Agronomy

21 pages, 2463 KB

Open AccessArticle

Potassium and Magnesium Balance the Effect of Nitrogen on the Yield and Quality of Sugar Beet

by Przemysław Barłóg and Witold Grzebisz

Agronomy 2025, 15(9), 2075; https://doi.org/10.3390/agronomy15092075 - 28 Aug 2025

The yield-enhancing effect of nitrogen (N) in sugar beets depends on the appropriate balance of other nutrients, including potassium (K) and magnesium (Mg). To determine the effects of these nutrients on beet yield (BY), quality parameters, white sugar yield (WSY), and nitrogen use [...] Read more.

The yield-enhancing effect of nitrogen (N) in sugar beets depends on the appropriate balance of other nutrients, including potassium (K) and magnesium (Mg). To determine the effects of these nutrients on beet yield (BY), quality parameters, white sugar yield (WSY), and nitrogen use efficiency (NUE) indices, a three-year field study was conducted in western Poland. Eight different fertilization treatments with potassium salt (PS), Korn-Kali (KK), and magnesium sulfate (Mg) were tested, K₀, K₁ (PS), K₂ (PS), K₂ (PS) + Mg, K₁ (KK), K₂ (KK), K₂(KK) + Mg, K₂ (KK) + Mg + FF, where 0, 1, and 2 are the K rates, respectively, for 0, 83, and 163 kg K ha⁻¹, and FF denotes foliar fertilization with magnesium sulfate. Potassium fertilization, both in the form of PS and KK, along with additional application of magnesium sulfate, positively affected BY and WSY. However, the response to fertilization depended strongly on seasonal factors, such as weather and soil conditions. Compared to the treatment without potassium (K₀), the average BY increased by 6.5–9.1%, and the WSY by 4.6–9.0%. Mineral fertilization had little effect on taproot quality parameters, including sucrose content. The exception was the concentration of α-amino-N, which significantly decreased with the application of K fertilizers. However, changes in α-amino-N content were not significantly related to WSY levels because this characteristic primarily depended on BY each year, and applying K and Mg to the soil improves NUE indices. Full article

(This article belongs to the Special Issue Fertilizer Innovation and Practice in Sustainable Intensified Agriculture)

24 pages, 4427 KB

Open AccessArticle

Three-Dimensional Convolutional Neural Networks (3D-CNN) in the Classification of Varieties and Quality Assessment of Soybean Seeds (Glycine max L. Merill)

by Piotr Rybacki, Kiril Bahcevandziev, Diego Jarquin, Ireneusz Kowalik, Andrzej Osuch, Ewa Osuch and Janetta Niemann

Agronomy 2025, 15(9), 2074; https://doi.org/10.3390/agronomy15092074 - 28 Aug 2025

Abstract

The precise identification, classification, sorting, and rapid and accurate quality assessment of soybean seeds are extremely important in terms of the continuity of agricultural production, varietal purity, seed processing, protein extraction, and food safety. Currently, commonly used methods for the identification and quality [...] Read more.

The precise identification, classification, sorting, and rapid and accurate quality assessment of soybean seeds are extremely important in terms of the continuity of agricultural production, varietal purity, seed processing, protein extraction, and food safety. Currently, commonly used methods for the identification and quality assessment of soybean seeds include morphological analysis, chemical analysis, protein electrophoresis, liquid chromatography, spectral analysis, and image analysis. The use of image analysis and artificial intelligence is the aim of the presented research, in which a method for the automatic classification of soybean varieties, the assessment of the degree of damage, and the identification of geometric features of soybean seeds based on numerical models obtained using a 3D scanner has been proposed. Unlike traditional two-dimensional images, which only represent height and width, 3D imaging adds a third dimension, allowing for a more realistic representation of the shape of the seeds. The research was conducted on soybean seeds with a moisture content of 13%, and the seeds were stored in a room with a temperature of 20–23 °C and air humidity of 60%. Individual soybean seeds were scanned to create 3D models, allowing for the measurement of their geometric parameters, assessment of texture, evaluation of damage, and identification of characteristic varietal features. The developed 3D-CNN network model comprised an architecture consisting of an input layer, three hidden layers, and one output layer with a single neuron. The aim of the conducted research is to design a new, three-dimensional 3D-CNN architecture, the main task of which is the classification of soybean seeds. For the purposes of network analysis and testing, 22 input criteria were defined, with a hierarchy of their importance. The training, testing, and validation database of the SB3D-NET network consisted of 3D models obtained as a result of scanning individual soybean seeds, 100 for each variety. The accuracy of the training process of the proposed SB3D-NET model for the qualitative classification of 3D models of soybean seeds, based on the adopted criteria, was 95.54%, and the accuracy of its validation was 90.74%. The relative loss value during the training process of the SB3D-NET model was 18.53%, and during its validation process, it was 37.76%. The proposed SB3D-NET neural network model for all twenty-two criteria achieves values of global error (GE) of prediction and classification of seeds at the level of 0.0992. Full article

(This article belongs to the Special Issue Intelligent Detection and Classification of External Traits in Crop Plants, Fruits, and Vegetables)

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18 pages, 10043 KB

Open AccessArticle

Driving Factors, Regional Differences and Mitigation Strategies for Greenhouse Gas Emissions from China’s Agriculture

by Shuo Zhou, Jianquan Wang, Dian Jin and Hailin Zhang

Agronomy 2025, 15(9), 2073; https://doi.org/10.3390/agronomy15092073 - 28 Aug 2025

Abstract

Global warming and climate deterioration are primarily driven by massive greenhouse gas emissions, making the comprehensive assessment of agricultural emissions imperative. This study integrates multiple datasets to achieve three objectives: (1) quantifying agricultural greenhouse gas emissions, (2) identifying regional influencing factors, and (3) [...] Read more.

