Crop Yield Stability Research Articles

Improved Prototypical Network Model for Classification of Farmland Shelterbelt Using Sentinel-2 Imagery

Farmland shelterbelt plays an important role in protecting farmland and ensuring stable crop yields, and it is mainly distributed in the form of bands and patches; different forms of distribution have different impacts on farmland, which is an important factor affecting crop yields. Therefore, high-precision classification of banded and patch farmland shelterbelt is a prerequisite for analyzing its impact on crop yield. In this study, we explored the effectiveness and transferability of an improved Prototypical Network model incorporating data augmentation and a convolutional block attention module for extracting banded and patch farmland shelterbelt in Northeast China, and we analyzed the potential of applying it to the production of large-scale farmland shelterbelt products. Firstly, we classified banded and patch farmland shelterbelt under different sample window sizes using the improved Prototypical Network in the source domain study area to obtain the optimal sample window size and the optimal classification model. Secondly, fine-tuning transfer learning and learning from scratch directly were used to classify the banded and patch farmland shelterbelt in the target domain study area, respectively, to evaluate the extraction model’s migratability. The results showed that classification of farmland shelterbelt using the improved Prototypical Network is very effective, with the highest extraction accuracy under the 5 × 5 sample window; the accuracies of the banded and patch farmland shelterbelt are 92.16% and 90.91%, respectively. Using the fine-tuning transfer learning method in the target domain can classify the banded and patch farmland shelterbelt with high accuracy, above 95% and 89%, respectively. The proposed approach can provide new insight into farmland shelterbelt classification and farmland shelterbelt products obtained from freely accessible Sentinel-2 multispectral images.

Saline Water Irrigation Changed the Stability of Soil Aggregates and Crop Yields in a Winter Wheat–Summer Maize Rotation System

Irrigation using saline water is extensively used in areas of agricultural production where freshwater is scarce. However, saline water irrigation adversely impacts soil’s physicochemical characteristics and crop productivity. In this study, we established irrigation water with five salinity levels (ECiw, 1.3, 3.4, 7.1, 10.6, 14.1 dS·m−1) to investigate how these salinity levels influenced grain yields as well as soil salinity, alkalinity, sodicity, and aggregate stability in the 0~20 cm soil layer of a wheat and maize rotation field (in 2022–2023). Tukey’s test, entropy-weighted TOPSIS, and the least squares method were used to analyze the significance analysis, comprehensively evaluate the soil aggregate stability and soil index comprehensive score (SICS), and achieve linear fitting, respectively. The results showed that when ECiw > 3.4 dS·m−1, there was a significant increase in the soil salinity, pH, and sodium adsorption ratio. When ECiw > 7.1 dS·m−1, a significant reduction in soil aggregate stability was observed. When ECiw ≤ 3.4 dS·m−1, there was no significant reduction in the grain yields of wheat and maize. Furthermore, the annual grain yields of wheat and maize decreased by 5% and 10%, respectively, resulting in a change in ECiw values from 2.98 to 4.24 dS·m−1, based on the linear regression analysis of SICS and ECiw, as well as the annual grain yields and SICS. Under uniform irrigation conditions, the soil salinity, alkalinity, and sodicity were lower, and soil aggregate indexes were more stable at the maturity stage of maize.

Effect of layered fertilizer strategies on rapeseed (Brassica napus L.) productivity and soil macropore characteristics under mechanical direct-sowing

