhari, El-Araby Salem, Mohamed El-Zaidy, Amr El-Sheikh and Ramalingam Raja
Agronomy 2024, 14(7), 1594; https://doi.org/10.3390/agronomy14071594 - 22 Jul 2024
Viewed by 278
Abstract
This study was conducted at El-Sabahia Research Station (latitude 31°12′ N, longitude 29°58′ E) in Alexandria, Egypt to evaluate the effect of Spirulina platensis algae extract on the growth, yield, and juice quality of four sugarcane genotypes during the 2020/2021 and 2021/2022 seasons. [...] Read more.
This study was conducted at El-Sabahia Research Station (latitude 31°12′ N, longitude 29°58′ E) in Alexandria, Egypt to evaluate the effect of Spirulina platensis algae extract on the growth, yield, and juice quality of four sugarcane genotypes during the 2020/2021 and 2021/2022 seasons. The sugarcane genotypes tested (G.T. 54-9, G. 2003-47, G. 84-47, and G. 2004-27) were treated with four concentrations (0, 0.1, 0.2, and 0.3%) of spirulina algae extract (SE) during their development as plant cane and first ratoon crops. At harvest, the growth, physiological, and juice quality characteristics were documented, while relative chlorophyll content was measured 210 days after sowing. Spraying canes with 0.2% of SE was the most effective treatment in enhancing all of the evaluated characteristics compared to those left without SE. Cane yield was more closely correlated with stalk weight (r = 0.88), followed by leaf area index (r = 0.82), relative chlorophyll content (r = 0.82), stalk length (r = 0.76), and number of tillers (r = 0.73), while recoverable sugar yield was closely correlated (p < 0.01) with sugar content % (r = 0.76). Full article
(This article belongs to the Section Horticultural and Floricultural Crops)
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13 pages, 2261 KiB  
Article
A Deep-Learning-Based Model for the Detection of Diseased Tomato Leaves
by Akram Abdullah, Gehad Abdullah Amran, S. M. Ahanaf Tahmid, Amerah Alabrah, Ali A. AL-Bakhrani and Abdulaziz Ali
Agronomy 2024, 14(7), 1593; https://doi.org/10.3390/agronomy14071593 - 22 Jul 2024
Viewed by 250
Abstract
This study introduces a You Only Look Once (YOLO) model for detecting diseases in tomato leaves, utilizing YOLOV8s as the underlying framework. The tomato leaf images, both healthy and diseased, were obtained from the Plant Village dataset. These images were then enhanced, implemented, [...] Read more.
This study introduces a You Only Look Once (YOLO) model for detecting diseases in tomato leaves, utilizing YOLOV8s as the underlying framework. The tomato leaf images, both healthy and diseased, were obtained from the Plant Village dataset. These images were then enhanced, implemented, and trained using YOLOV8s using the Ultralytics Hub. The Ultralytics Hub provides an optimal setting for training YOLOV8 and YOLOV5 models. The YAML file was carefully programmed to identify sick leaves. The results of the detection demonstrate the resilience and efficiency of the YOLOV8s model in accurately recognizing unhealthy tomato leaves, surpassing the performance of both the YOLOV5 and Faster R-CNN models. The results indicate that YOLOV8s attained the highest mean average precision (mAP) of 92.5%, surpassing YOLOV5’s 89.1% and Faster R-CNN’s 77.5%. In addition, the YOLOV8s model is considerably smaller and demonstrates a significantly faster inference speed. The YOLOV8s model has a significantly superior frame rate, reaching 121.5 FPS, in contrast to YOLOV5’s 102.7 FPS and Faster R-CNN’s 11 FPS. This illustrates the lack of real-time detection capability in Faster R-CNN, whereas YOLOV5 is comparatively less efficient than YOLOV8s in meeting these needs. Overall, the results demonstrate that the YOLOV8s model is more efficient than the other models examined in this study for object detection. Full article
(This article belongs to the Section Precision and Digital Agriculture)
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18 pages, 2307 KiB  
Article
Germination Biology of Three Cyperaceae Weeds and Their Response to Pre- and Post-Emergence Herbicides in Paddy Fields
by Lilin Jiang, Ke Chai, Mujeeba Fida, Bin Fang, Kun Wang and Yaling Bi
Agronomy 2024, 14(7), 1592; https://doi.org/10.3390/agronomy14071592 - 22 Jul 2024
Viewed by 206
Abstract
(1) Background: Cyperaceae weeds have become a major type of weed in local paddy fields in China. (2) Methods: We assessed the impact of environmental factors, including temperature, light, salinity, water stress and soil depth, on the germination and emergence of three dominant [...] Read more.
(1) Background: Cyperaceae weeds have become a major type of weed in local paddy fields in China. (2) Methods: We assessed the impact of environmental factors, including temperature, light, salinity, water stress and soil depth, on the germination and emergence of three dominant Cyperaceae weeds: Cyperus difformis L., C. iria L. and Fimbristylis littoralis Gaudich. Using the dish dipping method, the performances of the pre- and post-emergence herbicides commonly used in paddy fields on three Cyperaceae weeds were evaluated using the pot method. (3) Results: The seeds optimally germinated at 35 °C in constant conditions and 25 °C/40 °C in alternating conditions. The seeds of the three Cyperaceae weeds were sensitive to light and could not germinate under dark conditions. The germination rate of the three weeds decreased with the increase in the NaCl concentration and water potential; the three weeds could not germinate at a 320 mmol·L−1 NaCl concentration and −0.1 MPa water potential. When the pH levels were 4 to 9, the germination rates of the three weeds were all greater than 80%. The burial depths to inhibit 50% of the emergence of C. difformis, C. iria and F. littoralis were 0.27, 1.06 and 0.42 cm, respectively. The control efficacy of the pre-emergence herbicides of pretilachlor, butachlor and oxyfluorfen on the three weeds were all above 90% at the recommended dose in the field. Halosulfuron-methyl, florpyrauxifen-benzyl and bentazone could effectively control the three Cyperaceae weeds; their performances on the three weeds at the 3- to 4-leaf stage were all above 82%. (4) Conclusions: The three Cyperaceae weed seeds have a strong adaptability to temperature, water potential, salinity and soil depth, and these weeds are sensitive to most pre- and post-emergence herbicides. Therefore, taking Cyperaceae weed seeds into the deep soil layer by tillage or selecting appropriate herbicides according to their growth stages can effectively control Cyperaceae weeds in rice fields. Full article
(This article belongs to the Section Weed Science and Weed Management)
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14 pages, 1321 KiB  
Article
Plant and Soil Effects of Alternative Sources of Phosphorous over Three Years of Application
by Anna Karpinska, Thomais Kakouli-Duarte, S.M. Ashekuzzaman, John Byrne, Achim Schmalenberger and Patrick J. Forrestal
Agronomy 2024, 14(7), 1591; https://doi.org/10.3390/agronomy14071591 - 22 Jul 2024
Viewed by 270
Abstract
Plant growth and food security depend heavily on phosphorous (P). Recovering and recycling P from animal, municipal, and food waste streams can significantly reduce dependency on traditional mineral P. This is particularly pertinent in the EU regions with limited native P supplies. The [...] Read more.