Global warming and climate deterioration are primarily driven by massive greenhouse gas emissions, making the comprehensive assessment of agricultural emissions imperative. This study integrates multiple datasets to achieve three objectives: (1) quantifying agricultural greenhouse gas emissions, (2) identifying regional influencing factors, and (3) exploring mitigation strategies. In this study, a random forest regression model was used to fit the data, providing a new perspective for the analysis of emission factors. Key findings reveal fertilization and irrigation as the dominant emission drivers, with significant regional variations. Specifically, (1) fertilization practices, particularly nitrogen application, exert a greater influence than phosphorus on carbon emissions; (2) irrigation impacts correlate strongly with regional water usage patterns among staple crops; (3) distinct emission patterns emerge across China’s northeast–southwest divide, reflecting variations in grain crop impacts and climatic responses. The study proposes three mitigation approaches: precision fertilization, adaptive irrigation management, and crop structure optimization. These strategies provide actionable pathways for China to meet agricultural emission reduction targets while advancing sustainable development goals. Full article

(This article belongs to the Special Issue Assessment of Climate Change Effects on Food Security—Yield, Quality, and Diversity)

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25 pages, 2135 KB

Open AccessArticle

Monitoring Wolfberry (Lycium barbarum L.) Canopy Nitrogen Content with Hyperspectral Reflectance: Integrating Spectral Transformations and Multivariate Regression

by Yongmei Li, Hao Wang, Hongli Zhao, Ligen Zhang and Wenjing Xia

Agronomy 2025, 15(9), 2072; https://doi.org/10.3390/agronomy15092072 - 28 Aug 2025

Abstract

Accurate monitoring of canopy nitrogen content in wolfberry (Lycium barbarum L.) is essential for optimizing fertilization management, improving crop yield, and promoting sustainable agriculture. However, the sparse, architecturally complex canopy of this perennial shrub—featuring coexisting branches, leaves, flowers, and fruits across maturity [...] Read more.

Accurate monitoring of canopy nitrogen content in wolfberry (Lycium barbarum L.) is essential for optimizing fertilization management, improving crop yield, and promoting sustainable agriculture. However, the sparse, architecturally complex canopy of this perennial shrub—featuring coexisting branches, leaves, flowers, and fruits across maturity stages—poses significant challenges for canopy spectral-based nitrogen assessment. This study integrates methods across canopy spectral acquisition, transformation, feature spectral selection, and model construction, and specifically explores the potential of hyperspectral remote sensing, integrated with spectral mathematical transformations and machine learning algorithms, for predicting canopy nitrogen content in wolfberry. The overarching goal is to establish a feasible technical framework and predictive model for monitoring canopy nitrogen in wolfberry. In this study, canopy spectral measurements are systematically collected from densely overlapping leaf regions within the east, south, west, and north orientations of the wolfberry canopy. Spectral data undergo mathematical transformation using first-derivative (FD) and continuum-removal (CR) techniques. Optimal spectral variables are identified through correlation analysis combined with Recursive Feature Elimination (RFE). Subsequently, predictive models are constructed using five machine learning algorithms and three linear regression methods. Key results demonstrate that (1) FD and CR transformations enhance the correlation with nitrogen content (max correlation coefficient (r) = −0.577 and 0.522, respectively; p < 0.01), surpassing original spectra (OS, −0.411), while concurrently improving model predictive capability. Validation tests yield maximum R² values of 0.712 (FD) and 0.521 (CR) versus 0.407 for OS, confirming FD’s superior performance enhancement. (2) Nonlinear machine learning models, by capturing complex canopy-light interactions, outperform linear methods and exhibit superior predictive performance, achieving R² values ranging from 0.768 to 0.976 in the training set—significantly outperforming linear regression models (R² = 0.107–0.669). (3) The Random Forest (RF) model trained on FD-processed spectra achieves the highest accuracy, with R² values of 0.914 (training set) and 0.712 (validation set), along with an RPD of 1.772. This study demonstrates the efficacy of spectral transformations and nonlinear regression methods in enhancing nitrogen content estimation. It establishes the first effective field monitoring strategy and optimal predictive model for canopy nitrogen content in wolfberry. Full article

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

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14 pages, 1674 KB

Open AccessCommunication

Nutritional Value and Aerobic Stability of Safflower (Carthamus tinctorius L.) Silages Supplemented with Additives

by Jonathan Raúl Garay-Martínez, Fernando Lucio-Ruíz, Juan Eduardo Godina-Rodríguez, Xochilt Militza Ochoa-Espinoza, Santiago Joaquín-Cancino and José Felipe Orzuna-Orzuna

Agronomy 2025, 15(9), 2071; https://doi.org/10.3390/agronomy15092071 - 28 Aug 2025

Abstract

The objective of this study was to evaluate the effect of various additives on the nutritional value and aerobic stability of safflower (Carthamus tinctorius L.) silages. Silages were prepared from whole safflower plants harvested 102 days after planting, which were chopped to [...] Read more.