Layered fertilization parameters affects crop root system configuration and growth distribution, which in turn affects soil pore properties and aggregate structure. Therefore, understanding the spatial distribution of the root system and soil pore space is helpful in choosing a reasonable fertilization ratio in production practice, which ensures high and stable crop yields and at the same time improves fertilizer utilization and soil health. Albeit the impact of layered fertilization ratio at varied rates on soil pore characteristics in the soil profile at a microscale level remains limited. This study quantifies the impacts of layered fertilization ratio under on rapeseed root distribution and soil pore characteristics using the root analysis system and X-ray computed tomography (XCT). A new fertilization pattern that shallow-deep layer synchronized mechanical sowing was using, rotary tillage mixed fertilization in the shallow layer and 10 cm side-deep band fertilization in the deeper layer. It set five ratios of fertilizer amounts between shallow and deep layers as 0:4 (FD), 1:3 (FL), 2:2 (FM), 3:1 (FH), and 4:0 (F0), with non-fertilization (CK) as the control treatment. The results indicated that layered fertilization effectively improved the rape root conformation and spatial distribution, significantly increased total soil porosity and moisture content, and reduced soil bulk density and resistance (P < 0.05). Additionally, root configuration is closely related to soil pore structure and crop yield. Notably, compared with other treatments, the macroscopic porosity, equivalent pore diameter, hydraulic radius and roundness of FM treatment are significantly improved, and it effectively improves the yield and quality of rapeseed. Correlation analysis showed that the root system configuration parameters were negatively correlated with soil bulk density and resistance but positively correlated with soil moisture content, and macropore morphology parameters and rapeseed yield. Our study demonstrate that layered fertilization can improved rape growth and soil macropore porosity, but its effect depends on good tillage macropore characteristics and distribution created by reasonable fertilization ratio, which provided a theoretical basis for high-yield, efficient, green, and sustainable mechanized direct-sowing production of rapeseed.

Biotic stress and yield stability in English organic silvoarable agroforestry

In-field trees are thought to buffer arable crops from climate extremes through the creation of microclimates that may reduce the impacts of heat, wind, and cold. Much less is known about how trees and their biotic interactions (e.g. with natural enemies of pests and wild understory plants) impact crop yield stability to biotic stresses such as crop pests and disease. Modelling these interactions using conventional approaches is complex and time consuming, and we take a simplified approach, representing the agroecosystem as a Boolean regulatory network and parameterising Boolean functions using expert opinion. This allies our approach with decision analysis, which is increasingly finding applications in agriculture. Despite the naivety of our model, we demonstrate that it outputs complex and realistic agroecosystem dynamics. It predicts that, in English silvoarable, the biotic interactions of in-field trees boost arable crop yield overall, but they do not increase yield stability to biotic stress. Sensitivity analysis shows that arable crop yield is very sensitive to disease and weeds. We suggest that the focus of studies and debate on ecosystem service provision by English agroforestry needs to shift from natural enemies and pests to these ecosystem components. We discuss how our model can be improved through validation and parameterisation using real field data. Finally, we discuss how our approach can be used to rapidly model systems (agricultural or otherwise) than can be represented as dynamic interaction networks.

Long‐term tillage and cover cropping differentially influenced soil nitrous oxide emissions from cotton cropping system

AbstractClimate‐smart agricultural practices, such as no‐tillage (NT) and cover cropping, have been widely adopted and are anticipated to yield multiple benefits, including soil carbon sequestration, enhancing soil health, and crop yield stability. However, their influence on nitrous oxide (N2O) emissions varies, with the potential of both increasing and decreasing N2O emissions. Increasing N2O emissions under these practices may potentially offset the climate mitigation benefits from increased soil carbon sequestration. We investigated N2O emissions in response to 42 years of long‐term adoption of NT and legume cover crop, under nitrogen (N) rates of 0 and 67 kg N ha−1, in a continuous cotton system in the Southeastern United States. Intensive manual chamber‐based measurements were conducted over two growing seasons (2021–2022 and 2022–2023). Long‐term NT did not significantly affect cumulative N2O emissions during the study period (p &gt; 0.05). Hairy vetch cover crop‐grown plots emitted two to three times more N2O than those without cover crops in 2021–2022, with no significant effect observed in 2022–2023. Cumulative emissions in cover crop plots were greater compared to those in no cover crop plots when fertilized with 67 kg N ha−1 in 2021–2022; however, this trend did not persist in 2022–2023. While interannual variability exists, our results generally suggest that long‐term NT may not increase N2O emissions, hence its adoption could enhance its broader soil health and climate benefits via soil carbon sequestration, whereas managing legume cover crop residues in N‐fertilized systems is critical to mitigate N2O emissions.