Plant growth and food security depend heavily on phosphorous (P). Recovering and recycling P from animal, municipal, and food waste streams can significantly reduce dependency on traditional mineral P. This is particularly pertinent in the EU regions with limited native P supplies. The agronomic performance of including P-based recycling-derived fertilisers (two struvite and two ashes) or cattle slurry was compared to a conventional mineral P fertilisation programme along with no P and no fertiliser controls over three years. A field-scale experiment was set up to evaluate the perennial ryegrass dry matter yield (DMY), P uptake, and soil test P effects. Struvite, ash, and cattle slurry proved effective in replacing P mineral fertiliser and produced yields similar to those of the mineral fertiliser programme. Differences were observed in plant P recovery, with struvite-based programmes achieving a significantly higher P recovery than ash-based programmes, which had the lowest plant P recovery. Differences in Morgan’s soil test P were also noted, with potato waste struvite (PWS) and poultry litter ash (PLA) showing significantly higher soil test P values. The findings strongly indicate that a range of recycled bio-based fertilisers from the bioeconomy can be used to reduce reliance on conventional imported mineral P fertiliser, with some programmes based on recycled fertilisers even surpassing the performance of conventional linear economy mineral fertilisers. Full article
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20 pages, 4078 KiB  
Article
Effects of Incubation Temperature and Sludge Addition on Soil Organic Carbon and Nitrogen Mineralization Characteristics in Degraded Grassland Soil
by Xuxu Min, Lie Xiao, Zhanbin Li, Peng Li, Feichao Wang, Xiaohuang Liu, Shuyi Chen, Zhou Wang and Lei Pan
Agronomy 2024, 14(7), 1590; https://doi.org/10.3390/agronomy14071590 - 21 Jul 2024
Viewed by 328
Abstract
Elucidating the characteristics and underlying mechanisms of soil organic carbon (SOC) and nitrogen mineralization in the context of sludge addition is vital for enhancing soil quality and augmenting the carbon sink capacity of soil. This study examined the chemical properties, enzyme dynamics, and [...] Read more.
Elucidating the characteristics and underlying mechanisms of soil organic carbon (SOC) and nitrogen mineralization in the context of sludge addition is vital for enhancing soil quality and augmenting the carbon sink capacity of soil. This study examined the chemical properties, enzyme dynamics, and organic carbon and nitrogen mineralization processes of soil from degraded grasslands on the Loess Plateau at various incubation temperatures (5, 15, 25, and 35 °C) and sludge addition rates (0%, 5.0%, 10.0%, and 20.0%) through a laboratory incubation experiment. The results showed that incubation temperature, sludge addition, and their interactive effects significantly altered the soil enzyme C:N, C:P, and N:P stoichiometries. The cumulative mineralization rates of SOC and nitrogen increased significantly with increasing incubation temperature and sludge addition rate. Principal component analysis revealed a significant linear correlation between cumulative SOC and nitrogen mineralization. Random forest analysis indicated that β-1,4-Glucosidase (BG), β-1,4-N-acetyglucosaminidase (NAG), cellobiohydrolase (CBH), ammonium nitrogen (NO3), enzyme C:P ratio, alkaline phosphatase (ALP), and incubation temperature were crucial determinants of cumulative SOC mineralization. Structural equation modeling demonstrated that sludge addition, NO3, NAG, ALP, and enzyme C:P positively impacted SOC mineralization, whereas dissolved organic carbon and BG had negative impacts. Conversely, incubation temperature negatively affected soil nitrogen mineralization, whereas NO3, available phosphorus, and ALP contributed positively. Sludge addition and temperature indirectly modulated soil net nitrogen mineralization by altering soil chemical properties and enzyme activities. These findings underscore the role of SOC and nitrogen mineralization as indicators for evaluating soil nutrient retention capabilities. Full article
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18 pages, 7039 KiB  
Article
Two-Stage Detection Algorithm for Plum Leaf Disease and Severity Assessment Based on Deep Learning
by Caihua Yao, Ziqi Yang, Peifeng Li, Yuxia Liang, Yamin Fan, Jinwen Luo, Chengmei Jiang and Jiong Mu
Agronomy 2024, 14(7), 1589; https://doi.org/10.3390/agronomy14071589 - 21 Jul 2024
Viewed by 281
Abstract
Crop diseases significantly impact crop yields, and promoting specialized control of crop diseases is crucial for ensuring agricultural production stability. Disease identification primarily relies on human visual inspection, which is inefficient, inaccurate, and subjective. This study focused on the plum red spot ( [...] Read more.
Crop diseases significantly impact crop yields, and promoting specialized control of crop diseases is crucial for ensuring agricultural production stability. Disease identification primarily relies on human visual inspection, which is inefficient, inaccurate, and subjective. This study focused on the plum red spot (Polystigma rubrum), proposing a two-stage detection algorithm based on deep learning and assessing the severity of the disease through lesion coverage rate. The specific contributions are as follows: We utilized the object detection model YOLOv8 to strip leaves to eliminate the influence of complex backgrounds. We used an improved U-Net network to segment leaves and lesions. We combined Dice Loss with Focal Loss to address the poor training performance due to the pixel ratio imbalance between leaves and disease spots. For inconsistencies in the size and shape of leaves and lesions, we utilized ODConv and MSCA so that the model could focus on features at different scales. After verification, the accuracy rate of leaf recognition is 95.3%, and the mIoU, mPA, mPrecision, and mRecall of the leaf disease segmentation model are 90.93%, 95.21%, 95.17%, and 95.21%, respectively. This research provides an effective solution for the detection and severity assessment of plum leaf red spot disease under complex backgrounds. Full article
(This article belongs to the Special Issue The Applications of Deep Learning in Smart Agriculture)
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28 pages, 2248 KiB  
Review
Zinc Oxide Nanoparticles in the “Soil–Bacterial Community–Plant” System: Impact on the Stability of Soil Ecosystems
by Elena I. Strekalovskaya, Alla I. Perfileva and Konstantin V. Krutovsky
Agronomy 2024, 14(7), 1588; https://doi.org/10.3390/agronomy14071588 - 21 Jul 2024
Viewed by 507
Abstract
The use of man-made nanoparticles (NPs) has increased exponentially in recent years, many of which accumulate in significant quantities in soil, including through use in agriculture as nanofertilizers and nanopesticides. ZnO NPs are more environmentally friendly but have specific antimicrobial activity, which can [...] Read more.