The objective of this study was to evaluate the effect of various additives on the nutritional value and aerobic stability of safflower (Carthamus tinctorius L.) silages. Silages were prepared from whole safflower plants harvested 102 days after planting, which were chopped to a particle size of 2.0 ± 0.5 cm and fermented for 120 days in polyvinyl chloride microsilos (6” × 46 cm), evaluating the following treatments: (1) safflower silage (SS) without additives, (2) SS supplemented with Guanacaste tree (Enterolobium cyclocarpum) pod meal, (3) SS supplemented with corn meal, (4) SS supplemented with sorghum meal, (5) SS supplemented with molasses, (6) SS supplemented with homofermentative inoculant, and (7) SS supplemented with fermentative inoculant + molasses. Compared with SS without additives, the addition of all the evaluated additives increased (p < 0.0001) the crude protein content and the relative forage value, while simultaneously decreasing the pH in SS. In contrast, the use of Guanacaste tree pod meal, corn, and sorghum decreased (p < 0.0001) the neutral detergent fiber and acid detergent fiber contents, while simultaneously increasing (p < 0.0001) the in vitro digestibility of dry matter in SS. All the evaluated additives increased (p < 0.05) the aerobic stability of the SS, which broke 42 h after opening the microsilos, whereas the silage without additives broke at 30 h. In conclusion, the use of Guanacaste tree pod meal, corn, and sorghum as additives improves the nutritive value and aerobic stability of safflower silage. Full article

(This article belongs to the Special Issue Innovative Solutions for Producing High-Quality Silage)

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19 pages, 1537 KB

Open AccessArticle

Diversity and Community Structure of Rhizosphere Arbuscular Mycorrhizal Fungi in Songnen Grassland Saline–Alkali-Tolerant Plants: Roles of Environmental Salinity and Plant Species Identity

by Linlin Mei, Yingbin Liu, Zixian Wang, Zixuan Xiong, Yuze Wang, Tianqi Jin and Xuechen Yang

Agronomy 2025, 15(9), 2070; https://doi.org/10.3390/agronomy15092070 - 28 Aug 2025

Abstract

The Songnen Grassland, a typical saline–alkali ecosystem in Northeast China, is increasingly degraded by soil salinization. Arbuscular mycorrhizal fungi (AMF) are critical for enhancing plant tolerance to saline–alkali stress via root symbiosis. To investigate the species diversity and community structure of AMF in [...] Read more.

The Songnen Grassland, a typical saline–alkali ecosystem in Northeast China, is increasingly degraded by soil salinization. Arbuscular mycorrhizal fungi (AMF) are critical for enhancing plant tolerance to saline–alkali stress via root symbiosis. To investigate the species diversity and community structure of AMF in the rhizosphere of salt-tolerant plants in the Songnen Grassland, this study combined morphological identification with high-throughput sequencing (based on virtual taxa, VTs, from the MaarjAM database) to analyze the composition and distribution characteristics of AMF in the rhizosphere of eight salt-tolerant plant species, including Arundinella anomala, Leymus chinensis, Taraxacum mongolicum and others. Morphological identification revealed a total of 22 AMF species belonging to 7 genera. Among these, the genus Glomus was the dominant genus, comprising eight species (accounting for 36.4% of the total species), followed by the genus Acaulospora (five species, 22.7%), the genus Rhizophagus (four species, 18.2%), the genus Ambispora (two species, 9.1%), and the remaining genera each represented by one species (4.5%). High-throughput sequencing analysis identified a total of 40 virtual taxa (VTs) with clear taxonomic assignments belonging to six genera. The genus Glomus accounted for the highest proportion (34 VTs, 85%) with a relative abundance of 89.33%, representing the overwhelmingly dominant group. Rhizosphere soil electrical conductivity (EC) of the eight plant species indicated a significant gradient (high EC group: A–D and G, 2.07–2.61 mS/cm; low EC group: E, F, H, 0.20–0.48 mS/cm). The AMF diversity in the high EC group was significantly higher than that in the low EC group, indicating that AMF in the rhizosphere of salt-tolerant plants enhanced plant tolerance to high-salt environments, and their diversity did not decrease with increasing salinity but instead remained at a high level. Plant-specific AMF community characteristics were evident. Hierarchical clustering analysis further confirmed that the AMF community composition in the rhizosphere of Taraxacum mongolicum and Vicia amoena differed significantly from that of the other plant species, indicating that plant species have a key driving role in AMF community structure. These findings provide critical insights into the plant–AMF symbiotic mechanisms underlying saline–alkali adaptation and offer a theoretical basis for selecting efficient AMF strains to support ecological restoration of saline–alkali lands. Full article

(This article belongs to the Section Agricultural Biosystem and Biological Engineering)

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33 pages, 8300 KB

Open AccessArticle

Farmland Navigation Line Extraction Method Based on RS-LineNet Network and Root Subordination Relationship Optimization

by Yanlei Xu, Zhen Lu, Jian Li, Yuting Zhai, Chao Liu, Xinyu Zhang and Yang Zhou

Agronomy 2025, 15(9), 2069; https://doi.org/10.3390/agronomy15092069 - 28 Aug 2025

Abstract

Navigation line extraction is vital for visual navigation with agricultural machinery. The current methods primarily utilize plant canopy detection frames to extract feature points for navigation line fitting. However, this approach is highly susceptible to environmental changes, causing position instability and reduced extraction [...] Read more.

Navigation line extraction is vital for visual navigation with agricultural machinery. The current methods primarily utilize plant canopy detection frames to extract feature points for navigation line fitting. However, this approach is highly susceptible to environmental changes, causing position instability and reduced extraction accuracy. To address this problem, this study aims to develop a robust navigation line extraction method that overcomes canopy-based feature instability. We propose extracting feature points from root detection frames for navigation line fitting. Compared to canopy points, root feature point positions remain more stable under natural interference and less prone to fluctuations. A dataset of corn crop row images under multiple growth environments was collected. Based on YOLOv8n (You Only Look Once version 8, nano model), we proposed the RS-LineNet lightweight model and introduced a root subordination relationship filtering algorithm to further improve detection precision. Compared with the YOLOv8n model, RS-LineNet achieves 4.2% higher precision, 16.2% improved recall, and an 11.8% increase in mean average precision (mAP₅₀), while reducing the model weight and parameters to 32% and 23% of the original. Navigation lines extracted under different environments exhibit an 0.8° average angular error, which is 3.1° lower than canopy-based methods. On Jetson TX2, the frame rate exceeds 12 FPS, meeting practical application requirements. Full article

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

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16 pages, 3362 KB

Open AccessArticle

Electrical Impedance Spectroscopy Reveals Physiological Acclimation in Apple Rootstocks During Recurrent Water Stress Episodes

by Juan Zhou, Shuaiyang Wu, Jianan Chen, Bo Sun, Bao Di, Guilin Shan and Ji Qian

Agronomy 2025, 15(9), 2068; https://doi.org/10.3390/agronomy15092068 - 27 Aug 2025

Abstract

Waterlogging and drought have become major challenges in many regions worldwide. Under water stress, plants exhibit a range of physiological and electrical responses, including changes measurable by electrical impedance spectroscopy (EIS). Monitoring these parameters can provide valuable insights into plant growth status under [...] Read more.