Influence of Climatic Factors on Rust Severity in Sorghum in Dharwad, Karnataka, India

Sorghum rust, caused by Puccinia purpurea, significantly reduces crop yield, affecting plant growth and grain quality. Understanding the impact of weather parameters on disease incidence is crucial for timely disease management, to enhance crop resilience and yield stability. This study aims to identify and quantify the relationship between weather parameters and the incidence of sorghum rust, to inform decision-making on disease management strategies. A comprehensive analysis was conducted utilizing 17 years of secondary data (2006-2022) sourced from the All India Coordinated Research Project (AICRP) on Sorghum and the Department of Agrometeorology at the Climate Model Intercomparison Project (CMIP), University of Agricultural Sciences (UAS), Dharwad. The study employed statistical methods, including Multiple Linear Regression (MLR) and Step-wise Regression, to model the dependence of rust disease incidence on independent variables such as precipitation, temperature, relative humidity, wind speed, radiation, and heat flux. The results revealed the MLR model explains 65.45% of the variation and the Step-wise Regression model identifies four critical parameters- relative humidity, heat flux, wind speed, and radiation that together accounted for 65.09% of the variation without exhibiting multicollinearity (Variance Inflation Factor values below 10). These findings enhance the understanding of environmental impacts on sorghum rust and can inform future agricultural management strategies for disease prediction and control.

Genetic Control of Tolerance to Drought Stress in Wild Soybean (Glycine soja) at the Vegetative and the Germination Stages.

Drought stress, which is becoming more prevalent due to climate change, is a significant abiotic factor that adversely impacts crop production and yield stability. Cultivated soybean (Glycine max), a versatile crop for humans and animals, exhibits sensitivity to drought, resulting in reduced growth and development under drought conditions. However, few genetic studies have assessed wild soybean's (Glycine soja) response to drought stress. In this work, we conducted a genome-wide association study (GWAS) and analysis of wild soybean accessions to identify loci responsible for drought tolerance at the vegetative (n = 187) and the germination stages (n = 135) using the available resequencing data. The GWAS analysis of the leaf wilting score (LWS) identified eight single-nucleotide polymorphisms (SNPs) on chromosomes 10, 11, and 19. Of these, wild soybeans with both SNPs on chromosomes 10 (adenine) and 11 (thymine) produced lower LWS, indicating that these SNPs have an important role in the genetic effect on LWS for drought tolerance at the vegetative stage. At the germination stage, nine SNPs associated with five phenotypic measurements were identified on chromosomes 6, 9, 10, 13, 16, and 17, and the genomic regions identified at the germination stage were different from those identified for the LWS, supporting our previous finding that there may not be a robust correlation between the genes influencing phenotypes at the germination and vegetative stages. This research will benefit marker-assisted breeding programs aimed at enhancing drought tolerance in soybeans.

Assessment of bioenergy plant locations using a GIS-MCDA approach based on spatio-temporal stability maps of agricultural and livestock byproducts: A case study

Addressing the global challenge of energy sustainability and global directives on farming emissions, the United Nations, the European Union, and China have led with strict targets for clean energy, renewable share growth, and carbon neutrality, highlighting a commitment to collective sustainability. This work is situated within the ambit of the Sustainable Development Goals (SDGs), advocating for a transition towards renewable energy sources. With substantial and accessible bioenergy resources, notably in Hubei Province, China, biogas technology has emerged as an emission-cutting solution. This research, focused on the Jianghan Plain, employs an integrated approach combining spatial analyses with machine learning tools to evaluate crop yield stability over two decades, with the aim of maximising the biogas yield from agricultural byproducts, i.e., crop straw and livestock manure. Using Multi-Criteria Decision Analysis (MCDA), which is informed by grey-based DEMATEL, 9 constraints and 13 environmental, social, and economic criteria were assessed to identify optimal sites for biogas facilities. The findings underscore the significant bioenergy potential of agricultural byproducts from the plain of 6.3 × 1012 kJ/year at an 11.4 kJ/m2 density. Stability analyses revealed consistent biomass availability, with rice in Gongan and Shayang and wheat in Jiangling being the primary contributors. Through the MCDA, 45–66 optimal biogas plants were identified across 4 critical counties (Zhongxiang, Shangyang, Jingshan, and Yichen), balancing the energy supply and demand under various stable scenarios. Furthermore, this study demonstrated the criticality of moderate biomass stability for stakeholder consensus and identified areas of high stability essential for energy demand fulfilment. Theoretically, this study offers a practical model for bioenergy resource exploitation that aligns with global sustainability and carbon neutrality goals to address the urgent need for renewable energy solutions amidst the global energy crisis. Practically, this study sets a precedent for policy and planning in environmental, agricultural, and renewable sectors, signifying a step forwards in achieving environmental sustainability and an energy-efficient future.

