Affect Crop Yield Research Articles

Management of soil phosphorous using phosphate solubilizing microorganisms: A sustainable approach

Phosphorus is crucial for plant growth and productivity, and its scarcity in soil negatively affects crop yields. A major portion of chemical phosphate fertilizer precipitates with soil minerals, making it unavailable for plant growth. Phosphate-solubilizing microorganisms play a pivotal role in enhancing phosphorus availability, facilitating better nutrient absorption, and ultimately boosting plant growth. This article presents a brief overview of the phosphorus status in Indian soil, discusses the various forms of phosphorus and its dynamics across different soil types, and analyses the factors involved, highlighting the importance of phosphorus management for sustainable agriculture. Physiological and molecular mechanisms of microbial phosphate solubilization provide deep insights into exploring PSMs for managing phosphorous in different soil types. It also provides a path for the necessity to explore the multifarious plant growth-promoting traits of PSMs underscoring its applicability for sustainable agricultural practices with viable economy. The mechanism of solubilization of phosphorus has been discussed to understand the role of microorganisms in different soils. The study highlights the role of significant microorganisms in developing tailored consortia of PSMs and other plant growth-promoting rhizobacteria (PGPR) based on the chemical composition of the soil, along with an integrated nutrient approach incorporating PSMs. This review offers valuable insights into harnessing PSMs and their practical applications, facilitating their broader adoption in agricultural systems to maintain soil health.

Effect of P Reduction on phoD-Harboring Bacteria Community in Solar Greenhouse Soil

Phosphorus (P) enrichment frequently occurs in the soil used in greenhouse vegetable production (GVP). Minimizing the application of P fertilizer represents a crucial approach to mitigating the accumulation of P in the soil and enhancing its utilization efficiency. However, the changes in bacterial communities and the turnover mechanism of soil P fractions related to soil P cycling after P fertilizer reduction are still unclear. To unravel these complexities, we devised three experimental treatments: conventional nitrogen (N), P, and potassium (K) fertilizer (N1P1K1); conventional N and K fertilizer without P (N1P0K1); and no fertilizer (N0P0K0). These experiments were conducted to elucidate the effects of P reduction on cucumber plant growth, soil P fractions, and the phoD-harboring bacterial community in the P-rich greenhouse soil. The results showed that there were no significant differences between the N1P1K1 and N1P0K1 treatments in terms of plant growth, yield, and P uptake, and the values for the N0P0K0 treatment were significantly lower than those for the N1P1K1 treatment. In a state of P depletion (N0P0K0, N1P0K1), the main P sources were Resin-Pi, NaHCO3-Pi, NaHCO3-Po, and NaOH-Pi. The contents of NaOH-Po and CHCl-Po in the N1P0K1 treatment increased significantly. Without P fertilizer, alkaline phosphatase (ALP) activity, phoD gene abundance, and bacterial community diversity were significantly increased. The abundance of Ensifer in the N0P0K0 and N1P0K1 treatments was 8 and 10.58 times that in the N1P1K1 treatment, respectively. Additionally, total phosphorus (TP) and available nitrogen (AN) were key factors affecting changes in the phoD bacterial community, while Shinella, Ensifer and Bradyrhizobium were the main factors driving the change in soil P fractions, and NaHCO3-Pi and NaOH-Pi were key factors affecting crop yield. Therefore, reducing the application of P fertilizer will increases the diversity of phoD-gene-harboring bacterial communities and promote organic P mineralization, thus maintaining the optimal crop yield.