Waterlogging and drought have become major challenges in many regions worldwide. Under water stress, plants exhibit a range of physiological and electrical responses, including changes measurable by electrical impedance spectroscopy (EIS). Monitoring these parameters can provide valuable insights into plant growth status under adverse conditions. This study investigated changes in relative chlorophyll content (SPAD), maximum photochemical efficiency (Fv/Fm), relative water content (RWC), non-structural carbohydrates (NSC), and EIS parameters in apple rootstocks subjected to different water stress treatments. Results indicated that all physiological indicators, except NSC, showed a declining trend under two water stress episodes. Critically, the initial water stress episode elicited significantly greater physiological disruption than its subsequent counterpart. This suggests that plants developed a degree of physiological adaptation—such as osmotic adjustment and enhanced antioxidant activity—reducing their sensitivity to subsequent stress. Correlation analysis revealed that high-frequency resistivity (r) and intracellular resistivity (r_i) were strongly associated with key physiological parameters. Thus, r and r_i may serve as effective indicators for assessing plant water stress status. Furthermore, classification algorithms—Fuzzy K-Nearest Neighbors (FKNN) and sparse Linear Discriminant Analysis (sLDA)—were applied to distinguish water status in apple rootstocks, achieving high classification accuracy. These findings provide a theoretical basis for improved water management in apple cultivation. Full article

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

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15 pages, 2812 KB

Open AccessArticle

Optimizing the Light Intensity, Nutrient Solution, and Photoperiod for Speed Breeding of Alfalfa (Medicago sativa L.) Under Full-Spectrum LED Light

by Lingjuan Han, Yuanyuan Lv, Yifei Zhang, Xiaoyan Zhao, Peng Gao, Yinping Liang and Bin Li

Agronomy 2025, 15(9), 2067; https://doi.org/10.3390/agronomy15092067 - 27 Aug 2025

Abstract

Speed breeding technology has been used as a promising approach to accelerate plant breeding cycles and enhance agricultural productivity. However, systematic research on optimizing speed breeding conditions for alfalfa (Medicago sativa L.) in controlled plant factory environments remains limited. This study aimed [...] Read more.

Speed breeding technology has been used as a promising approach to accelerate plant breeding cycles and enhance agricultural productivity. However, systematic research on optimizing speed breeding conditions for alfalfa (Medicago sativa L.) in controlled plant factory environments remains limited. This study aimed to optimize light intensity, nutrient solution formulations, and photoperiod conditions for alfalfa speed breeding in plant factories equipped with full-spectrum LEDs, and to validate the applicability of these conditions across cultivars with different fall dormancy levels. Results demonstrated that a light intensity of 250 μmol·m⁻²·s⁻¹ significantly enhanced photosynthetic parameters, antioxidant enzyme activities, and biomass accumulation while minimizing malondialdehyde (MDA). The 75% concentration of the Japanese garden-test formula (JGTF) outperformed the Hoagland solution in promoting growth and photosynthetic pigment synthesis. An extended photoperiod (22 h/d) substantially accelerated growth and shortened flowering time. Under optimized conditions (250 μmol·m⁻²·s⁻¹ light intensity, 22 h/d photoperiod, and 75% Japanese Garden Test Formula), alfalfa cultivars reached initial flowering in approximately 37 days, regardless of fall dormancy level. This study establishes an effective speed breeding protocol for alfalfa, and the optimized conditions demonstrate broad applicability across cultivars with varying fall dormancy characteristics, providing a valuable foundation for accelerated alfalfa breeding programs and contributing to enhanced forage crop development efficiency. Full article

(This article belongs to the Special Issue Nutrient Cycle in Hydroponic Cultivation)

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19 pages, 15633 KB

Open AccessArticle

Comparative Analysis of Germination Traits and Gene Expression in Hybrid Progeny of Neo-Tetraploid Rice Under NaCl Stress Conditions

by Peishan Huang, Xinhui Xie, Xiaoyu Cai, Shihui Chen, Yutong Zheng, Zijuan Huang, Muhammad Qasim Shahid, Xiangdong Liu and Jinwen Wu

Agronomy 2025, 15(9), 2066; https://doi.org/10.3390/agronomy15092066 - 27 Aug 2025

Abstract

Neo-tetraploid rice is a highly fertile variety created from autotetraploid rice. It demonstrates stronger heterosis and produces stable hybrid progeny. However, there is insufficient data regarding abiotic stress in neo-tetraploid hybrid progeny, especially in relation to salt stress. Two hybrid progenies, high salt-resistance [...] Read more.

