Agronomy

24 pages, 5129 KiB

Open AccessArticle

Multi-Source Indicator Modeling and Spatiotemporal Evolution of Spring Sowing Agricultural Risk Along the Great Wall Belt, China

by Guofang Wang, Juanling Wang, Mingjing Huang, Jiancheng Zhang, Xuefang Huang and Wuping Zhang

Agronomy 2025, 15(8), 1930; https://doi.org/10.3390/agronomy15081930 (registering DOI) - 10 Aug 2025

Abstract

The spatiotemporal heterogeneity of hydrothermal conditions during the spring sowing period profoundly shapes cropping layouts and sowing strategies. Using NASA’s GLDAS remote sensing reanalysis, we developed a continuous agricultural climate risk index that integrates three remotely driven indicators—spring sowing window days (SWDs) derived [...] Read more.

The spatiotemporal heterogeneity of hydrothermal conditions during the spring sowing period profoundly shapes cropping layouts and sowing strategies. Using NASA’s GLDAS remote sensing reanalysis, we developed a continuous agricultural climate risk index that integrates three remotely driven indicators—spring sowing window days (SWDs) derived from a “continuous suitable-day” logic, the hydrothermal coordination degree (D value), and a comprehensive suitability index (SSH_SI)—thus advancing risk assessment from single metrics to a multidimensional framework. Methodologically, dominant periodic structures of spring sowing hydrothermal risk were extracted via a combination of wavelet power spectra and the global wavelet spectrum (GWS), while spatial trend-surface fitting and three-dimensional directional analysis captured spatial non-stationarity. The index’s spatial migration trajectories and centroid-evolution paths were then quantified. Results reveal pronounced gradients along the Great Wall Belt: SWD displays a “central-high, terminal-low” pattern, with sowing windows restricted to only 3–6 days in northeastern Inner Mongolia and western Liaoning but extending to 11–13 days in the central plains of Inner Mongolia and Shanxi; SSH_SI and D values form an overall “south-west high, north-east low” pattern, indicating more favorable hydrothermal coordination in southwestern areas. Temporally, although SWD and SSH_SI show no significant downward trend, their interannual variability has increased, signaling rising instability, whereas the D value declines markedly in most regions, reflecting intensified hydrothermal imbalance. The integrated risk index identifies high-risk hotspots in eastern Inner Mongolia and northern North China, and low-risk zones in western provinces such as Gansu and Ningxia. Centroid-shift analysis further uncovers a dynamic regional adjustment in optimal sowing patterns, offering scientific evidence for addressing spring sowing climate risks. These findings provide a theoretical foundation and decision support for optimizing regional cropping structures, issuing climate risk warnings, and precisely regulating spring sowing schedules. Full article

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

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20 pages, 27551 KiB

Open AccessArticle

From Coconut Waste to Circular Plant Factories with Artificial Light: Renewable Substrate-Enhanced Crop Yield and Energy Efficiency

by Jun Ju, Yingjun Zhang, Yangyue Yu, Minggui Zhang, Youzhi Hu, Xiaojuan Liu, Xiaolong Yang, Jiali Song and Houcheng Liu

Agronomy 2025, 15(8), 1929; https://doi.org/10.3390/agronomy15081929 (registering DOI) - 10 Aug 2025

Abstract

Developing environmentally friendly and cost-effective substrates is critical to enhance resource efficiency and productivity in plant factories with artificial lighting (PFALs). This study employed a molded coconut coir substrate (coconut coir composited with polyurethane hydrophilic adhesive, MCCS) in PFALs to cultivate lettuce ( [...] Read more.

Developing environmentally friendly and cost-effective substrates is critical to enhance resource efficiency and productivity in plant factories with artificial lighting (PFALs). This study employed a molded coconut coir substrate (coconut coir composited with polyurethane hydrophilic adhesive, MCCS) in PFALs to cultivate lettuce (Lactuca sativa L.) and pak choi (Brassica rapa ssp. chinensis). During the transplanting stage, the roots exposed outside the MCCS of lettuce and pak choi were 13.40% and 19.92% shorter, respectively, than in the sponge treatment, and more amenable to mechanical transplanting. This compensated for the neglect of operational efficiency in traditional lifecycle assessment (LCA). Furthermore, compared with sponge and rockwool, MCCS significantly enhanced the yield of lettuce and pak choi by up to 27.33% and 67.19%, respectively. Meanwhile, MCCS significantly increased the chlorophyll content of lettuce compared to sponge by 8.56%. Compared with rockwool, MCCS significantly increased the chlorophyll b content (7.36%), antioxidant content, and antioxidant activity (total phenolics by 13.59%, total flavonoid by 18.43%, FRAP by 12.96%, and DPPH by 19.87%) of lettuce. For pak choi, MCCS increased the soluble protein content in the blade and total phenolics content in the petiole by 32.01% and 14.76%, respectively. More importantly, the use of MCCS led to a significant reduction in the energy consumption per unit area yield of lettuce and pak choi, with maximum reductions of 22.98% and 40.91%, respectively. This eco-friendly substrate is suitable for replacing sponge and rockwool in the production of lettuce and pak choi in PFALs. Full article

(This article belongs to the Special Issue Advanced Hydroponics Technology for Vegetable Production: New Opportunities and Challenges)

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31 pages, 2141 KiB

Open AccessReview

Climate, Soil, and Microbes: Interactions Shaping Organic Matter Decomposition in Croplands

by Muhammad Tahir Khan, Skaidrė Supronienė, Renata Žvirdauskienė and Jūratė Aleinikovienė

Agronomy 2025, 15(8), 1928; https://doi.org/10.3390/agronomy15081928 (registering DOI) - 10 Aug 2025

Abstract

Soil organic matter (SOM) decomposition is a critical biogeochemical process that regulates the carbon cycle, nutrient availability, and agricultural sustainability of cropland systems. Recent progress in multi-omics and microbial network analyses has provided us with a better understanding of the decomposition process at [...] Read more.