The use of man-made nanoparticles (NPs) has increased exponentially in recent years, many of which accumulate in significant quantities in soil, including through use in agriculture as nanofertilizers and nanopesticides. ZnO NPs are more environmentally friendly but have specific antimicrobial activity, which can affect soil microbiota, thereby influencing key microbial processes such as mineralization, nitrogen fixation and plant growth-promoting activities. Their behavior and persistence in soil depend on their chemical nature and soil characteristics. This review summarizes the applications of ZnO NPs in soil systems and their effects on various plants and soil microorganisms, particularly rhizobacteria that promote plant growth. A stimulating effect of ZnO NPs on the morphometric and biochemical characteristics of plants, as well as on soil microbiota and its activity at relatively low concentrations of up to 500 mg/mL and 250 mg/kg, respectively, is observed. As the concentration of ZnO NPs increases above these limits, toxic effects appear. The different effects of ZnO NPs are related to their size, dose, duration of exposure, solubility in water, as well as soil type, acidity and organic matter content. The review substantiates the need to study the behavior of ZnO NPs in the “soil-plant-microbiota” system for the possibility of using nanotechnologies in the agricultural industry and ensuring the safety of agricultural products. Full article
(This article belongs to the Special Issue Cutting Edge Research of Nanoparticles Application in Agriculture)
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17 pages, 7932 KiB  
Article
ICS-ResNet: A Lightweight Network for Maize Leaf Disease Classification
by Zhengjie Ji, Shudi Bao, Meng Chen and Linjing Wei
Agronomy 2024, 14(7), 1587; https://doi.org/10.3390/agronomy14071587 - 21 Jul 2024
Viewed by 300
Abstract
The accurate identification of corn leaf diseases is crucial for preventing disease spread and improving corn yield. Plant leaf images are often affected by factors such as complex backgrounds, climate, light, and sample data imbalance. To address these issues, we propose a lightweight [...] Read more.
The accurate identification of corn leaf diseases is crucial for preventing disease spread and improving corn yield. Plant leaf images are often affected by factors such as complex backgrounds, climate, light, and sample data imbalance. To address these issues, we propose a lightweight convolutional neural network, ICS-ResNet, based on ResNet50. This network incorporates improved spatial and channel attention modules as well as a deep separable residual structure to enhance recognition accuracy. (1) The residual connections in the ResNet network prevent gradient loss during deep network training. (2) The improved channel attention (ICA) and spatial attention (ISA) modules fully utilize semantic information from different feature layers to accurately localize key features of the network. (3) To reduce the number of parameters and lower computational costs, we replace traditional convolutional computation with a depth-separable residual structure. (4) We also employ cosine annealing to dynamically adjust the learning rate, enhancing the network’s training stability, improving model convergence, and preventing local optima. Experiments on the corn dataset in Plant Village compare the proposed ICS-ResNet with eight popular networks: CSPNet, InceptionNet_v3, EfficientNet, ShuffleNet, MobileNet, ResNet50, ResNet101 and ResNet152. The results show that the ICS-ResNet achieves an accuracy of 98.87%, which is 5.03%, 3.18%, 1.13%, 1.81%, 1.13%, 0.68%, 0.44% and 0.60% higher than the other networks, respectively. Furthermore, the number of parameters and computations are reduced by 69.21% and 54.88%, respectively, compared to the original ResNet50 network, significantly improving the efficiency of corn leaf disease classification. The study provides strong technical support for sustainable agriculture and the promotion of agricultural science and technology innovation. Full article
(This article belongs to the Section Pest and Disease Management)
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23 pages, 11618 KiB  
Article
Identification of Insect Pests on Soybean Leaves Based on SP-YOLO
by Kebei Qin, Jie Zhang and Yue Hu
Agronomy 2024, 14(7), 1586; https://doi.org/10.3390/agronomy14071586 - 20 Jul 2024
Viewed by 371
Abstract
Soybean insect pests can seriously affect soybean yield, so efficient and accurate detection of soybean insect pests is crucial for soybean production. However, pest detection in complex environments suffers from the problems of small pest targets, large inter-class feature similarity, and background interference [...] Read more.
Soybean insect pests can seriously affect soybean yield, so efficient and accurate detection of soybean insect pests is crucial for soybean production. However, pest detection in complex environments suffers from the problems of small pest targets, large inter-class feature similarity, and background interference with feature extraction. To address the above problems, this study proposes the detection algorithm SP-YOLO for soybean pests based on YOLOv8n. The model utilizes FasterNet to replace the backbone of YOLOv8n, which reduces redundant features and improves the model’s ability to extract effective features. Second, we propose the PConvGLU architecture, which enhances the capture and representation of image details while reducing computation and memory requirements. In addition, this study proposes a lightweight shared detection header, which enables the model parameter amount computation to be reduced and the model accuracy to be further improved by shared convolution and GroupNorm. The improved model achieves 80.8% precision, 66.4% recall, and 73% average precision, which is 6%, 5.4%, and 5.2%, respectively, compared to YOLOv8n. The FPS reaches 256.4, and the final model size is only 6.2 M, while the number of computational quantities of covariates is basically comparable to that of the original model. The detection capability of SP-YOLO is significantly enhanced compared to that of the existing methods, which provides a good solution for soybean pest detection. SP-YOLO provides an effective technical support for soybean pest detection. Full article
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16 pages, 2453 KiB  
Article
Combination of Polymer-Coated Urea and Rapid-Release Urea Increases Grain Yield and Nitrogen Use Efficiency of Rice by Improving Root and Shoot Activities
by Rongyue Xu, Jiangyao Fu, Yajun Zhang, Zhiwei Sun, Yuemei Xu, Weiyang Zhang, Kuanyu Zhu, Junfei Gu, Zhiqin Wang and Jianchang Yang
Agronomy 2024, 14(7), 1585; https://doi.org/10.3390/agronomy14071585 - 20 Jul 2024
Viewed by 310
Abstract
The use of polymer-coated urea (PCU) can improve nitrogen use efficiency (NUE), compared to the application of rapid-release urea (RU). However, the effect of PCU-based nitrogen management on grain yield and the NUE of rice and its underlying mechanism remain unclear. A japonica [...] Read more.
The use of polymer-coated urea (PCU) can improve nitrogen use efficiency (NUE), compared to the application of rapid-release urea (RU). However, the effect of PCU-based nitrogen management on grain yield and the NUE of rice and its underlying mechanism remain unclear. A japonica rice cultivar Jinxiangyu 1 was grown in the field with four treatments including N omission (0N), split application of RU (Control), one-time application of 100% PCU (T1), and one-time application of 70% PCU + 30% RU (T2). Results showed that, compared to the control, the grain yield was significantly increased in the T2 treatment, while it was comparable in the T1 treatment. This was mainly due to increased total spikelets in the T2 treatment. Root oxidation activity (ROA) and root zeatin (Z) + zeatin riboside (ZR) content during booting were the distinct advantages of the T2 treatment, compared to either the control or T1 treatment, exhibiting significant or highly significant correlations with leaf photosynthesis. This process contributed significantly to total spikelets and total N uptake. Additionally, the T2 treatment absorbed more N than the control without reducing the internal N use efficiency (IEN), primarily due to its unchanged harvest index (HI) driven by comparable non-structural carbohydrate remobilization. In conclusion, combining PCU with RU can enhance the coordination of root and shoot traits during booting while maintaining a competitive HI at maturity, thereby significantly improving grain yield and achieving a balance in N uptake and utilization. Full article
(This article belongs to the Section Farming Sustainability)
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17 pages, 1539 KiB  
Article
Managing Residue Return Increases Soil Organic Carbon, Total Nitrogen in the Soil Aggregate, and the Grain Yield of Winter Wheat
by Yuhai Tang, Xiangju Cui, Haicheng Xu, Dianliang Peng and Bin Liang
Agronomy 2024, 14(7), 1584; https://doi.org/10.3390/agronomy14071584 - 20 Jul 2024
Viewed by 295
Abstract
Soil tillage and maize residues return are important practices for tackling and promoting soil quality and improving crop yield in the North China Plain (NCP), where winter wheat production is threatened by soil deterioration. Although maize residues incorporation with rotary tillage (RS) or [...] Read more.