Neo-tetraploid rice is a highly fertile variety created from autotetraploid rice. It demonstrates stronger heterosis and produces stable hybrid progeny. However, there is insufficient data regarding abiotic stress in neo-tetraploid hybrid progeny, especially in relation to salt stress. Two hybrid progenies, high salt-resistance tetraploid rice hybrid progeny (HSRTH) and low salt-resistance tetraploid rice hybrid progeny (LSRTH), were generated by crossing the neo-tetraploid rice cultivars ‘Huaduo 3’ and ‘Huaduo 8’ with the autotetraploid rice Huanghuazhan-4x. Here, we assessed the germination characteristics and seedling growth of two neo-tetraploid hybrids at six NaCl concentrations: 0, 50, 100, 150, 200, and 250 mmol/L. HSRTH demonstrated a higher tolerance to salt stress, achieving a grain germination rate of 48.00 ± 2.63% compared to LSRTH, which reached only 5.00 ± 1.41% under a 250 mmol/L NaCl treatment. Cytological observations showed that the root tip differentiation zone and coleoptiles of HSRTH were less affected by NaCl stress treatment, resulting in fewer cortical cell abnormalities, decreased stele issues, and fewer rhizodermis cell problems, such as shrinkage. Gene expression analysis revealed nine genes that showed differential expression in HSRTH compared to LSRTH. Our study demonstrated that HSRTH showed strong salt stress tolerance, providing a basis for selecting salt-resistant rice germplasm and offering insights for developing salt-tolerant rice varieties using neo-tetraploid resources. Full article

(This article belongs to the Special Issue Innovative Research on Rice Breeding and Genetics)

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22 pages, 2895 KB

Open AccessArticle

Dynamic Degradation of Seed Ropes: Influence of Material Type and Adhesion to Different Soils

by Jiaoyang Duan, Xiang Liu and Baolong Wang

Agronomy 2025, 15(9), 2065; https://doi.org/10.3390/agronomy15092065 - 27 Aug 2025

Abstract

Seed rope direct seeding technology is a precision seeding method that can accurately mix and arrange multiple varieties based on specific grain spacing and quantity, making it suitable for precision breeding and variety comparison studies. As seed ropes serve as the crucial seed [...] Read more.

Seed rope direct seeding technology is a precision seeding method that can accurately mix and arrange multiple varieties based on specific grain spacing and quantity, making it suitable for precision breeding and variety comparison studies. As seed ropes serve as the crucial seed encapsulation material in seed rope direct seeding, this study employed a multi-faceted approach to investigate the dynamic degradation of nonwoven fabric and paper material seed ropes under diverse environmental conditions as well as their adhesion properties with Ultisols, Oxisols, and the Substrate in this seeding technique. Firstly, the degradation dynamics were systematically analyzed using image-based surface area detection, breaking force measurement, and organic carbon content analysis. Secondly, the process of seed rope laying was simulated by modeling the sliding friction and adhesion forces during the detachment of soil slurry. The laying motion was simulated considering both sliding friction (during the uniform-speed interaction between the seed rope and soil slurry) and adhesion (during upward detachment), providing crucial reference values for optimizing the rope-breaking mechanism in field applications. The study yielded several significant findings: In natural environments, Wood pulp paper seed rope degrades significantly faster than nonwoven fabric, with a degradation cycle of only 5.68 days in winter (approximately 34% of the degradation cycle of nonwoven fabric) and 4.70 days in summer (approximately 78% of the degradation cycle of nonwoven fabric). The main effect of seed viability on the degradation rate of seed tapes was not statistically significant. The degradation of Wood pulp paper seed rope was relatively predictable in indoor settings but exhibited notable fluctuations outdoors. The peak friction occurred at 35% soil moisture content, with values of 1.22 N for Wood pulp paper seed rope and 2.08 N for nonwoven fabric when interacting with Oxisols; nonwoven ropes demonstrated stronger adhesion than Wood pulp paper seed rope in the Substrate (at moisture contents of 25–30% and 40–45%) and Oxisols (at 35–45% moisture). In Ultisols, nonwoven fabric only showed superior adhesion compared to Wood pulp paper seed rope at 35–45% moisture, while Wood pulp paper seed rope exhibited better adhesion in other moisture ranges. Full article

(This article belongs to the Special Issue Effects of Efficient Crop Cultivation Techniques on Plant Nutrition and Physiology)

18 pages, 2538 KB

Open AccessArticle

Contrasting Roles of Archaeal Core Clusters in Soil Nitrification of Northeast China’s Black Soil Region

by Feng Wang, Lingzhi Liu, Weijun Zhang, Keren Wu, Bingqing Guo, Tingting An, Shuangyi Li, Xiaodan Gao and Jingkuan Wang

Agronomy 2025, 15(9), 2064; https://doi.org/10.3390/agronomy15092064 - 27 Aug 2025

Abstract

The black soil region of Northeast China is crucial for agricultural productivity. Ammonia-oxidizing archaea (AOA) are key indicators of soil nitrification in this region, yet it remains unclear whether this process is driven by the entire community or by specific clusters. Here, we [...] Read more.

The black soil region of Northeast China is crucial for agricultural productivity. Ammonia-oxidizing archaea (AOA) are key indicators of soil nitrification in this region, yet it remains unclear whether this process is driven by the entire community or by specific clusters. Here, we investigated the AOA community across a long-term fertilization Brown Soil Experimental Station and 15 sites in the Typical Black Soil Zone. Using Illumina MiSeq sequencing of the AOA amoA gene and cluster-specific primers, 14 OTUs were selected as core clusters based on relative abundance >0.1% and strong correlations (r > 0.7) with soil properties or PNR, and were further grouped into five distinct clusters according to phylogenetic analysis. Compared to the overall AOA community, core clusters responded more precisely to fertilization, straw addition, and spatial variation, with contrasting environmental responses reflected in their relationships with soil nitrification dynamics. Clusters G1 and G2 had positive correlations with soil PNR, while Clusters G4 and G5 had negative correlations. Moreover, AOA core clusters demonstrated stronger correlations with soil properties, including pH, C/N ratio, and NH₄⁺/NO₃⁻ ratio. These findings demonstrate that AOA core clusters are reliable microbial indicators of soil nitrification, and monitoring their abundance changes under nitrogen input can provide early insights into potential inhibition, informing predictive models and guiding more precise nitrogen management to support sustainable agricultural practices. Full article