Soil organic matter (SOM) decomposition is a critical biogeochemical process that regulates the carbon cycle, nutrient availability, and agricultural sustainability of cropland systems. Recent progress in multi-omics and microbial network analyses has provided us with a better understanding of the decomposition process at different spatial and temporal scales. Climate factors, such as temperature and seasonal variations in moisture, play a critical role in microbial activity and enzyme kinetics, and their impacts are mediated by soil physical and chemical properties. Soil mineralogy, texture, and structure create different soil microenvironments, affecting the connectivity of microbial habitats, substrate availability, and protective mechanisms of organic matter. Moreover, different microbial groups (bacteria, fungi, and archaea) contribute differently to the decomposition of plant residues and SOM. Recent findings suggest the paramount importance of living microbial communities as well as necromass in forming soil organic carbon pools. Microbial functional traits such as carbon use efficiency, dormancy, and stress tolerance are essential drivers of decomposition in the soil. Furthermore, the role of microbial necromass, alongside live microbial communities, in the formation and stabilization of persistent SOM fractions is increasingly recognized. Based on this microbial perspective, feedback between local microbial processes and landscape-scale carbon dynamics illustrates the cross-scale interactions that drive agricultural productivity and regulate soil climate. Understanding these dynamics also highlights the potential for incorporating microbial functioning into sustainable agricultural management, which offers promising avenues for increasing carbon sequestration without jeopardizing soil nutrient cycling. This review explores current developments in intricate relationships between climate, soil characteristics, and microbial communities determining SOM decomposition, serving as a promising resource in organic fertilization and regenerative agriculture. Specifically, we examine how nutrient availability, pH, and oxygen levels critically influence these microbial contributions to SOM stability and turnover. Full article

(This article belongs to the Section Farming Sustainability)

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22 pages, 3303 KiB

Open AccessArticle

Improving Groundcover Establishment Through Seed Rate, Seed Ratio, and Hydrophilic Seed Coating

by Jack Moran, A. Susana Goggi, Ken J. Moore, Shui-zhang Fei and Shelby Gruss

Agronomy 2025, 15(8), 1927; https://doi.org/10.3390/agronomy15081927 (registering DOI) - 10 Aug 2025

Abstract

Kentucky bluegrass (KBG) is well-suited as a perennial groundcover in corn production due to its vigorous growth during the fall and spring and its natural dormancy during the summer, aligning with the corn growing season. However, seeds of KBG germinate slowly, potentially resulting [...] Read more.

Kentucky bluegrass (KBG) is well-suited as a perennial groundcover in corn production due to its vigorous growth during the fall and spring and its natural dormancy during the summer, aligning with the corn growing season. However, seeds of KBG germinate slowly, potentially resulting in poor stand establishment in the Midwest, USA. This study was conducted to assess the effect of the seeding rate, the seed ratio in a perennial ryegrass/KBG mixture (PRG:KBG), and seed treatment on KBG percentage groundcover, green rating, the red/far-red ratio, soil temperature, soil moisture, and summer biomass. The split-plot design consisted of KBG seeds treated with the Hydroloc^TM hydrophilic polymer and untreated seeds with seeding rates and ratios in a randomized design. Hydroloc™ seed treatment showed a significant difference in the fall percentage of groundcover but did not affect the spring groundcover. The seed ratio had a significant effect on the fall and spring groundcover, with a ratio of 1:1 (PRG:KBG) performing best, followed by 1:3, 1:5, and 0:1. The seeding rate was also significant, with 44.8 kg ha⁻¹ having the highest groundcover, followed by 22.4 kg ha⁻¹ and 11.2 kg ha⁻¹. The red/far-red readings, which reflect plant density, gave corresponding results to the percentage of groundcover. The Hydroloc™ hydrophilic polymer increases the groundcover percentage by improving KBG establishment. These results are important for farmers and seed companies interested in using KBG as a perennial groundcover in corn production systems. We recommend a seed ratio of 1:1 (PRG:KBG) and a seeding rate of 22.4 kg ha⁻¹ to provide a dense and rapid-establishing groundcover that is also financially viable for the farmer. Full article

(This article belongs to the Section Innovative Cropping Systems)

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32 pages, 3566 KiB

Open AccessReview

Research Progress and Development Trend of Visual Detection Methods for Selective Fruit Harvesting Robots

by Wenbo Wang, Chenshuo Li, Yidan Xi, Jinan Gu, Xinzhou Zhang, Man Zhou and Yuchun Peng

Agronomy 2025, 15(8), 1926; https://doi.org/10.3390/agronomy15081926 (registering DOI) - 10 Aug 2025

Abstract

The rapid development of artificial intelligence technologies has promoted the emergence of Agriculture 4.0, where the machines participating in agricultural activities are made smart with the capacities of self-sensing, self-decision-making, and self-execution. As representative implementations of Agriculture 4.0, intelligent selective fruit harvesting robots [...] Read more.