Soil tillage and maize residues return are important practices for tackling and promoting soil quality and improving crop yield in the North China Plain (NCP), where winter wheat production is threatened by soil deterioration. Although maize residues incorporation with rotary tillage (RS) or deep plowing tillage (DS) is widespread in this region, only few studies have focused on rotation tillage. Four practices, namely RT (continuous rotary tillage without maize residues return), RS, DS, and RS/DS (rotary tillage every year and deep plowing interval of 2 years), were evaluated under field conditions lasting a period of 5 years. After a 5-year field experiment, the mean soil bulk density of the 0–30 cm soil layer decreased significantly with RS, DS, and RS/DS, i.e., by 4.19%, 6.33%, and 6.71% compared with RT, respectively. The treatments greatly improved the total soil porosity, soil aggregate size distribution, soil aggregate stability, and the root length density in the 0–30 cm soil layers. Residues return with DS and RS/DS treatments significantly increased the soil organic carbon (SOC) and total nitrogen (TN) storage in the 0–30 cm soil layer, mainly owed to the increases in the SOC and TN pool associated with the macro-aggregate. A positive trend in the grain yield was noted under both DS and RS/DS conditions, whereas a decreasing tendency was presented in continuous rotary treatments. In summary, RS/DS treatment significantly increased the amount of SOC and TN, improved the particle size distribution of soil aggregates, and thus improved the soil’s physicochemical properties, which is beneficial for wheat to achieve high yields. Our results suggested that RS/DS was a highly efficient practice to improve soil quality and increase crop production in the NCP. Full article
(This article belongs to the Special Issue Soil Organic Matter and Tillage)
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18 pages, 2256 KiB  
Article
Biochar Co-Compost: A Promising Soil Amendment to Restrain Greenhouse Gases and Improve Rice Productivity and Soil Fertility
by Muhammad Umair Hassan, Guoqin Huang, Rizwan Munir, Tahir Abbas Khan and Mehmood Ali Noor
Agronomy 2024, 14(7), 1583; https://doi.org/10.3390/agronomy14071583 - 20 Jul 2024
Viewed by 275
Abstract
Agriculture is a major source of greenhouse gas (GHG) emissions. Biochar has been recommended as a potential strategy to mitigate GHG emissions and improve soil fertility and crop productivity. However, few studies have investigated the potential of biochar co-compost (BCC) in relation to [...] Read more.
Agriculture is a major source of greenhouse gas (GHG) emissions. Biochar has been recommended as a potential strategy to mitigate GHG emissions and improve soil fertility and crop productivity. However, few studies have investigated the potential of biochar co-compost (BCC) in relation to soil properties, rice productivity, and GHG emissions. Therefore, we examined the potential of BC, compost (CP), and BCC in terms of environmental and agronomic benefits. The study comprised four different treatments: control, biochar, compost, and biochar co-compost. The application of all of the treatments increased the soil pH; however, BC and BCC remained the top performers. The addition of BC and BBC also limited the ammonium nitrogen (NH4+-N) availability and increased soil organic carbon (SOC), which limited the GHG emissions. Biochar co-compost resulted in fewer carbon dioxide (CO2) emissions, while BC resulted in fewer methane (CH4) emissions, which was comparable with BCC. Moreover, BC caused a marked reduction in nitrous oxide (N2O) emissions that was comparable to BCC. This reduction was attributed to increased soil pH, nosZ, and nirK abundance and a reduction in ammonia-oxidizing archaea (AOA) and ammonia-oxidizing bacteria (AOB) abundance. The application of different amendments, particularly BCC, favored rice growth and productivity by increasing nutrient availability, soil carbon, and enzymatic activities. Lastly, BCC and BC also increased the abundance and diversity of soil bacteria, which favored plant growth and caused a reduction in GHG emissions. Our results suggest that BCC could be an important practice to recycle organic sources while optimizing climate change and crop productivity. Full article
(This article belongs to the Section Agricultural Biosystem and Biological Engineering)
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12 pages, 2828 KiB  
Article
Multidimensional Quality Characteristics of Sichuan South-Road Dark Tea and Its Chemical Prediction
by Yao Zou, Xian Li and Deyang Han
Agronomy 2024, 14(7), 1582; https://doi.org/10.3390/agronomy14071582 - 20 Jul 2024
Viewed by 236
Abstract
The distinctive quality of Sichuan south-road dark tea (SSDT) is gradually disappearing with processing innovation. Here, near-infrared (NIR) spectroscopy (NIRS) and spectrofluorometric techniques were utilized to determine the spectral characteristics of dried SSDT and its brew, respectively. Combined with chemical analysis, the multidimensional [...] Read more.
The distinctive quality of Sichuan south-road dark tea (SSDT) is gradually disappearing with processing innovation. Here, near-infrared (NIR) spectroscopy (NIRS) and spectrofluorometric techniques were utilized to determine the spectral characteristics of dried SSDT and its brew, respectively. Combined with chemical analysis, the multidimensional quality characteristics of SSDT will be presented. Finally, the NIR spectral fingerprint of dried SSDT was observed, with Kangzhuan (KZ) and Jinjian (JJ) showing a very similar NIR spectrum. The SiPLS models effectively predicted the levels of theabrownin, caffeine, and epigallocatechin gallate, based on the NIR spectrum, with root-mean-square errors of calibration of 0.15, 0.12, and 0.02 for each chemical compound, root-mean-square errors of prediction of 0.20, 0.09, and 0.03, and both corrected and predicted correlation coefficients greater than 0.90. Meanwhile, the fluorescence characteristics of the SSDT brew were identified based on the parallel factor analysis for the fluorescence excitation–emission matrix (EEM). The KZ and JJ brews could be classified with 100% accuracy using extreme-gradient-boosting discriminant analysis. The integration of NIRS and fluorometric EEM seems to be a powerful technique for characterizing SSDTs, and the results can greatly benefit the production and quality control of SSDTs. Full article
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17 pages, 13436 KiB  
Article
The Influence of the Distribution Law and Uniformity of a Threshed Mixture with the Working Parameters of a Soybean Threshing Device
by Yifan Hu, Zhong Tang, Shiguo Wang, Bin Li, Xiaohu Guo and Shuren Chen
Agronomy 2024, 14(7), 1581; https://doi.org/10.3390/agronomy14071581 - 20 Jul 2024
Viewed by 193
Abstract
Soybean plants cultivated using mulched drip irrigation planting technology have the following characteristics during the harvest period: green stems and leaves, and a high straw/grain ratio. Moreover, the threshing device of a soybean combine harvester is difficult to adapt to, resulting in an [...] Read more.