Effect of center-pivot and subsurface drip irrigation systems on growth and evapotranspiration of volunteer corn in corn, soybean, and sorghum

Abstract Volunteer corn (Zea mays L.) is a competitive weed in corn-based cropping systems. Scientific literature does not exist about the water use of volunteer corn grown in different crops and irrigation systems. The objectives of this study were to characterize the growth and evapotranspiration (ETa) of volunteer corn in corn, soybean [Glycine max (L). Merr.], and sorghum [Sorghum bicolor (L.) Moench] under center-pivot irrigation (CPI) and subsurface drip irrigation (SDI) systems. Field experiments were conducted in south-central Nebraska in 2021 and 2022. Soil moisture sensors were installed at depths of 0 to 0.30, 0.30 to 0.60, and 0.60 to 0.90 m to track soil water balance and quantify seasonal total ETa. Corn was the most competitive, as volunteer corn had the lowest biomass, leaf area, and plant height compared with the fallow. Soybean was the least competitive with volunteer corn, as the plant height, biomass, and leaf area of volunteer corn in soybean were similar to fallow at 15, 30, 45, and 60 d after transplanting (DATr). Averaged across crop treatments, irrigation type did not affect volunteer corn growth at 15 to 45 DATr. Soil water depletion and ETa were similar across crop treatments with and without volunteer corn, as water was not a limiting factor in this study. The ETa of volunteer corn was the highest in soybean (623 mm), followed by sorghum (622 mm), and corn (617 mm) under CPI. The SDI had higher irrigation efficiency, because without affecting crop yield, it had 3%, 6%, and 8% lower ETa in soybean (605 mm), sorghum (585 mm), and corn (571 mm), respectively. Although soil water use did not differ with volunteer corn infestation, a soybean yield loss of 27% was observed, which suggests that volunteer corn may not compete for moisture under fully irrigated conditions; however, it can impact the crop yield potential due to competition for factors other than soil moisture.

Climate-Resilient Horticulture: Adapting to Climate Change through Innovative Practices and Technologies

Climate change is a serious threat to horticulture as it will increase temperatures, cause unpredictable rainfall patterns, and extreme weather events that will affect crop yields, quality, and overall agricultural sustainability. Climate-resilient horticulture uses cutting-edge technologies and equipment to overcome these obstacles. Developing crop varieties that are resistant to heat, drought, and salt is a key strategy to make plants more resilient to adverse conditions. To conserve water and guarantee a constant supply of moisture, advanced water management techniques such as drip irrigation and rainwater collection are crucial. Climate adaptation is aided by soil management techniques that increase soil fertility and health, such as conservation tillage and organic amendments. Technological advancements such as precision horticulture enable farmers to optimize inputs and reduce waste, while controlled environment agriculture (CEA) systems, including greenhouses, hydroponics, allow cultivation of crops in regulated environments, reducing external climate impacts. Additionally, genetic engineering and biotechnology offer promising solutions to develop crops with increased climate resilience. Despite the potential of these innovations, challenges such as high costs, knowledge barriers, and policy constraints must be addressed for widespread adoption. This summary underscores the need to integrate these strategies to secure the future of horticulture in a changing climate, ultimately contributing to global food security and agricultural sustainability.

Four birds with one stone: applying nitrification inhibitor on the basis of percarbamide restores yield, decreases fungicide residue, enhances soil multifunctionality and stimulates bacterial community.

Fungicide residues were frequently detected in vegetables and soils, which severely affected crop yields and qualities. Reasonable nitrogen management might promote yields and decrease fungicide carbendazim residues in plant-soil systems. Current study explores comprehensive relationships among carbendazim residues, crop yields, soil multifunctionalities and endophytic and soil bacterial communities after applying nitrification inhibitors (3,4-dimethylpyrazole phosphate and dicyandiamide) and percarbamide to different soils. Combined nitrification inhibitor and percarbamide additions produced multi-effects on restoring yields, declining fungicide residues, promoting soil multifunctionalities and stimulating bacterial communities. Relative to the control, percarbamide application promoted carbendazim dissipations in upland soils but decreased bacterial community diversities and stabilities in different soils. Compared to exclusive percarbamide, extra dicyandiamide applications decreased carbendazim residues by 25.8% in upland soils and 70.2% in paddy soils, declined carbendazim residues in carrots via improving soil pH, ammonium nitrogen (NH4 +-N) and Proteobacteria ratios. Relative to percarbamide application alone, extra dicyandiamide addition promoted the dry carrot yields by 133.2% in upland soils and 33.5% in paddy soils via promoting soil NH4 +-N, Acidobacteriota and Actinobacteriota ratios and bacterial community diversities and stabilities. Upland soil multifunctionality improvements diminished soil carbendazim residues via promoting soil pH and NH4 +-N, and paddy soil multifunctionalities and endophytic bacterial community structures generated negative influences on carrot carbendazim residues. Our study suggested that nitrification inhibitor on the basis of percarbamide generated multi-effects on the different crop-soil systems: restoring carrot yields, reducing carbendazim contents, promoting soil multifunctionalities and stimulating bacterial community diversities and stabilities. © 2024 Society of Chemical Industry.