The rapid development of artificial intelligence technologies has promoted the emergence of Agriculture 4.0, where the machines participating in agricultural activities are made smart with the capacities of self-sensing, self-decision-making, and self-execution. As representative implementations of Agriculture 4.0, intelligent selective fruit harvesting robots demonstrate significant potential to alleviate labor-intensive demands in modern agriculture, where visual detection serves as the foundational component. However, the accurate detection of fruits remains a challenging issue due to the complex and unstructured nature of fruit orchards. This paper comprehensively reviews the recent progress in visual detection methods for selective fruit harvesting robots, covering cameras, traditional detection based on handcrafted feature methods, detection based on deep learning methods, and tree branch detection methods. Furthermore, the potential challenges and future trends of the visual detection system of selective fruit harvesting robots are critically discussed, facilitating a thorough comprehension of contemporary progress in this research area. The primary objective of this work is to highlight the pivotal role of visual perception in intelligent fruit harvesting robots. Full article

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

19 pages, 9835 KiB

Open AccessArticle

Genome-Wide Identification, Molecular Evolution, and Abiotic Stress-Responsive Regulation of Cupin Superfamily Genes in Rice (Oryza sativa L.)

by Hongwei Chen, Mingze Xiao, Wenqi Shang, Xianju Wang, Hong Gao, Wenjing Zheng and Zuobin Ma

Agronomy 2025, 15(8), 1925; https://doi.org/10.3390/agronomy15081925 (registering DOI) - 9 Aug 2025

Abstract

The Cupin superfamily, characterized by a conserved β-barrel structure, plays crucial roles in plant growth, development, and stress responses. However, comprehensive analyses of this gene family in rice remains limited. Here, we performed a genome-wide identification, molecular evolution, and expression analysis of Cupin [...] Read more.

The Cupin superfamily, characterized by a conserved β-barrel structure, plays crucial roles in plant growth, development, and stress responses. However, comprehensive analyses of this gene family in rice remains limited. Here, we performed a genome-wide identification, molecular evolution, and expression analysis of Cupin genes in rice under abiotic stress. Utilizing the telomere-to-telomere (T2T) genome of rice, 54 Cupin genes (OsCupins) were identified and classified into four subfamilies (GLP, PIRIN, TRR14, and ARD) based on phylogenetic relationships with Arabidopsis homologs. These genes were unevenly distributed across ten chromosomes, with tandem and segmental duplications driving their expansion. Structural and synteny analyses revealed conserved motifs and orthologous relationships with sorghum and Arabidopsis. The promoter regions of OsCupins were enriched in stress-responsive cis-elements, including ABRE, MYB, and MYC motifs. qRT-PCR data demonstrated the significant upregulation of multiple OsCupins (e.g., OsGLP15, OsGLP38, and OsGLP43) under NaCl and PEG 6000 treatments. Functional validation in yeast showed that the overexpression of OsGLP15, OsGLP38, or OsGLP43 enhanced salt and drought tolerance in yeast, with OsGLP43 exhibiting the strongest stress resilience. Our findings provide insights into the evolutionary dynamics and stress-responsive regulatory mechanisms of the Cupin superfamily in rice, offering potential targets for enhancing abiotic stress tolerance in this critical crop. Full article

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

20 pages, 19465 KiB

Open AccessArticle

Enhanced Visual Detection and Path Planning for Robotic Arms Using Yolov10n-SSE and Hybrid Algorithms

by Hongjun Wang, Anbang Zhao, Yongqi Zhong, Gengming Zhang, Fengyun Wu and Xiangjun Zou

Agronomy 2025, 15(8), 1924; https://doi.org/10.3390/agronomy15081924 (registering DOI) - 9 Aug 2025

Abstract

Pineapple harvesting in natural orchard environments faces challenges such as high occlusion rates caused by foliage and the need for complex spatial planning to guide robotic arm movement in cluttered terrains. This study proposes an innovative visual detection model, Yolov10n-SSE, which integrates split [...] Read more.