Soybean plants cultivated using mulched drip irrigation planting technology have the following characteristics during the harvest period: green stems and leaves, and a high straw/grain ratio. Moreover, the threshing device of a soybean combine harvester is difficult to adapt to, resulting in an increase in the accumulation and unevenness of the threshed mixture. This leads to an increase in impurity content and the loss rate. We conducted a single-factor experiment on a self-developed longitudinal/axial-flow soybean threshing and separation test bench, employing drum speed, feeding rate, and threshing clearance as experimental factors. The influence of the soybean threshing and separation device’s working parameters on the distribution and uniformity of the threshed mixture in the axial and radial directions of the drum was explored through experiments. The results showed that the mass of the threshed mixture and soybean seeds showed a trend of first rapidly increasing and then slowly decreasing in the axial direction of the drum. Additionally, the mass showed a distribution feature of large values on both sides and small values in the middle in the radial direction. A lower drum speed, greater threshing clearance, and a smaller feeding rate make the radial distribution of a threshed mixture more uniform. Based on the combination of the crushing rate and unthreshed rate, the optimal working parameter combination was determined to be as follows: a drum speed of 500 r/min, a feeding rate of 6 kg/s, and a threshing clearance of 25 mm. The findings of this research offer valuable insights for the structural optimization and design enhancement of threshing and cleaning mechanisms within soybean combine harvesters. Full article
(This article belongs to the Section Agricultural Biosystem and Biological Engineering)
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17 pages, 4358 KiB  
Article
Distribution Characteristics and Prediction of Temperature and Relative Humidity in a South China Greenhouse
by Xinyu Wei, Bin Li, Huazhong Lu, Jiaming Guo, Zhaojie Dong, Fengxi Yang, Enli Lü and Yanhua Liu
Agronomy 2024, 14(7), 1580; https://doi.org/10.3390/agronomy14071580 - 20 Jul 2024
Viewed by 225
Abstract
South China has a climate characteristic of high temperature and high humidity, and the temperature and relative humidity inside a Venlo greenhouse are higher than those in the atmosphere. This paper studied the effect of ventilation conditions on the spatial and temporal distribution [...] Read more.
South China has a climate characteristic of high temperature and high humidity, and the temperature and relative humidity inside a Venlo greenhouse are higher than those in the atmosphere. This paper studied the effect of ventilation conditions on the spatial and temporal distribution of temperature and relative humidity in a Venlo greenhouse. Two ventilation conditions, with and without a fan-pad system, were studied. A GA + BP neural network was applied to predict the temperature and relative humidity in fan-pad ventilation in the greenhouse. The results show that the temperature in the Venlo greenhouse ranged from 15.8 °C to 48.5 °C, and the relative humidity ranged from 24.9% to 100% during the tomato-planting cycle. The percentage of days when the temperature exceeded 35 °C was 67.3%, and the percentage of days when the average relative humidity exceeded 70% was 83.7%. The maximum temperature differences between the three heights under NV (Natural Ventilation) and FPV (Fan-pad Ventilation) conditions were 3.4 °C and 4.5 °C, respectively. The maximum relative humidity differences between the three heights under NV and FPV conditions were 8.4% and 21.7%, respectively. The maximum temperature difference in the longitudinal section under the FPV conditions was 3.2 °C, while the relative humidity was 11.4%. The cooling efficiency of the fan-pad system ranged from 16.6% to 70.2%. The non-uniform coefficients of the temperature under the FPV conditions were higher than those under the NV conditions, while the nonuniform coefficients of the relative humidity were the highest during the day. The R2, MAE, MAPE and RMSE of the temperature-testing model were 0.91, 0.94, 0.11, and 1.33, respectively, while those of relative humidity model were 0.93, 2.83, 0.10, and 3.86, respectively. The results provide a reference for the design and management of Venlo greenhouses in South China. Full article
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18 pages, 6035 KiB  
Article
Rice Growth and Leaf Physiology in Response to Four Levels of Continuous Drought Stress in Southern China
by Wenlong Zhang, Hong Shi, Shuo Cai, Qiaoling Guo, Yulong Dai, Haiyuan Wang, Shaoyuan Wan and Yizhe Yuan
Agronomy 2024, 14(7), 1579; https://doi.org/10.3390/agronomy14071579 - 19 Jul 2024
Viewed by 319
Abstract
Exploring the growth and physiological response mechanisms of rice under continuous drought stress circumstances can provide a significant scientific foundation and technological assistance for meeting drought difficulties, improving drought resistance and rice (Oryza sativa L.) output, and ensuring food security. In this [...] Read more.
Exploring the growth and physiological response mechanisms of rice under continuous drought stress circumstances can provide a significant scientific foundation and technological assistance for meeting drought difficulties, improving drought resistance and rice (Oryza sativa L.) output, and ensuring food security. In this study, a rice field experiment was conducted under a rain shelter with five different treatments set up: P1 (drought stress from tillering stage), P2 (drought stress from jointing–booting stage), P3 (drought stress from heading–flowering stage), P4 (drought stress from grain filling stage), and CK (adequate water management throughout the growth stage). Continuous drought stress from different growth stages with four levels (mild, medium, moderate, and severe). The results showed that the effects of different drought stress treatments on rice growth varied significantly. Compared with the CK treatment, plant height was reduced by 12.10%, 8.14%, 3.83%, and 1.06% in the P1, P2, P3, and P4 treatments, respectively, and the number of tillers was reduced by 23.83%, 18.91%, 13.47%, and 8.68%, respectively. With the increase in drought stress levels, SPAD values and Rubisco activity of rice leaf continued to decrease; SOD activity showed a decreasing trend, but the decreasing trend of POD and CAT activities was not significant, while MDA content showed an increasing trend. For yield components, continuous drought stress significantly reduced spike length of rice by an average of 3.5%, effective number of spikes by 18.9%, thousand grain weight by 3.7%, grain number per spike by 11.6%, and fruiting rate by 1.8%, respectively, compared to CK treatments during the growth period. In general, continuous drought stress during the early growth period affected the effective spike number and the grain number per spike. Continuous drought stress after the grain filling stage had the least effect on yield (17.62% of yield reduction), and water use efficiency (1.76 kg m−3) was much higher than other treatments. These researchers’ findings provide insight into how rice physiology and growth react to continuous drought stress, which is significant for agricultural operations. Full article
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17 pages, 4856 KiB  
Article
Preparation and Evaluation of a Temperature-Sensitive Cuelure Nano-Controlled Release Agent
by Aqiang Wang, Sihua Peng, Bei Zeng, Yuyang Lian, Jingjing Jia, Qiongkuan Zhang, Qianxing Wu and Shihao Zhou
Agronomy 2024, 14(7), 1578; https://doi.org/10.3390/agronomy14071578 - 19 Jul 2024
Viewed by 330
Abstract
Cuelure, an effective lure specifically targeting Tephritid fruit flies, has been widely adopted and applied in the monitoring and control of these pests, providing significant support for agricultural pest management. However, its uncontrollable release speed and duration usually lead to a lot of [...] Read more.