Buckwheat (Fagopyrum esculentum Moench.) as an emerging companion crop in annual cropping systems: A systematic review

Sustainable intensification is considered an efficient alternative to conventional agriculture to feed a growing population while maintaining and benefitting the environment. Intercropping is one of the most studied practices to obtain production gains and other ecosystem services. Most intercrops involve legumes and cereals, but other species combinations should be explored to further increase the diversity of intercropping systems. Buckwheat (Fagopyrum esculentum Moench.; Polygonaceae) is an emerging minor crop which is gaining attention in alternative intercropping systems.This review provides a comprehensive view of the state of the art on the role of buckwheat as a companion crop in arable cropping systems. Despite buckwheat being well-known for its weed-suppressive ability, intercropping using buckwheat for weed control has received little attention. Few crops have so far been considered in relation to the introduction of buckwheat in annual cropping systems. This review uncovers a largely untapped research field involving buckwheat. The research perspectives are multiple as buckwheat consumption is increasing and its attractive flower resources and rapid growth offer the provision of several agro-ecosystem services that directly and indirectly benefit crop yield stability.

Precision phenotyping of a barley diversity set reveals distinct drought response strategies.

Plants exhibit an array of drought responses and adaptations, where the trade-off between water loss and CO2 uptake for growth is mediated by regulation of stomatal aperture in response to soil water content (SWC), among other factors. For crop yield stability, the question is how drought timing and response patterns relate to post-drought growth resilience and vigor. We earlier identified, in a few reference varieties of barley that differed by the SWC at which transpiration was curtailed, two divergent water use strategies: water-saving ("isohydric") and water-spending ("anisohydric"). We proposed that an isohydric strategy may reduce risk from spring droughts in climates where the probability of precipitation increases during the growing season, whereas the anisohydric is consistent with environments having terminal droughts, or with those where dry periods are short and not seasonally progressive. Here, we have examined drought response physiology in an 81-line barley (Hordeum vulgare L.) diversity set that spans 20th century European breeding and identified several lines with a third, dynamic strategy. We found a strong positive correlation between vigor and transpiration, the dynamic group being highest for both. However, these lines curtailed daily transpiration at a higher SWC than the isohydric group. While the dynamic lines, particularly cv Hydrogen and Baronesse, were not the most resilient in terms of restoring initial growth rates, their strong initial vigor and high return to initial transpiration rates meant that their growth nevertheless surpassed more resilient lines during recovery from drought. The results will be of use for defining barley physiological ideotypes suited to future climate scenarios.

Effects of Long-Term Fertilizer Application on Crop Yield Stability and Water Use Efficiency in Diversified Planting Systems

Exploring crop yield stability and the relationship between the water–fertilizer effect and annual precipitation type in a broomcorn millet–potato–spring corn rotation system under long-term fertilization on chestnut cinnamon soil in loess tableland can provide a scientific basis for rational fertilization in the northwest Shanxi region in years with different precipitation. This study was based on a 33-year long-term fertilizer experiment, using four fertilizer treatments: no fertilizer as control (CT), single fertilizer nitrogen (N), single organic fertilizer (M), and nitrogen fertilizer with organic fertilizer (NM). The results showed that broomcorn millet and maize had the highest yield in wet years, while potatoes had the highest yield in normal years and the yield under NM treatment was the highest. The sustainable yield index (SYI) values for potato and maize were higher than the SYI for the broomcorn millet during years with different precipitation and the SYI for the NM treatment was the highest. The water use efficiency of NM treatment was the highest. The yield of broomcorn millet and maize was affected by nitrogen fertilizer, organic fertilizer, and precipitation during the growth period, while the potato yield was mainly affected by nitrogen fertilizer and organic fertilizer. Therefore, the rotation of potato–maize and the rational allocation of organic and inorganic fertilizer (NM) is the best planting system in this region.