Pineapple harvesting in natural orchard environments faces challenges such as high occlusion rates caused by foliage and the need for complex spatial planning to guide robotic arm movement in cluttered terrains. This study proposes an innovative visual detection model, Yolov10n-SSE, which integrates split convolution (SPConv), squeeze-and-excitation (SE) attention, and efficient multi-scale attention (EMA) modules. These improvements enhance detection accuracy while reducing computational complexity. The proposed model achieves notable performance gains in precision (93.8%), recall (84.9%), and mAP (91.8%). Additionally, a dimensionality-reduction strategy transforms 3D path planning into a more efficient 2D image-space task using point clouds from a depth camera. Combining the artificial potential field (APF) method with an improved RRT* algorithm mitigates randomness, ensures obstacle avoidance, and reduces computation time. Experimental validation demonstrates the superior stability of this approach and its generation of collision-free paths, while robotic arm simulation in ROS confirms real-world feasibility. This integrated approach to detection and path planning provides a scalable technical solution for automated pineapple harvesting, addressing key bottlenecks in agricultural robotics and fostering advancements in fruit-picking automation. Full article

(This article belongs to the Special Issue Facility Agriculture Robots and Autonomous Unmanned Management for Crops)

15 pages, 1816 KiB

Open AccessArticle

Biological Enzymatic Hydrolysis—Single Screw Co-Extrusion Treatment to Improve the Mechanical Properties of Biodegradable Straw Fiber Mulching Films

by Tao Jiang, Xing Wang, Haoyuan Yang, Chuang Gao, Mende Hongyang, Xinhang Xu, Shubai Cong, Yuanjun Sun, Tianzheng Pei, Bin Wang, Shuang Liu, Yu Wang, Rui Li, Haitao Chen and Longhai Li

Agronomy 2025, 15(8), 1923; https://doi.org/10.3390/agronomy15081923 (registering DOI) - 9 Aug 2025

Abstract

Biodegradable agricultural films manufactured with straw serve as a viable substitute for plastic films, effectively addressing the issue of white pollution. However, existing biodegradable straw fiber films exhibit insufficient mechanical properties, primarily characterized by their susceptibility to fracture damage. To address this issue, [...] Read more.

Biodegradable agricultural films manufactured with straw serve as a viable substitute for plastic films, effectively addressing the issue of white pollution. However, existing biodegradable straw fiber films exhibit insufficient mechanical properties, primarily characterized by their susceptibility to fracture damage. To address this issue, a novel method for the preparation of film raw materials was proposed, which employs the synergistic treatment of bioenzymes and a single screw extruder, with the aim of enhancing the mechanical properties of the film. The method begins with the application of microbial agents to pretreat the straw, for improving its fiber morphology and inducing beneficial physicochemical structural changes. Subsequently, single screw extrusion technology is employed to further enhance the quality of the straw fibers and the mechanical performance of the film. The bio-mechanical pulp produced with this method demonstrated an increase in the crystallinity index (CrI) from 50.33% to 60.78%, while the degree of polymerization (DP) decreased from 866.51 to 749.60. Furthermore, the tensile strength, tear strength, and burst strength of the fiber covering film increased by 35.74%, 16.22%, and 11.65%, respectively, which meet the mechanical durability requirements for farmland mulching. This research effectively mitigates agricultural white pollution by converting agricultural waste straw into biodegradable mulch film, which promotes the recycling of straw resources. This study presents a novel method with significant potential application value for the production of bio-pulping in the paper industry. Full article

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

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15 pages, 3935 KiB

Open AccessArticle

Spatiotemporal Evolution of Soil Quality Under Long-Term Apple Cultivation in the Taihang Mountains, China

by Yang Liu, Xingrui Zhang, Zhuo Li, Xiaoyi Liang, Meidan Chi and Feng Ge

Agronomy 2025, 15(8), 1922; https://doi.org/10.3390/agronomy15081922 (registering DOI) - 9 Aug 2025

Abstract

The present study aims to investigate the impact of long-term apple production and orchard management practices on soil quality in gneiss mountainous regions. The microbial community (as measured by phospholipid fatty acid analysis) and soil physicochemical properties (bulk density, organic matter, nitrogen, phosphorus, [...] Read more.

The present study aims to investigate the impact of long-term apple production and orchard management practices on soil quality in gneiss mountainous regions. The microbial community (as measured by phospholipid fatty acid analysis) and soil physicochemical properties (bulk density, organic matter, nitrogen, phosphorus, and potassium) were determined in soil samples collected from apple plantations of various ages (0-, 8-, 22-, 29-, and 36-year) in Gangdi Village, Xingtai, China. The soil samples were collected from depths of 0–20, 20–40, and 40–60 cm. The findings of the present study demonstrate that with increasing duration of apple cultivation, the soil bulk density and porosity decreased and increased, respectively. Initially, the content of soil nutrients such as organic matter, nitrogen, and phosphorus increased, eventually stabilizing, accompanied by a decline in pH. The soil microbial biomass significantly increased, accompanied by discernible alterations in the composition of the microbial community. Organic matter was found to be the primary factor influencing the structure and diversity of microbial communities. It is evident from forward analysis that the soil Gram-negative and actinomycete communities were predominantly influenced by soil pH, bulk density, and total phosphorus. In contrast, the Gram-positive and eukaryote communities were less affected by soil environmental factors. Notably, the soil bacterial community presented a greater degree of sensitivity to the duration of apple cultivation than did the fungal community. A marked vertical difference in the soil quality indicators was evident, with the increase in surface soil quality exceeding that of deeper soil depths. Full article

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

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24 pages, 10014 KiB

Open AccessArticle

A Simplified Model for Substrate-Cultivated Pepper in a Hexi Corridor Greenhouse

by Ning Ma, Jianming Xie, Xiaodan Zhang, Jing Zhang and Youlin Chang

Agronomy 2025, 15(8), 1921; https://doi.org/10.3390/agronomy15081921 (registering DOI) - 8 Aug 2025

Abstract

The aim of this study was to investigate the method of estimating actual crop evapotranspiration (ET_c_act) in a greenhouse using other measured meteorological parameters when solar radiation (R_s) data are missing. The study estimated ET_c [...] Read more.