Cuelure, an effective lure specifically targeting Tephritid fruit flies, has been widely adopted and applied in the monitoring and control of these pests, providing significant support for agricultural pest management. However, its uncontrollable release speed and duration usually lead to a lot of waste, diminishing its effectiveness and increasing the cost of pest control. In order to solve these problems, we focused on Zeugodacus cucurbitae Coquillett and developed a temperature-sensitive nano-controlled release agent for cuelure. The release rate of this agent can be adjusted by adjusting the ambient temperature. The results show that the temperature-sensitive cuelure nano-controlled release agent demonstrates remarkable temperature-responsive controlled release characteristics. It still exhibits exceptional stability even after being subjected to high-temperature treatment at 60 °C for a week, and the trapping efficiency of this attractant remains between 73% and 75%. This study not only holds immense practical value in monitoring, warning, and managing of fruit fly pests, but it also lays a novel theoretical foundation for the development of insect attractants. Full article
(This article belongs to the Special Issue Green Control of Pests and Pathogens in Tropical Plants)
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15 pages, 3931 KiB  
Article
Poly-γ-Glutamic Acid-Induced Assemblage of Root Endophytic Microbiota Enhances Disease Resistance in Chrysanthemum Plants
by Feng Cui, Lin Zhu and Cheng Zhou
Agronomy 2024, 14(7), 1577; https://doi.org/10.3390/agronomy14071577 - 19 Jul 2024
Viewed by 280
Abstract
Plant microbiota composition changes with the environment and host state, suggesting potential for engineering. However, engineering plant microbiomes is promising but currently undeveloped. This study investigated the role of root-associated bacterial microbiomes in poly-γ-glutamic acid (γ-PGA)-induced plant disease resistance. γ-PGA treatment significantly reduced [...] Read more.
Plant microbiota composition changes with the environment and host state, suggesting potential for engineering. However, engineering plant microbiomes is promising but currently undeveloped. This study investigated the role of root-associated bacterial microbiomes in poly-γ-glutamic acid (γ-PGA)-induced plant disease resistance. γ-PGA treatment significantly reduced wilt disease caused by Fusarium oxysporum f. sp. chrysanthemi (Foc). Quantitative PCR analysis revealed a 73.2% reduction in Foc abundance in the roots following γ-PGA exposure. However, the disease suppression effect of γ-PGA was notably weakened in sterilized soils or soils treated with bactericide, indicating the essential role of root-associated microbiomes in this process. 16S rRNA gene amplicon sequencing showed that γ-PGA treatments increased the abundance of Proteobacteria, particularly the family Burkholderiaceae, in the roots. Metabolite analysis further indicated that γ-PGA treatment significantly elevated salicylic acid (SA) levels, suggesting that SA played a critical role in the assembly of the root microbiome under γ-PGA treatment. Further experiments confirmed the antagonistic activity and induced systemic resistance (ISR) of Burkholderia sp. against Fusarium wilt. Burkholderia sp. CM72 was found to enhance plant disease resistance through antibiosis and activation of jasmonic acid (JA)-related pathways. In summary, γ-PGA significantly improved plant disease resistance by modulating the SA pathway and promoted the colonization of beneficial microbiota, particularly with Burkholderia sp. Full article
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12 pages, 1004 KiB  
Perspective
Research Progress Related to Sorghum Biological Nitrification Inhibitors
by Fangfang Qin, Hao Su, Lei Sun and Yaying Li
Agronomy 2024, 14(7), 1576; https://doi.org/10.3390/agronomy14071576 - 19 Jul 2024
Viewed by 184
Abstract
To meet the growing population’s demand for food, humans have introduced large amounts of nitrogen fertilizers into agricultural systems, resulting in highly nitrified environments in most farmland soils. In highly nitrified environments, the application of nitrogen fertilizer easily leads to the formation of [...] Read more.
To meet the growing population’s demand for food, humans have introduced large amounts of nitrogen fertilizers into agricultural systems, resulting in highly nitrified environments in most farmland soils. In highly nitrified environments, the application of nitrogen fertilizer easily leads to the formation of nitrate (NO3) and subsequent leaching, resulting in very low utilization rates. Moreover, nitrogen loss can cause harm to both the environment and human health, making it necessary to inhibit the nitrification process. Nitrification inhibitors can suppress nitrification, and inhibitors derived biologically from plant roots are gaining attention due to their low cost and environmental friendliness. Sorghum, as a crop capable of growing in arid environments, holds economic value and also possesses the ability to secrete biological nitrification inhibitors. This article utilizes sorghum as a case study to review different types of BNIs (MHPP, sorgoleone, and sakuranetin), their mechanisms of inhibition, and influencing factors. This article summarizes the contributions of these inhibitors in reducing N2O emissions and increasing food production, while also providing insight into future research directions for sorghum’s biological nitrification inhibitors in terms of agricultural production efficiency. BNIs are expected to play an important role in improving agricultural production and reducing environmental pollution. Full article
(This article belongs to the Section Soil and Plant Nutrition)
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20 pages, 8757 KiB  
Review
Current Status of Yam Diseases and Advances of Their Control Strategies
by Hamza Tariq, Chun Xiao, Lanning Wang, Hongjun Ge, Gang Wang, Danyu Shen and Daolong Dou
Agronomy 2024, 14(7), 1575; https://doi.org/10.3390/agronomy14071575 - 19 Jul 2024
Viewed by 223
Abstract
Yam (Dioscorea spp.) is an important tuber crop consumed globally. However, stable yam production faces challenges from a variety of diseases caused by fungi, nematodes, viruses, and bacteria. Prominent diseases such as anthracnose, leaf spot, yam wilt, dry rot, and crazy root [...] Read more.