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

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14 pages, 1210 KB

Open AccessArticle

Genetic Diversity Analysis of Phenotypic Traits in Jujube Germplasm Resources

by Yiqun Bai, Jingmei Xie, Taohong Tong, Xiaofeng Zhou, Ze Yuan, Yingxia Zhang, Xiangyu Li and Cuiyun Wu

Agronomy 2025, 15(9), 2063; https://doi.org/10.3390/agronomy15092063 - 27 Aug 2025

Abstract

To explore the phenotypic diversity of jujube germplasm resources and identify superior genotypes, this study systematically evaluated 150 jujube accessions. Multiple organ-related traits—including branches, thorns, bearing shoots, leaves, flowers, and fruits—were investigated. A comprehensive, multidimensional analysis was conducted to assess phenotypic variation and [...] Read more.

To explore the phenotypic diversity of jujube germplasm resources and identify superior genotypes, this study systematically evaluated 150 jujube accessions. Multiple organ-related traits—including branches, thorns, bearing shoots, leaves, flowers, and fruits—were investigated. A comprehensive, multidimensional analysis was conducted to assess phenotypic variation and diversity. The results provide valuable insights for germplasm conservation and the selection of elite jujube varieties. The results showed that the variation coefficient of 18 quantitative traits ranged from 5.07% to 21.43%; the variation coefficient of fruit quality traits ranged from 4.25% to 13.48%; and the results of the cluster analysis showed that the germplasm resources were classified into three categories according to the quantitative traits and four categories according to the fruit quality traits. Principal component analysis extracted six significant components for fruit quality traits, accounting for 86.88% of the total variance. Based on the comprehensive evaluation of factor analysis, Sanlengzao, Linyilajiaozao, Zan 2, Jinmanguo, and Jing 39 performed well and ranked high in the comprehensive ranking, which can be used as an important reference for the evaluation of jujube germplasm resources and the selection and breeding of good varieties. Full article

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

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23 pages, 7690 KB

Open AccessArticle

Attractiveness of Food Baits and Tea Volatile Components to Mirid Bug Apolygus lucorum in Tea Plantation

by Zhifei Jia, Binghai Gong, Yusheng Li, Yongyu Xu and Zhenzhen Chen

Agronomy 2025, 15(9), 2062; https://doi.org/10.3390/agronomy15092062 - 27 Aug 2025

Abstract

Apolygus lucorum is one of the main pests affecting tea quality. Chemical control is the primary method for managing this pest, but issues such as pesticide residues and the development of resistance are inevitable. The pest’s extensive host range holds significant practical implications [...] Read more.

Apolygus lucorum is one of the main pests affecting tea quality. Chemical control is the primary method for managing this pest, but issues such as pesticide residues and the development of resistance are inevitable. The pest’s extensive host range holds significant practical implications for developing novel food baits. This study first investigated the preference of adult A. lucorum for tea branches under different conditions and various host plants by using the Y-tube olfactometer. Subsequently, the trapping efficacy of active tea volatile components and food baits was tested. The results revealed that adult A. lucorum exhibited a stronger preference for healthy and mechanically damaged tea branches, while they avoided branches infested with high densities of conspecifics. Adult A. lucorum showed significantly higher selection rates for Gossypium hirsutum, Vigna radiata leaf, Glycine max leaf, Phaseolus vulgaris, Lablab purpureus, and Brassica pekinensis compared with healthy tea branches. In field trials, three tea volatile baits showed effective trapping performance, (E,E)-α-farnesene, nonanal, and (Z)-3-hexenol. Three mixture baits of foods and tea plant volatiles, B. pekinensis + (Z)-3-hexenol, P. vulgaris + (E,E)-α-farnesene, and S. melongena + (Z)-3-hexenol, not only demonstrated high attractiveness but also maintained a residual effect period as long as 20 days. This study provides new insights and approaches for the integrated management of A. lucorum and offers technical support for the development of novel green pest control technologies in tea plantations. Full article

(This article belongs to the Section Pest and Disease Management)

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15 pages, 4062 KB

Open AccessArticle

Dose-Dependent Effects of Paecilomyces variotii Extract on Drought Resistance in Pear Trees: Plant Growth, Soil Enzyme Activities, and Root Exudates

by Ziyang Guo, Yujing Wei, Wenjing Yin, Zhongchen Yang, Yawei Zhang, Yanhong Lou, Hong Pan, Quangang Yang, Guoqing Hu, Yuping Zhuge and Hui Wang

Agronomy 2025, 15(9), 2061; https://doi.org/10.3390/agronomy15092061 - 27 Aug 2025

Abstract

Constrained by site conditions and water resources, pear tree cultivation faces increasing drought stress. Paecilomyces variotii extract (PVE), a novel biostimulant extracted from wild sea buckthorn root-isolated strains and containing chitin, humic/fulvic acids, and beneficial microbes, has gained attention due to its high [...] Read more.