The aim of this study was to investigate the method of estimating actual crop evapotranspiration (ET_c_act) in a greenhouse using other measured meteorological parameters when solar radiation (R_s) data are missing. The study estimated ET_c_act of greenhouse green peppers by combining solar radiation estimation models with the Penman–Monteith (PM) model and evaluated model performance. The results showed that the prediction accuracy of the temperature-based solar radiation model was higher than the model based on sunshine hours in the Hexi Corridor region. The effect of the insulation cover on the incident solar radiation in the greenhouse is modeled by introducing a ramp function. In terms of crop coefficients (K_cb), the initial K_cb value of green peppers in the 2023 growing season was generally consistent with the updated FAO-56 standard values, whereas the initial K_cb values (0.17) were higher than the standard values in the 2023–2024 growing season. During the two growing seasons, the mid-stage K_cb values were 1.01 in the 2023 growing season and 0.82 in the 2023–2024 growing season. The study also found that PM–RT4, PM–RT5, and PM–RT6 models were all able to accurately predict the ET_c_act of greenhouse green peppers during the 2023 growing season. The PM–RT4 model performed well in both growing seasons, with R² = 0.8101 in the 2023 growing season and R² = 0.7561 in the 2023–2024 growing season. Our research supports the PM–RT4 model as appropriate to estimate green pepper actual evapotranspiration in Gobi solar greenhouses (GSGs) and may be further used to improve irrigation scheduling for green peppers grown in GSGs. Full article

(This article belongs to the Section Water Use and Irrigation)

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24 pages, 849 KiB

Open AccessReview

Recent Advances in the Remediation of Degraded and Contaminated Soils: A Review of Sustainable and Applied Strategies

by Viorica Ghisman, Alina Crina Muresan, Nicoleta Lucica Bogatu, Elena Emanuela Herbei and Daniela Laura Buruiana

Agronomy 2025, 15(8), 1920; https://doi.org/10.3390/agronomy15081920 (registering DOI) - 8 Aug 2025

Abstract

This review explores the pressing issue of soil degradation and contamination, highlighting their adverse environmental effects and the necessity for sustainable solutions. Soil degradation disrupts ecosystems and accelerates climate change, while soil contamination poses serious health risks to humans and wildlife. Recent advances [...] Read more.

This review explores the pressing issue of soil degradation and contamination, highlighting their adverse environmental effects and the necessity for sustainable solutions. Soil degradation disrupts ecosystems and accelerates climate change, while soil contamination poses serious health risks to humans and wildlife. Recent advances in mitigation strategies demonstrate promising solutions, focusing on both degradation and contamination. This paper presents innovative methods, including the utilization of a dolomite–sewage sludge mixture to combat soil degradation effectively, enhancing soil fertility and supporting ecosystem restoration. Additionally, it introduces a novel approach using a dolomite–stainless steel slag mixture for petroleum hydrocarbon absorption, showcasing its efficacy in remediating contaminated sites. The results indicate significant improvements in soil health and a reduction in environmental pollutants, underscoring the potential of these mixtures to revolutionize soil management practices. Implementing such strategies not only mitigates degradation and contamination but also contributes to the sustainability of agricultural and natural ecosystems. This article aims to provide a comprehensive overview of these advancements, offering insights for researchers, policymakers, and environmental practitioners striving to foster a healthier and more sustainable environment. Full article

(This article belongs to the Section Agroecology Innovation: Achieving System Resilience)

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16 pages, 1952 KiB

Open AccessArticle

Unraveling the NRAMP Gene Family: Aegilops tauschii’s Prominent Barrier Against Metal Stress

by Hongying Li, Yibo Li, Fuqiang Yang, Xiaolin Liang, Yifan Ding, Ning Wang and Xiaojiao Han

Agronomy 2025, 15(8), 1919; https://doi.org/10.3390/agronomy15081919 - 8 Aug 2025

Abstract

The natural resistance-associated macrophage proteins (NRAMPs) gene family represents a group of membrane transporter proteins with wide distribution in plants. This family of membrane transporters plays a pivotal role in mediating plant responses to metal stress by coordinating ion transport processes [...] Read more.

The natural resistance-associated macrophage proteins (NRAMPs) gene family represents a group of membrane transporter proteins with wide distribution in plants. This family of membrane transporters plays a pivotal role in mediating plant responses to metal stress by coordinating ion transport processes and maintaining cellular metal homeostasis, thereby effectively mitigating the detrimental effects of metal ion stress on plant growth and development. This study conducted a comprehensive genome-wide analysis of the NRAMP gene family in A. tauschii using integrated bioinformatics approaches, as well as the expression pattern when exposed to heavy metal-induced stress. By means of phylogenetic investigation, eleven AetNRAMP proteins were categorized into five distinct subgroups. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis revealed that the majority of NRAMP genes exhibited marked differential expression patterns under specific stress treatments. Subsequently, yeast cells were employed to validate the functions of AetNRAMP1 and AetNRAMP3. It was confirmed that AetNRAMP1 functioned in copper transport, and AetNRAMP3 showed an increase in its expression level under manganese stress. These findings establish a molecular foundation for elucidating the functional specialization of NRAMP gene family members in A. tauschii’s heavy metal detoxification pathways, providing critical genetic evidence for their stress-responsive regulatory networks. Nevertheless, significant knowledge gaps persist regarding its functions in A. tauschii. Research on metal stress resistance in this wheat progenitor species may establish a theoretical foundation for enhancing wheat tolerance and developing improved cultivars. Full article