Yam (Dioscorea spp.) is an important tuber crop consumed globally. However, stable yam production faces challenges from a variety of diseases caused by fungi, nematodes, viruses, and bacteria. Prominent diseases such as anthracnose, leaf spot, yam wilt, dry rot, and crazy root syndrome, currently pose serious threats to yam yields. These diseases not only result in quality degradation but also cause great economic losses. This review summarizes the damages, symptoms, causal agents, and epidemic factors of major yam diseases. It also outlines a comprehensive disease control strategy that includes the use of resistant varieties, proper crop rotation, sanitation measures, and the application of agrochemicals and biocontrol agents. Additionally, this review addresses future perspectives on risk factors and knowledge gaps, aiming to serve as a reference for in-depth research into advanced disease monitoring and control technologies for yams. Full article
(This article belongs to the Special Issue Phytopathogens and Crop Diseases)
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18 pages, 2792 KiB  
Article
Penalties in Granule Size Distribution and Viscosity Parameters of Starch Caused by Lodging in Winter Wheat
by Dianliang Peng, Jingmin Zhang, Lingbin Meng, Mei Liu, Yuhai Tang, Xingcui Wang, Wenxia Yang, Haicheng Xu and Dongqing Yang
Agronomy 2024, 14(7), 1574; https://doi.org/10.3390/agronomy14071574 - 19 Jul 2024
Viewed by 229
Abstract
Granule size distribution of wheat starch is an important characteristic that could affect the functionality of wheat (Triticum aestivum L.) products. Lodging is a major limiting factor for wheat production. Few studies have been conducted to clarify how lodging influences the granule [...] Read more.
Granule size distribution of wheat starch is an important characteristic that could affect the functionality of wheat (Triticum aestivum L.) products. Lodging is a major limiting factor for wheat production. Few studies have been conducted to clarify how lodging influences the granule size distribution and viscosity parameters of starch in wheat grains. Two growing seasons, two high-yield winter wheat cultivars, and five artificial lodging treatments were imposed. The results indicated that lodging significantly reduced the content of starch and increased that of protein. Additionally, lodging caused a marked drop in both starch and protein yields. The relative loss of grain yield, starch yield, harvest index, and protein yield all differed remarkably among lodging treatments with a ranking of L2 > L1 > L4 > L3. Lodging also led to a reduction in the proportion (both by volume and by surface area) of B-type granules and a corresponding increase in that of A-type granules, and the more serious the lodging degree, the greater effect on the changes in these proportions. The smaller starch granules predominated in number, even though their collective contribution to the overall volume is was relatively minor. Meanwhile, it was found that the peak viscosity, hold viscosity, final viscosity, breakdown viscosity, and rebound value of wheat starch were significantly decreased by lodging. Correlation analysis showed that the peak and final viscosities were negatively correlated with volume percentages of A-type starch granules, but were positively correlated with B-type granules. This indicates that B-type granules have higher peak and final viscosities compared with A-type granules in wheat kernels. Lodging can reduce the proportion of B-type starch granules, and thus reduce the peak and the final viscosity in wheat grain. Full article
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20 pages, 4766 KiB  
Article
Assessing the Evolution of Stability and Maturity in Co-Composting Sheep Manure with Green Waste Using Physico-Chemical and Biological Properties and Statistical Analyses: A Case Study of Botanique Garden in Rabat, Morocco
by Majda Oueld Lhaj, Rachid Moussadek, Latifa Mouhir, Meriem Mdarhri Alaoui, Hatim Sanad, Oumaima Iben Halima and Abdelmjid Zouahri
Agronomy 2024, 14(7), 1573; https://doi.org/10.3390/agronomy14071573 - 19 Jul 2024
Viewed by 183
Abstract
Organic waste utilization stands as a pivotal approach to ecological and economic sustainability. This study aimed to assess the stability, maturity, and evolution of co-composts comprising various blends of green waste (GW) and sheep manure (SM). Employing a diverse array of physico-chemical and [...] Read more.
Organic waste utilization stands as a pivotal approach to ecological and economic sustainability. This study aimed to assess the stability, maturity, and evolution of co-composts comprising various blends of green waste (GW) and sheep manure (SM). Employing a diverse array of physico-chemical and biological parameters, we investigated the co-composting process over 120 days. Three types of garden waste (mixture of green waste (MGW), fallen leaves (FL), and grass cutting (GC)) were utilized. The results revealed significant compost transformation, evident by odor and insect absence and a shift to dark brown coloration, indicating maturation. The compost C2, derived from FL, exhibited superior soil amendment potential. Significantly, it exhibited a pH level of 6.80, an EC of 2.45 mS/cm, and an OM content of 55%, along with a C/N ratio of 16.15. Analysis of the macronutrients revealed values of 1.98% for TN, 3.22% for TP, and 0.61% for K. Crucially, the compost showed no phytotoxic effects and boasted a high GI of 94.20% and a low respiration rate of 4.02 mg/50 g, indicating its stability and appropriateness for agricultural application. Our findings underscore compost’s potential as an eco-friendly soil amendment, offering valuable insights for sustainable agricultural management and supporting the circular economy. Full article
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15 pages, 20124 KiB  
Article
Molecular Mechanism of Pyrroloquinoline Quinone-Mediated Rice Tolerance to Imidazolinone Herbicide Imazamox
by Sifu Li, Shiyuan Hu, Kai Luo, Tao Tang, Guolan Ma, Ducai Liu, Yajun Peng, Yang Liu, Yuzhu Zhang and Lianyang Bai
Agronomy 2024, 14(7), 1572; https://doi.org/10.3390/agronomy14071572 - 19 Jul 2024
Viewed by 234
Abstract
The Clearfield® technology is an useful tool for controlling weedy rice due to the effectiveness of imazamox and the cultivation of rice varieties resistant to imidazolines. However, residual imazamox in the soil probably causes phytotoxicity to subsequent non-resistant rice crops. We previously [...] Read more.
The Clearfield® technology is an useful tool for controlling weedy rice due to the effectiveness of imazamox and the cultivation of rice varieties resistant to imidazolines. However, residual imazamox in the soil probably causes phytotoxicity to subsequent non-resistant rice crops. We previously found that pyrroloquinoline quinone (PQQ), a bioactive elicitor, can enhance rice tolerance to imazamox. In this study, we explored the molecular mechanism of PQQ-mediated rice tolerance to imazamox by RNA-seq analysis, real-time quantitative PCR (RT-qPCR) assay, and enzyme activity assay. The results indicated that compared to imazamox at 66.7 mg a.i./L (IMA) alone, rice plants treated with imazamox at 66.7 mg a.i./L and PQQ at 0.66 mg a.i./L (IMA + PQQ) exhibited significantly reduced sensitivity to imazamox. Seven days post-treatment, IMA + PQQ-treated rice plants showed partial chlorosis and leaf curling, but IMA-treated rice plants had severe wilting and died. The fresh weight inhibition rate was 29.3% in the IMA + PQQ group, significantly lower than that of 56.6% in the IMA group alone. RNA-seq analysis showed differentially expressed genes were mainly involved in phenylpropanoid biosynthesis, diterpenoid biosynthesis, and MAPK signaling pathways in response to IMA + PQQ treatment. Both RNA-seq analysis and RT-qPCR assay showed that the expression of OsCATB gene in the catalase (CAT) gene family was upregulated at 12 h, the expression of OsGSTU1 gene was upregulated at 12, 24, and 48 h, while the expressions of OsABCB2, OsABCB11, and OsABCG11 genes were upregulated at 24 and 48 h. Enzyme activity assays revealed that the activity of superoxide dismutase in the IMA + PQQ group was increased by 47.45~120.31% during 12~72 h, compared to that in the IMA group. CAT activity in the IMA + PQQ group was increased by 123.72 and 59.04% at 12 and 48 h, respectively. Moreover, malondialdehyde levels indicative of oxidative damage were consistently lower in IMA + PQQ-treated plants, with a reduction of 46.29, 11.37, and 14.50% at 12, 36, and 72 h, respectively. Overall, these findings discover that PQQ has potential in reducing imazamox phytotoxicity in rice by enhancing antioxidant enzyme activities and regulating oxidative stress responses. They will provide valuable strategies for improving imazamox tolerance in crops. Full article
(This article belongs to the Section Weed Science and Weed Management)
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18 pages, 6988 KiB  
Article
SAW-YOLO: A Multi-Scale YOLO for Small Target Citrus Pests Detection
by Xiaojiang Wu, Jinzhe Liang, Yiyu Yang, Zhenghao Li, Xinyu Jia, Haibo Pu and Peng Zhu
Agronomy 2024, 14(7), 1571; https://doi.org/10.3390/agronomy14071571 - 19 Jul 2024
Viewed by 252
Abstract
Citrus pests pose a major threat to both citrus yield and fruit quality. The early prevention of pests is essential for sustainable citrus cultivation, cost savings, and the reduction of environmental pollution. Despite the increasing application of deep learning techniques in agriculture, the [...] Read more.