Constrained by site conditions and water resources, pear tree cultivation faces increasing drought stress. Paecilomyces variotii extract (PVE), a novel biostimulant extracted from wild sea buckthorn root-isolated strains and containing chitin, humic/fulvic acids, and beneficial microbes, has gained attention due to its high activity and efficacy in alleviating plant stresses (e.g., drought). In this study, Pyrus pyrifolia ‘Qiu Yue’ was used as the experimental material, and pot experiments were conducted to examine the drought-mitigating effects of different PVE concentrations. Drought stress was achieved by maintaining soil water content at 35–45% of water holding capacity for 45 days under natural evaporation conditions in rain shelters. The growth status of pear trees, soil enzyme activity, and metabolite levels were analyzed. The results showed that the application of 5 ng/mL PVE promoted pear tree growth, enhanced leaf antioxidant enzyme activity, and improved photosynthetic capacity and soil enzyme activity. Under normal water conditions, the shoot growth length, plant height, stem diameter, and root system activity of the 5 ng/mL PVE group were 31.91%, 12.05%, 3.54%, and 10.94% higher than those of the control group, respectively. Under drought stress, these values increased by 25.12%, 8.87%, 12.21%, and 16.98%, respectively. The addition of 5 ng/mL PVE facilitates trehalose release and upregulates starch-sucrose, glycerophospholipid, and galactose metabolic pathways, thereby potentiating drought stress tolerance in pear trees. However, at 20 ng/mL, reductions were observed in pear tree growth indicators, leaf antioxidant enzyme activity, soil enzyme activity, and trehalose content in root exudates compared to the 5 ng/mL PVE treatment. Overall, 5 ng/mL PVE effectively promotes pear tree growth and enhances drought resistance, making it suitable for broader use in pear cultivation practices. Full article

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

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21 pages, 6668 KB

Open AccessArticle

Identification and Analysis of Differentially Expressed Genes in Sugarcane Roots Under Different Potassium Application Levels

by Rudan Li, Zhongfu Zhang, Yanye Li, Yong Zhao, Jiayong Liu and Jun Deng

Agronomy 2025, 15(9), 2060; https://doi.org/10.3390/agronomy15092060 - 27 Aug 2025

Abstract

Potassium (K) is a critical macronutrient for sugarcane (Saccharum spp.), playing a vital role in metabolic processes, sucrose accumulation, and yield formation. Herein, this study systematically evaluated the effects of potassium oxide (K₂O) application on sugarcane (cultivar YZ1696) growth at [...] Read more.

Potassium (K) is a critical macronutrient for sugarcane (Saccharum spp.), playing a vital role in metabolic processes, sucrose accumulation, and yield formation. Herein, this study systematically evaluated the effects of potassium oxide (K₂O) application on sugarcane (cultivar YZ1696) growth at the seedling and tillering stages. Hydroponic experiments demonstrated that 6 mmol/L K₂O optimally promoted seedling growth, whereas field trials revealed that 150 kg/ha K₂O maximized growth rate, yield, and sucrose content. Sugarcane growth exhibited a biphasic response—stimulation followed by inhibition—with increasing K₂O dosage at both developmental stages. Transcriptomic profiling of sugarcane roots under low-potassium (K-deficient), optimal potassium, and high-potassium conditions identified 10,266 differentially expressed genes (DEGs), with the most pronounced transcriptional shifts occurring under K deficiency. Functional enrichment analysis identified DEGs associated with potassium transport, calcium signaling, and carbohydrate metabolism. Notably, potassium uptake was mediated by distinct mechanisms: Shaker family channels (AKT1, AKT2, SPIKE) and the TPK family member KCO1 were induced under optimal K supply, whereas HAK/KUP/KT transporters (HAK1/5/10/21/25) exhibited broad activation across K concentrations, underscoring their key role in K homeostasis. Furthermore, calcium signaling genes (e.g., CIPK23) displayed K-dependent expression patterns. Weighted gene co-expression network analysis identified key gene modules that correlated strongly with agronomic traits, including plant height, yield, and sucrose content. Optimal K conditions favored the expression of yield- and sucrose-associated genes, suggesting a molecular basis for K-mediated productivity enhancement. Our findings revealed the genetic and physiological mechanisms underlying K-dependent sugarcane improvement, providing actionable insights for precise potassium fertilization to maximize the yield and sugar content. Full article

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

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26 pages, 40392 KB

Open AccessArticle

Crop Health Assessment from Predicted AGB and NPK Derived from UAV Spectral Indices and Machine Learning Techniques

by Ayyappa Reddy Allu and Shashi Mesapam

Agronomy 2025, 15(9), 2059; https://doi.org/10.3390/agronomy15092059 - 27 Aug 2025

Abstract

Crop health assessment is essential for the early detection of nutrient deficiencies, diseases, and pests, allowing for timely interventions that optimize yield, reduce losses, and support sustainable agricultural practices. While traditional methods and satellite-based remote sensing offer broad scale monitoring, they often suffer [...] Read more.

Crop health assessment is essential for the early detection of nutrient deficiencies, diseases, and pests, allowing for timely interventions that optimize yield, reduce losses, and support sustainable agricultural practices. While traditional methods and satellite-based remote sensing offer broad scale monitoring, they often suffer from coarse spatial resolution, and insufficient precision at the plant level. These limitations hinder accurate and dynamic assessment of crop health, particularly for high-resolution applications such as nutrient diagnosis during different crop growth stages. This study addresses these gaps by leveraging high-resolution UAV (Unmanned Aerial Vehicle) imagery to monitor the health of paddy crops across multiple temporal stages. A novel methodology was implemented to assess the crop health condition from the predicted Above-Ground Biomass (AGB) and essential macro-nutrients (N, P, K) using vegetation indices derived from UAV imagery. Four machine learning models were used to predict these parameters based on field observed data, with Random Forest (RF) and XGBoost outperforming other algorithms, achieving high regression scores (AGB > 0.92, N > 0.96, P > 0.92, K > 0.97) and low prediction errors (AGB < 80 gm/m², N < 0.11%, P < 0.007%, K < 0.08%). A significant contribution of this study lies in the development of decision-making rules based on threshold values of AGB and specific nutrient critical, optimum, and toxic levels for the paddy crop. These rules were used to derive crop health maps from the predicted AGB and NPK values. The resulting spatial health maps, generated using RF and XGBoost models with high classification accuracy (Kappa coefficient > 0.64), visualize intra-field variability, allowing for site-specific interventions. This research contributes significantly to precision agriculture by offering a robust, plant-level monitoring approach that supports timely, site-specific nutrient management and enhances sustainable crop production practices. Full article

(This article belongs to the Topic Advances in Smart Agriculture with Remote Sensing as the Core and Its Applications in Crops Field)

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0 pages, 11901 KB

Open AccessArticle

Expression and Functional Analysis of the ABORTED MICROSPORES (AMS) Gene in Marigold (Tagetes erecta L.)

by Xuejing Ma, Jinhua Tian, Daocheng Tang, Qiuyue Liang and Nan Tang

Agronomy 2025, 15(9), 2058; https://doi.org/10.3390/agronomy15092058 - 26 Aug 2025

Abstract

Male sterility is an important trait in heterosis utilization and marigold (Tagetes erecta L.) breeding. Currently, most male-sterile lines used in production are derived from natural mutations. ABORTED MICROSPORES (AMS) is an important gene that regulates tapetum and microspore development. [...] Read more.