(This article belongs to the Special Issue Physiological and Molecular Mechanisms of Plant Under the Abiotic Stress)

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33 pages, 5299 KiB

Open AccessReview

The Effect of Polyploidisation on the Physiological Parameters, Biochemical Profile, and Tolerance to Abiotic and Biotic Stresses of Plants

by Marta Koziara-Ciupa and Anna Trojak-Goluch

Agronomy 2025, 15(8), 1918; https://doi.org/10.3390/agronomy15081918 - 8 Aug 2025

Abstract

Polyploidisation is a very common phenomenon in the plant kingdom and plays a key role in plant evolution and breeding. It promotes speciation and the extension of biodiversity. It is estimated that approximately 47% of flowering plant species are polyploids, derived from two [...] Read more.

Polyploidisation is a very common phenomenon in the plant kingdom and plays a key role in plant evolution and breeding. It promotes speciation and the extension of biodiversity. It is estimated that approximately 47% of flowering plant species are polyploids, derived from two or more diploid ancestral species. In natural populations, the predominant methods of whole-genome multiplication are somatic cell polyploidisation, meiotic cell polyploidisation, or endoreduplication. The formation and maintenance of polyploidy is accompanied by a series of epigenetic and gene expression changes, leading to alterations in the structural, physiological, and biochemical characteristics of polyploids relative to diploids. This article provides information on the mechanisms of formation of natural and synthetic polyploids. It presents a number of examples of the effects of polyploidisation on the composition and content of secondary metabolites of polyploids, providing evidence of the importance of the phenomenon in plant adaptation to the environment, improvement of wild species, and crops. It aims to gather and systematise knowledge on the effects of polyploidisation on plant physiological traits, including stomatal conductance (Gs), transpiration rate (Tr), light saturation point (LSP), as well as the most important photosynthetic parameters determining biomass accumulation. The text also presents the latest findings on the adaptation of polyploids to biotic and abiotic stresses and explains the basic mechanisms of epigenetic changes determining resistance to selected stress factors. Full article

(This article belongs to the Special Issue Stress Responses and Resistance Mechanisms in Plants: Physiology, Genetics, and Molecular Pathways)

23 pages, 1466 KiB

Open AccessArticle

Design and Optimization Experiment of a Cam-Swing Link Precision Metering Device for Peanut Based on Simulation

by Jinling Cong, Jiaming Wang, Yunlong Xie, Kaiqi Ouyang, Shisen Wu, Kun Cao and Lei Wang

Agronomy 2025, 15(8), 1917; https://doi.org/10.3390/agronomy15081917 - 8 Aug 2025

Abstract

To address the problem of unstable seed filling and low seeding accuracy caused by poor seed flow in conventional peanut seed metering devices, a novel precision metering device based on a cam-swing link was developed. Using EDEM simulations, the capacity of different type [...] Read more.

To address the problem of unstable seed filling and low seeding accuracy caused by poor seed flow in conventional peanut seed metering devices, a novel precision metering device based on a cam-swing link was developed. Using EDEM simulations, the capacity of different type hole installation positions to induce seed cluster disturbance was analyzed. A single-factor test and MBD–DEM coupled simulation were conducted to analyze the seeding performance. The simulation results indicate that when the type hole protrusion height was set to half the thickness of the seeding disc, seed cluster kinetic energy remained relatively stable, enhancing the capability to disturb seeds. As the seeding disc rotational speed increased from 10 to 40 rpm, the qualified index initially increased and then declined. Increasing the cluster wrap angle from 20° to 70° similarly led to a peak in the qualified index and a steady decrease in the missed index. Using the JPS-12 computer vision-based test platform, a second-order rotary orthogonal design was applied to evaluate the seeding performance. The experimental results show that when the seeding disc rotational speed was set at 26 rpm and the seed cluster wrap angle at 46°, the qualified index reached 89.95%, and the missed index was 4.04%. The average plant spacing of peanuts in field experiments was 137.82 mm. These results meet the operational requirements for precision peanut planting. Full article

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

17 pages, 4734 KiB

Open AccessArticle

Identification of Key Waterlogging-Tolerance Genes in Cultivated and Wild Soybeans via Integrated QTL–Transcriptome Analysis

by Yiran Sun, Lin Chen, Yuxin Jin, Shukun Wang, Shengnan Ma, Lin Yu, Chunshuang Tang, Yuying Ye, Mingxuan Li, Wenhui Zhou, Enshuang Chen, Xinru Kong, Jinbo Fu, Jinhui Wang, Qingshan Chen and Mingliang Yang

Agronomy 2025, 15(8), 1916; https://doi.org/10.3390/agronomy15081916 - 8 Aug 2025

Abstract

Soybean (Glycine max), as an important crop for both oil and grains, is a major source of high-quality plant proteins for humans. Among various natural disasters affecting soybean production, waterlogging is one of the key factors leading to yield reduction. It [...] Read more.