Citrus pests pose a major threat to both citrus yield and fruit quality. The early prevention of pests is essential for sustainable citrus cultivation, cost savings, and the reduction of environmental pollution. Despite the increasing application of deep learning techniques in agriculture, the performance of existing models for small target detection of citrus pests is limited, mainly in terms of information bottlenecks that occur during the transfer of information. This hinders its effectiveness in fully automating the detection of citrus pests. In this study, a new approach was introduced to overcome these limitations. Firstly, a comprehensive large-scale dataset named IP-CitrusPests13 was developed, encompassing 13 distinct citrus pest categories. This dataset was amalgamated from IP102 and web crawlers, serving as a fundamental resource for precision-oriented pest detection tasks in citrus farming. Web crawlers can supplement information on various forms of pests and changes in pest size. Using this comprehensive dataset, we employed the SPD Module in the backbone network to preserve fine-grained information and prevent the model from losing important information as the depth increased. In addition, we introduced the AFFD Head detection module into the YOLOv8 architecture, which has two important functions that effectively integrate shallow and deep information to improve the learning ability of the model. Optimizing the bounding box loss function to WIoU v3 (Wise-IoU v3), which focuses on medium-quality anchor frames, sped up the convergence of the network. Experimental evaluation on a test set showed that the proposed SAW-YOLO (SPD Module, AFFD, WIoU v3) model achieved an average accuracy of 90.3%, which is 3.3% higher than the benchmark YOLOv8n model. Without any significant enlargement in the model size, state-of-the-art (SOTA) performance can be achieved in small target detection. To validate the robustness of the model against pests of various sizes, the SAW-YOLO model showed improved detection performance on all three scales of pests, significantly reducing the rate of missed detections. Our experimental results show that the SAW-YOLO model performs well in the detection of multiple pest classes in citrus orchards, helping to advance smart planting practices in the citrus industry. Full article
(This article belongs to the Special Issue AI, Sensors and Robotics for Smart Agriculture—2nd Edition)
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22 pages, 8608 KiB  
Article
Development and Validation of a Potato Seeding Machine with Integrated Plastic Film Mulch Punching Mechanism
by Baowei Li, Wei Sun, Zhiwei Zhao and Petru A. Simionescu
Agronomy 2024, 14(7), 1570; https://doi.org/10.3390/agronomy14071570 - 19 Jul 2024
Viewed by 233
Abstract
A seeding machine for planting potatoes in double rows on large ridges in the cold and arid regions of northwest China was designed and built at Gansu Agricultural University. The machine is capable to achieve the integrated operations of ridge formation, mulching, hole [...] Read more.
A seeding machine for planting potatoes in double rows on large ridges in the cold and arid regions of northwest China was designed and built at Gansu Agricultural University. The machine is capable to achieve the integrated operations of ridge formation, mulching, hole punching, and the precise covering of holes on the film. The key components were analyzed and designed, and the link lengths of the crank film-piercing and hole-punching mechanism were refined using MATLAB R2022a software. The structures and working parameters of the film-piercing and hole-punching mechanism, the dual-opening punching and seeding mechanism, the ridge-forming and soil-covering mechanism, and the seed-casting device were designed. The dynamics of the ridge-forming and soil-covering were simulated using the discrete element method to capture the effects of different machine parameters on the soil covering operation. Field tests showed that the full soil-covering rate of film holes, the qualified rate of hole spacing, the hole misalignment rate, the degree of damage to the light-receiving surface of the film, and the qualified rate of sowing depth under the film were 94.8%, 87.6%, 4.3%, 33.4%, and 95.6%, respectively. These indicators met the requirements of industry standards, and the test results met the design and actual operation requirements, enabling the integrated operations of ridge formation, mulching, hole punching, sowing on the film, and the accurate soil covering of the holes. Full article
(This article belongs to the Section Precision and Digital Agriculture)
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20 pages, 7360 KiB  
Article
Linking the Laboratory and the Field in Potato Early Dying Detection: From Spectral Signatures to Vegetation Indices Obtained with Multispectral Cameras Coupled to Drones
by William A. León-Rueda, Sandra Gómez-Caro, Luis A. Mendoza-Vargas, Camilo A. León-Sánchez and Joaquín G. Ramírez-Gil
Agronomy 2024, 14(7), 1569; https://doi.org/10.3390/agronomy14071569 - 19 Jul 2024
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Abstract
Potato production systems present various phytosanitary problems. Among these, potato early dying (PED) caused by Verticillium spp. is a disease that is difficult to detect in its early stages and whose expression occurs in critical growing phases of the crop, such as tuber [...] Read more.
Potato production systems present various phytosanitary problems. Among these, potato early dying (PED) caused by Verticillium spp. is a disease that is difficult to detect in its early stages and whose expression occurs in critical growing phases of the crop, such as tuber filling, generating a high economic impact. The objective of this work was to use spectral data to classify potato plants and identify the degree of severity of PED using spectral signatures and multispectral images captured on potato plants under greenhouse and commercial production conditions. Methods such as principal component analysis (PCA), random forest (RF), support vector machine (SVM), and artificial neural network (ANN) algorithms were implemented. All algorithms performed well; however, the RF was more accurate after iteration. The RF had a good capacity for indirect detection of PED, with an average accuracy of 60.9%. The wavelengths related to the red and red edges, especially from 710 to 735 nm, proved to be highly informative. As a result of the congruence between field and greenhouse data, the RECI, NDRE, VWI, and GRVI spectral indices were consistent with the discrimination of symptoms and PED severity levels. Identified wavelengths can be applied in the design of optical sensors that, together with the use of ML algorithms, can be implemented in the remote detection of early death in potato crops. Full article
(This article belongs to the Section Precision and Digital Agriculture)
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