Exploring management strategies to improve yields and reduce reactive nitrogen emissions in a summer maize‐winter wheat cropping system under long‐term climate variability

AbstractAchieving high stable crop yields and minimal environmental damage is crucial to enhance the sustainability of agriculture in China. Process‐based models are indispensable tools to develop agronomy management practices to achieve sustainable agriculture by simulating crop production and emissions of reactive nitrogen (N), particularly in complex climate scenarios. In this study, a long‐term field experiment with an intensive summer maize‐winter wheat rotation system in north‐central China was simulated using the DeNitrification‐DeComposition (DNDC) model. The DNDC model validation and calibration was done by using two‐year monitoring data of crop yields and nitrous oxide emission fluxes and ammonia volatilization. Moreover, the optimal management practices to promote crop production and reduce the reactive N loss under 22 years of climate variability were explored using the calibrated DNDC model in this region. The results showed that the DNDC model effectively simulated wheat and maize yields, N uptake, ammonia volatilization, and nitrous oxide emissions. Sensitivity analyses demonstrated that the agronomic management practices (N rates and ratio of base to topdressing, planting time, and tillage depth) substantially affected crop yields and reactive N losses under long‐term climate variability. Compared with current farming practices, optimal Nutrient Expert (NE) management achieved an increase in high yields and environmental pollution radiation by altering the rate of N application and ratio of base to topdressing. Moreover, the optimal management strategies developed by the DNDC model, such as adjusting the planting date and tillage depth, further increased the average grain yield by 2.9% and reduced the average reactive N losses by 10.5% compared with the NE management implemented in the annual rotation cropping with a 22‐year simulation. This study suggests that the modeling method facilitates the development of most effective agronomic management practices to promote crop production and alleviate the negative impact on environment.

Photosynthesis of rice leaves with a parallel venation is highly tolerant to vein severing.

Vein severing in plants caused by leaf damage is common in fields where crops are cultivated. It is hypothesized that leaves with complex reticulate venation can withstand hydraulic disturbances caused by vein severing, thereby preserving leaf carbon assimilation. However, limited research focuses on vein damage of leaves with parallel venation. We studied how vein-severing affected the photosynthetic traits of rice (Oryza sativa) leaves in seconds, minutes and days, under varying water-demand conditions and differing extents of water supply disruption. Rice leaves completely lost their photosynthetic capacity within 2.5 minutes after excision. Severing the midrib resulted in reduced light-saturated photosynthetic rate (A), stomatal conductance (gsw ) and transpiration rate (E) by 2.6, 6.8 and 5.9%, respectively, already after thirty minutes. We further investigated the photosynthetic trait responses to various extents of leaf width severing, while keeping the midrib functional. Surprisingly, A, gsw and E in the downstream area of the severed leaves largely remained stable, showing minimal variation across different leaf width severing ratios. These traits declined only slightly even under increased ambient light intensity and leaf-to-air vapor pressure deficit. This sustained photosynthesis post-severing is attributed to the efficient lateral water transport. Long-term leaf damage slightly but not significantly, impacted the downstream photosynthetic traits within five days post-severing. However, a more pronounced reduction in gas exchange during leaf senescence was observed nine days after severing. These findings suggested that rice leaves can tolerate hydraulic disturbances from vein severing and maintain functionality under various conditions, which is crucial for crop yield stability. However, long-term consequences require further investigation.