Male sterility is an important trait in heterosis utilization and marigold (Tagetes erecta L.) breeding. Currently, most male-sterile lines used in production are derived from natural mutations. ABORTED MICROSPORES (AMS) is an important gene that regulates tapetum and microspore development. Therefore, the effect of AMS on fertility was studied. TeAMS was located in the nucleus and exhibited self-activation activity. TeAMS was highly expressed in the flower buds of T. erecta. The expression of this gene in fertile plants was higher than that in sterile plants, and the expression level gradually increased with the development of flower buds. The expression level of TeAMS was highest in the flower buds with a diameter of 1.2 cm at the floret differentiation stage, while the expression level was extremely low in the flower buds with a diameter of 1.6 cm. The expression trend of TeAMS in sterile plants was opposite to that in fertile plants. At the inflorescence primordium differentiation stage, flower buds with a diameter of 0.2 cm had the highest expression level, and the stem tip had the lowest expression level. In tobacco (Nicotiana tabacum L.), overexpression of the TeAMS gene resulted in shortened floral tubes, increased thousand-seed weight, a reduced flowering period, and decreased flower numbers. The pollen viability of transgenic tobacco was significantly lower than that of the wild type, and the pollen grains were smaller and showed irregular shapes. The pollen wall was dry and shrunk. Some pollen germinal furrows were distorted, and a few were almost invisible. Silencing TeAMS resulted in a longer flowering period in tobacco, reduced thousand-seed weight, and high pollen viability. Pollen morphology in silenced lines showed no significant differences compared to the wild-type and empty vector controls. Only a few pollen grains were smaller, shriveled, and shrunken. Therefore, the TeAMS gene plays an important role in regulating the fertility of marigolds. This study provides a theoretical foundation for breeding marigold male-sterile lines. Full article

(This article belongs to the Special Issue Mechanism of Flower Growth in Ornamental Plants: From Floral Induction to Development)

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0 pages, 1255 KB

Open AccessArticle

Temperature Regimes Modulate Growth and Nutritional Quality of Three African Leaf Vegetables

by Omolara Rukayat Ibrahim, Fang He, Björn Thiele, Thorsten Kraska, Odunayo Clement Adebooye, Ulrich Schurr and Arnd Jürgen Kuhn

Agronomy 2025, 15(9), 2057; https://doi.org/10.3390/agronomy15092057 - 26 Aug 2025

Abstract

A large population in Africa, particularly West Africa, depends on leafy vegetables such as red amaranth (Amaranthus cruentus), Lagos spinach (Celosia argentea), and African eggplant (Solanum macrocarpon) as affordable and readily available sources of nutrition. These vegetables [...] Read more.

A large population in Africa, particularly West Africa, depends on leafy vegetables such as red amaranth (Amaranthus cruentus), Lagos spinach (Celosia argentea), and African eggplant (Solanum macrocarpon) as affordable and readily available sources of nutrition. These vegetables are rich sources of phenolics, minerals, vitamins, and bioactive compounds, contributing significantly to dietary nutrition and providing an important source of revenue for farmers. However, the temperature rise due to climate change threatens their availability and nutritional value. This study assessed the effects of temperature regimes (23, 30, and 40 °C) on the growth and quality of these vegetables under greenhouse conditions for 48 (A. cruentus and C. argentea) and 54 (S. macrocarpon) days after sowing by measuring biomass (leaf, stem, shoot, root dry weight, root/shoot and leaf area), photosynthetic parameters, pigments, sugars, mineral content, antioxidant activity, total phenolic compounds, total flavonoids, and free amino acids. Temperature significantly affected biomass, with A. cruentus and C. argentea showing declines of 13.5–32.2% and 5.1–27.8%, respectively, at 40 °C compared to 23 °C, indicating sensitivity to heat stress. Photosynthetic rates increased with a rise from 23 to 30 °C by 2.1–29.2% across all species. Sugar contents remained generally stable, except for notable decreases in glucose and soluble sugars by 43.3% and 40.5%, respectively, in C. argentea between 30 and 40 °C, and a 52.6% reduction in starch in S. macrocarpon from 23 to 40 °C. Mineral nutrient responses varied by species; however, they exhibited similar increases in nitrogen and phosphorus, as well as decreases in calcium and manganese, at higher temperatures. Notably, antioxidant capacity and total phenolic compounds declined significantly in C. argentea (8.1% and 8.0%) and S. macrocarpon (4.7% and 13.3%). In contrast, free amino acid contents increased by 35.2% and 28.8% in A. cruentus and S. macrocarpon, respectively. It was concluded that A. cruentus and C. argentea suffer reduced growth and nutrients at 40 °C, while S. macrocarpon maintains biomass but has some biochemical declines; antioxidant capacity and phenolics drop at high temperatures, free amino acids rise, and 30 °C is optimal for all three. Full article

(This article belongs to the Topic The Effect of Climate Change on Crops and Natural Ecosystems, 2nd Volume)

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