Soybean (Glycine max), as an important crop for both oil and grains, is a major source of high-quality plant proteins for humans. Among various natural disasters affecting soybean production, waterlogging is one of the key factors leading to yield reduction. It can cause root rot and seedling death, and in severe cases, even total crop failure. Given the significant differences in responses to waterlogging stress among different soybean varieties, traditional single-trait indicators are insufficient to comprehensively evaluate flood tolerance. In this study, relative seedling length (RSL) was used as a comprehensive evaluation index for flood tolerance. Using a chromosome segment substitution line (CSSL) population derived from SN14 and ZYD00006, we successfully identified seven quantitative trait loci (QTLs) associated with seed waterlogging tolerance. By integrating RNA-Seq transcriptome sequencing and phenotypic data, the functions of candidate genes were systematically verified. Phenotypic analysis indicated that Suinong14 had significantly better flood tolerance than ZYD00006. Further research revealed that the Glyma.05G160800 gene showed a significantly up-regulated expression pattern in Suinong14; qPCR analysis revealed that this gene exhibits higher expression levels in submergence-tolerant varieties. Haplotype analysis demonstrated a significant correlation between different haplotypes and phenotypic traits. The QTLs identified in this study can provide a theoretical basis for future molecular-assisted breeding of flood-tolerant varieties. Additionally, the functional study of Glyma.05G161800 in regulating seed flood tolerance can offer new insights into the molecular mechanism of seed flood tolerance. These findings could accelerate the development of submergence-tolerant rice varieties, enhancing crop productivity and stability in flood-prone regions. Full article

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

23 pages, 2872 KiB

Open AccessArticle

Study on Cherry Blossom Detection and Pollination Parameter Optimization Using the SMD-YOLO Model

by Longlong Ren, Yonghui Du, Yuqiang Li, Ang Gao, Wei Ma, Yuepeng Song and Xingchang Han

Agronomy 2025, 15(8), 1915; https://doi.org/10.3390/agronomy15081915 - 8 Aug 2025

Abstract

In response to the need for precise blossom identification and optimization of key operational parameters in intelligent cherry spraying pollination, the SMD-YOLO (You Only Look Once with spatial and channel reconstruction convolution, multi-scale channel attention, and dual convolution modules) cherry blossom detection model [...] Read more.

In response to the need for precise blossom identification and optimization of key operational parameters in intelligent cherry spraying pollination, the SMD-YOLO (You Only Look Once with spatial and channel reconstruction convolution, multi-scale channel attention, and dual convolution modules) cherry blossom detection model is proposed, along with a pollination experiment platform for parameter optimization. The SMD-YOLO model, built upon YOLOv11, enhances feature extraction through the ScConvC3k2 (spatial and channel reconstruction convolution C3k2) module, incorporates the MSCA (multi-scale channel attention) attention mechanism, and employs the DualConv module for a lightweight design, ensuring both detection accuracy and operational efficiency. Tested on a self-constructed cherry blossom dataset, the model delivered a precision of 87.6%, a recall rate of 86.1%, and an mAP(mean average precision) reaching 93.1% with a compact size of 4765 KB, 2.28 × 10⁶ parameters, a computational cost of 5.8 G, and a detection speed of 75.76 FPS, demonstrating strong practicality and potential for embedded real-time detection in edge devices, such as cherry pollination robots. To further enhance pollination effectiveness, a dedicated pollination experiment bench was designed, and a second-order orthogonal rotational combination experiment method was employed to systematically optimize three key parameters: spraying distance, spraying time, and liquid flow rate. Experimental results indicate that the optimal pollination effect occurs when the spraying distance is 3.4 cm, spraying time is 1.9 s, and liquid flow rate is 339 mL/min, with a deposition amount of 0.18 g and a coverage rate of 97.25%. This study provides a high-precision image detection algorithm and operational parameter optimization basis for intelligent and precise cherry blossom pollination. Full article

(This article belongs to the Special Issue Facility Agriculture Robots and Autonomous Unmanned Management for Crops)

15 pages, 2379 KiB

Open AccessArticle

QTL Mapping of Tomato Fruit Weight-Related Traits Using Solanum pimpinellifolium Introgression Lines

by Yuanhao Zhang, Fei Ding, Huiling Qui, Yingjie Tian, Fangling Jiang, Rong Zhou and Zhen Wu

Agronomy 2025, 15(8), 1914; https://doi.org/10.3390/agronomy15081914 - 8 Aug 2025

Abstract

As the primary harvested organ, fruit size and weight hold significant economic importance during tomato production. Therefore, elucidating the genetic mechanisms underlying fruit size and weight is of considerable agronomic value. In this study, the Solanum pimpinellifolium introgression lines were constructed with “LA2093” [...] Read more.