Regional detection and assessment of chilling damage on maize considering land surface temperature, crop growth status and solar radiation changes

AbstractIncreased frequency and severity of chilling damage events pose potential risks to crop performance and productivity due to climate change. Accurate and real‐time access to chilling damage is important for crop growth and yield stability based on field's actual environment. To precisely identify regional chilling events and evaluate the impacts on crops, this study presents a model to estimate field air temperature in view of field crop situations. Land surface temperature, enhanced vegetation index, solar‐induced chlorophyll fluorescence and solar declination were involved in the model. With field simultaneous continuous monitoring and multisource fused remote sensing data, the model was calibrated and validated in Jiefangzha Irrigation Area (JIA) and Changchun City (CC) in North China, accompanied by the determination coefficient ≥0.756, root mean square error ≤0.782°C, relative error ≤0.041 and consistency index ≥0.902. Meanwhile, sensitivities of the model factors were determined through path analysis, where the factors performed according to the order solar‐induced chlorophyll fluorescence &gt;solar declination &gt;land surface temperature &gt; enhanced vegetation index. Using the validated model, chilling damage to maize was further detected in JIA and CC from 2010 to 2020. Results showed that the severity of chilling damage was greater in CC than in JIA, along with the sterile‐type occurring three events in JIA and seven in CC, while the delayed‐type only twice in JIA in 2012 and 2016, but five times in CC in 2013, 2014, 2016, 2017 and 2019, respectively, being consistent with local statistics. In response to chilling damage, enhanced vegetation index and solar‐induced chlorophyll fluorescence demonstrated the negative chilling effects on greenness and light use efficiency for fluorescence. Serious yield losses were caused, with yield‐reducing by 5.00% (Dehui, 2013), 19.00% (Jiutai, 2014), 21.65% (Suburban district, 2016), 8.83% (Shuangyang, 2017) and 2.19% (Jiutai, 2019) in CC. The linear relationship between yield and growing degree days was a bit weakened by chilling damage, with the determination coefficient varying from 0.614 to 0.531. The increasing rate of yield with growing degree days decreased from 20.365 kg/(°C·d) in non‐chilling damage years to 9.670 kg/(°C·d) in chilling damage years. These findings indicate that the presented model is especially adaptive for agricultural field environments, enabling rapid precision detection of chilling damage on crops at regional scales. It will provide references for gauging the impact of chilling damage on crops, finding efficient solutions to the stress and ensuring sustainable development of agriculture.

Effects of Different Proportions of Organic Fertilizer Replacing Chemical Fertilizer on Soil Nutrients and Fertilizer Utilization in Gray Desert Soil

Organic fertilizer can improve soil management and alleviate soil nutrient loss caused by excessive fertilization. This study determines a fertilization scheme that can achieve high and stable crop yield and effective soil fertilization by exploring the effects of different organic fertilizer proportions on soil nutrient content, fertilizer utilization rate, and wheat yield. The experiment was conducted from 2018 to 2020 using the Xinchun 38 wheat variety and gray desert soil. The experiment used six treatments: no fertilizer (CK), with normal nitrogen and phosphorus fertilizer (CF). The amount of conventional chemical nitrogen fertilizer was reduced by 6%, 12%, 18%, and 24%, respectively, and supplemented with organic nitrogen fertilizer of the same proportion. The experimental treatment codes were SF6, SF12, SF18, and SF24, respectively. Plant samples from six wheat growth stages and 0–20 cm soil samples were collected to analyze the nitrogen and phosphorus content and organic matter; dry matter accumulation, crop yield, and yield components were measured at the harvest stage. Soil available nitrogen, phosphorus, potassium, and soil organic matter contents increased with the replacement ratio of organic fertilizer after three consecutive years of application. The available nutrients and organic matter in soil treated with SF18 and SF24 were significantly higher than those in CK and CF. The dry matter accumulation and nutrient accumulation of wheat increased with increasing organic fertilizer replacement rates of SF18 and SF24, respectively. Nitrogen and phosphorus fertilizer utilization rates, partial productivity, and agricultural use efficiency also increased, with the SF18 and SF24 treatments having higher organic fertilizer replacement rates than those in the other treatments. The number of ears, 1000-grain weight, and yield of wheat treated with SF18 treatment produced the best results. Therefore, continuously using organic fertilizer as a partial replacement for conventional fertilizer can increase wheat growth and soil nutrient availability, which can improve the utilization rate of fertilizer, thereby achieving stability and even a significant increase in yield.

Optimized tillage can enhance crop tolerance to extreme weather events: Evidence from field experiments and meta-analysis

The frequency of droughts and floods has increased due to climate change and human activities, leading to adverse impacts on agricultural production. Conventional tillage exacerbates the vulnerability of crops to extreme weather. Optimized tillage practices can maintain crop yield stability by increasing soil water-holding capacity during dry seasons and improving crop lodging resistance during heavy rainfall events. The effects of tillage practice under different rainfall types on the productivity of summer maize were studied by combining a five-year field experiment and a meta-analysis. The study tested four tillage treatments: conventional tillage (CT), no-tillage (NT), ridge cultivation with no-tillage (RNT), and winter wheat conventional tillage followed by summer maize no-tillage (NC). Normal rainfall years (2018, 2019 and 2021), a wet year (2020), and a drought year (2022) were experienced during the experiment. Compared to CT, NC significantly increased available soil water storage during the dry season by an average of 19.7 % (P < 0.05). NC and RNT had lower lodging rates during the wet year than CT, and over the five years, NC had a higher average maize yield (9.8 t ha−1) than RNT, while RNT had a higher yield during the wet year (10.7 t ha−1). NC also had significantly higher yield stability than CT. Furthermore, NC and RNT had higher rainwater use efficiencies (RUE) (23.9 and 23.0 kg ha−1 mm−1, respectively) than NT and CT (22.9 and 21.6 kg ha−1 mm−1, respectively). A meta-analysis showed that the crop yield under combined tillage (COT) was significantly higher than CT and NT by 6.7 % and 7.1 %, respectively, confirming the reliability and universality of the field experiment results. Overall, NC rotation is recommended as the best tillage system for sustainable crop production under semi-arid conditions, while RNT can be used in areas with abundant rainfall and prone to flooding. Our research findings offer evidence-based insights into management strategies that can enhance agricultural ecosystem resilience and production stability under extreme climate conditions.

Controlling Fusarium head blight in wheat through a Mixture of varieties in an organic production system

In the organic production system, the management of diseases and pests is based on agricultural practices rather than the use of certified phytosanitary inputs. The mixture of varieties is an agricultural practice that has shown its interest not only in the management of diseases and pests but also in the increase and stability of crop yields. The objective of our study is to evaluate the performance of this practice in the management of fusarium head blight in wheat. To achieve this objective, we conducted four trials. Two trials (one on durum and the other on soft wheat) in 2019 on a certified organic farm and the two trials were repeated in 2020. During the two years of experimentation, we compared the mixture of four durum wheat varieties and the mixture of four soft wheat varieties with the monoculture varieties. In the field, we evaluated the severity of Fusarium head blight and wheat yield components as well as the grain yield. The results showed a significant difference between the different treatments for Fusarium head blight severity and yield components for both species and in both years of the experiment.

Application of machine learning methods for crop rotation selection in organic farming system

This study demonstrates the possibility of crop rotation selection based on the assessment of productivity and sustainability of crop production under different atmospheric moisture conditions. The study considers 8 crop rotations oriented to grain production. The data obtained in long-term field experiments in the forest-steppe of the Novosibirsk region were used. As a result of the implementation of the decision tree (CART) and the use of ensemble algorithm (Random Forest) the construction of a model characterized by a fairly high predictive ability was performed. Standardized Precipitation Index was chosen as the main predictor characterizing atmospheric moistening in different periods of vegetation. The most stable from the point of view of stability of crop yield – grain-fallow with winter rye, grain-fallow with legumes (vetch-oats), in conditions of manifestation of atmospheric drought of different severity were selected. The possibility of using machine learning methods (CART, Random Forest) as effective tools in the selection of crop rotation for sustainable grain production without the use of chemicalization in soil and climatic conditions of Siberia, as well as the assessment of possible risks in the transition of crop production to organic technologies were scientifically substantiated.