As the primary harvested organ, fruit size and weight hold significant economic importance during tomato production. Therefore, elucidating the genetic mechanisms underlying fruit size and weight is of considerable agronomic value. In this study, the Solanum pimpinellifolium introgression lines were constructed with “LA2093” as the donor and “Jina” as the recipient, and a genetic linkage map was constructed. Preliminary QTL mapping was conducted using four fruit-related traits: single fruit weight, fruit diameter, fruit length, and fruit shape index. A total of 10 QTLs were identified, including one for single fruit weight (qFw-3), five for fruit diameter (qFtd-3-1, qFtd-3-2, qFtd-4, qFtd-7, and qFtd-12), two for fruit length (qFl-3 and qFl-11), and two for fruit shape index (qFsi-2 and qFsi-3). To explore the key regulatory genes of the single fruit weight QTL qFw-3 locus, it was further finely mapped between SSR3-14 and C03M65101. The SSR3-14 and C03M65101 interval contained 57 genes on chromosome 3 (64.68–65.10 Mb) in the reference genome. Among these, eight genes, including Solyc03g114830, Solyc03g114870, Solyc03g114880, Solyc03g114890, Solyc03g114900, Solyc03g114910, Solyc03g115200, and Solyc03g115380, were identified as candidate genes involved in regulating fruit weight. These studies provide a basis for future functional validation of key regulatory genes and offer valuable genetic resources for the improvement of fruit size and weight during tomato breeding. Full article

(This article belongs to the Special Issue Genetics and Breeding of Field Crops in the 21st Century)

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18 pages, 12456 KiB

Open AccessArticle

Predicting the Global Distribution of Fusarium circinatum Using MaxEnt Modeling

by Xiaorui Zhang, Chao Chen, Fengqi Wang and Tingting Dai

Agronomy 2025, 15(8), 1913; https://doi.org/10.3390/agronomy15081913 - 8 Aug 2025

Abstract

Fusarium circinatum poses severe threats to agroforestry ecosystem as a globally significant pathogenic fungus. This study utilized multi-source species distribution data and environmental variables (climatic, topographic, and soil factors) to predict the global potential habitat suitability of F. circinatum and its response to [...] Read more.

Fusarium circinatum poses severe threats to agroforestry ecosystem as a globally significant pathogenic fungus. This study utilized multi-source species distribution data and environmental variables (climatic, topographic, and soil factors) to predict the global potential habitat suitability of F. circinatum and its response to future climate change using an optimized MaxEnt model (RM = 1, FC = LQ). The results indicate that the current total suitable area spans approximately 69.29 million km², with highly suitable habitats (>0.493) accounting for 15.07%, primarily concentrated in East Asia, southwestern North America, western South America, the Mediterranean coast, and eastern Australia. The distribution of F. circinatum’s suitable habitats is primarily constrained by the following environmental factors, ranked by contribution rate: coldest quarter precipitation (29.4%), coldest quarter mean temperature (18.2%), annual mean temperature (17.2%), and annual precipitation (12%). Under future climate scenarios, the suitable habitats exhibited an overall contraction and poleward shift, with the most significant decline in highly suitable areas observed under SSP370-2050s (−52.1%). The centroid of suitable habitats continuously migrated northwestward from Gombe State, Nigeria, with the maximum displacement reaching 1077.6 km by SSP585-2090s. This study reveals a latitude gradient redistribution pattern of F. circinatum driven by climate warming, providing a scientific basis for transboundary biosecurity and early warning systems. Full article

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

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26 pages, 483 KiB

Open AccessReview

Engineering Crops for Enhanced Drought Stress Tolerance: A Strategy for Sustainable Agriculture

by Heriberto García-Coronado, Angel-Javier Ojeda-Contreras, Guillermo Berumen-Varela, Jesús-Martín Robles-Parra, Avtar K. Handa and Martín-Ernesto Tiznado-Hernández

Agronomy 2025, 15(8), 1912; https://doi.org/10.3390/agronomy15081912 - 8 Aug 2025

Abstract

Drought stress can reduce agricultural production, which is a challenge considering the food demand due to the increase in world population. To face this challenge, the design of plants with a phenotype of drought stress tolerance is needed. Conventional breeding has been widely [...] Read more.

Drought stress can reduce agricultural production, which is a challenge considering the food demand due to the increase in world population. To face this challenge, the design of plants with a phenotype of drought stress tolerance is needed. Conventional breeding has been widely used with this goal, but it requires considerable time and resources. Drought stress response and tolerance are complex issues influenced by numerous environmental and genotypic factors. In this review, experiments involving novel biotechnological tools to improve plant breeding are described and discussed. These experiments involve the use of techniques to accelerate breeding cycles and to enhance the selection of superior genotypes. Furthermore, experiments carried out to elucidate the molecular mechanism of drought stress tolerance and to engineer crops to achieve drought stress tolerance using recombinant DNA technology are described. The main traits associated with drought-tolerant genotypes and the response to drought stress at the morphological, physiological, metabolic, and biochemical levels are analyzed. To cope with the complexity of plant drought response, conventional breeding needs to be integrated with novel tools. It is hoped that this will help to achieve sustainable agriculture development; however, the implications of the use of these biotechnological tools, both alone and coupled, need to be analyzed. Full article

(This article belongs to the Special Issue Physiological, Biochemical, and Molecular Mechanisms of Abiotic Stress Tolerance in Fruits)

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