Biological soil conditioner with reduced rates of chemical fertilization improves soil functionality and enhances rice production in vegetable-rice rotation

Soil is an essential source of nutrients for crop growth, but excessive chemical fertilizer can lead to soil acidification and decreased sustainability. Organic fertilizer helps improve soil physicochemical properties and increase soil utilization efficiency. However, soil functionality and crop sustainability response to organic fertilizers need further research. In this study, multiple fertilizer practices (including different amounts of nitrogen fertilizer or soil conditioners, traditional organic fertilizer), various rice varieties, and other rotation systems were applied to test the effects of soil conditioners on crop yield and soil fertility. The results showed that crop yield sustainability and stability were significantly positively correlated with soil pH, EC value, and nitrogen (Pearson r > 0.5). In addition, improving soil quality was beneficial to increasing crop yield sustainability and stability (R2 > 0.5). Chemical fertilizers and soil conditioners can increase soil nutrient content and improve crop yield sustainability index (>0.8). Applying soil conditioners can enhance the activity of soil catalase and urease in paddy soil, especially in the 12 and 15 m3 ha−1 soil conditioner treatments due to soil microbial activity being affected by soil salinity and organic matter content. Soil conditioners increase the mass of Nitrospira species in soil, decompose nitrogen in the soil, and reduce soil nitrate and nitrite content, thereby improving soil pH and reducing the risk of soil acidification caused by excessive chemical fertilizer. Combining soil conditioners and chemical fertilizer (20 % less than traditional fertilization) can promote soil quality and fertility while improving crop yield sustainability and stability.

Variations in crop yield caused by different ratios of organic substitution are closely related to microbial ecological clusters in a fluvo-aquic soil

ContextPartial substitution of chemical fertilizer with organic fertilizer (PSCFOF) can improve soil quality and reduce the overreliance of crop yield on chemical fertilizers. However, the relationship between alterations in crop yield and soil microbial community in response to various substitution ratios is not comprehensively understood. ObjectivesThis study aimed to investigate the impact of PSCFOF on soil nutrient supply, enzyme activity, bacterial and fungal community, and crop yield. MethodsAn 11-year (2009 – 2021) field experiment was carried out in a winter wheat–summer maize double-cropping system with four fertilization regimes (no fertilizer, NF; pure chemical fertilizer, NPK; 30% organic substitution, NPKLM; and 50% organic substitution, NPKHM). Co-occurrence network analysis was applied to examine the importance of ecological clusters and keystone species in controlling microbial activities and crop yields. ResultsThere were no significant differences in soil nutrient contents and annual crop yield between the NPK and NPKLM treatments. However, the NPKHM treatment resulted in significant reductions in crop yield by 9.49%− 16.78%, despite increasing soil organic matter (SOM), total nitrogen (TN), available nitrogen (AN), and available phosphorus (AP) by 9.05%, 7.26%, 11.67%, and 26.62%, respectively. This contrasting effect was primarily attributed to the influence of a specific ecological cluster (module 2), rather than the entire microbial community. Long-term 50% organic substitution would suppress keystone species within module 2, such as Aggregatilinea, Luteimonas, Usitatibacter and Microvirga. These species were specifically correlated with soil carbon enzyme activities, including β-glucosidase, invertase, and dehydrogenase, and contributed significantly and positively to crop yield. ConclusionsOrganic substitution at different ratios altered soil nutrient content, enzyme activities and microbial community in different intensities and directions. Long-term 30% organic substitution could preserve soil fertility and microbial community, leading to stable crop yield; whereas 50% organic substitution could inhibit keystone species, reduce extracellular enzyme activity and ultimately lead to a decrease in crop yield. ImplicationsOur results highlight the importance of ecological clusters within soil microbial co-occurrence network in regulating crop yield, presenting a new perspective on the variations in crop yield resulting from varying ratios of organic substitution.