Optimizing crop monitoring: mapping cultivation stages and types with sentinel-1/2 and random forest algorithm

ABSTRACT Crop-type mapping is essential for agricultural monitoring, improving crop yield models, and supporting sustainable land management. Studying crop phenology, which includes the timing from germination to maturity, is equally important for precise agricultural practices. However, maps detailing crop phenology are scarce. This study addresses this gap by mapping both crop types and cultivation time, offering valuable insights for agriculture applications. The research integrates Sentinel-1/2 data, NDVI phenology curves, and machine learning (ML) algorithms through Google Earth Engine to map crops in El-Behera Governorate, Egypt. By stratifying the region into different soil types, it accounts for various agro-environmental conditions. Field visits in July 2022 provided crop-type information, and Sentinel-2 NDVI curves were used to determine cultivation time. The random forest (RF) classifier, known for its accuracy, was employed, achieving an overall accuracy (OA) of 97.4% for crop type and 95.6% for cultivation time, with high Kappa coefficients. Feature importance analysis highlighted the significance of specific spectral bands, particularly in the Red Edge region, for classification accuracy. Hyperparameter tuning across different zones demonstrated the need for customized tuning. This study enhances understanding of agro-environmental variability’s impact on crop classification and shows the potential of the RF algorithm in advancing crop mapping, suggesting further studies on how shifts in cultivation time could affect crop yield.

Model for Predicting Maize Crop Yield on Small Farms Using Clusterwise Linear Regression and GRASP

Planting a crop involves several key steps: resource assessment, crop selection, crop rotation, planting schedules, soil preparation, planting, care, and harvesting of crops. In this context, estimating the productivity of a crop based on available information, such as expected climatic conditions and agricultural practices, helps farmers reduce the uncertainty of their investment. In Colombia, maize is the fourth most important crop in the country. Significant efforts are required to improve productivity in traditional and technified production systems. In this sense, this research proposes and evaluates an approach called Clusterwise Linear Regression (CLR) to predict the crop maize yield in small farms, considering data on climate, soil, fertilization, and management practices, among others. To develop the CLR model, we conducted the following steps: data collection and preparation, clustering using k-means, cluster optimization with Greedy Random Adaptive Search Procedure (GRASP), and performance evaluation. The cluster optimization process allows the identification of clusters with similar characteristics and generates multiple linear regression models with mixed variables that explain the yield of the farms on each cluster. The Simulated Multiple Start Annealing (MSSA) metaheuristics were also evaluated, but the results of GRASP were the best. The results indicate that the proposed CLR approach is more effective than the linear and nonlinear algorithms mentioned in the literature, such as multiple lasso linear regression, random forests, XGBoost, and support vector machines. These algorithms achieved an accuracy of 70%. However, with the new CLR model, a significantly improved accuracy of 87% was achieved with test data. The clusters’ studies revealed key factors affecting crop yield, such as fertilization, drainage, and soil type. This transparency is a benefit over black-box models, which can be harder to interpret. This advancement can allow farmers to make better decisions about the management of their crops.

Photosynthetic characteristics and genetic mapping of a yellow-green leaf mutant jym165 in soybean

BackgroundLeaves are important sites for photosynthesis and can convert inorganic substances into organic matter. Photosynthetic performance is an important factor affecting crop yield. Leaf colour is closely related to photosynthesis, and leaf colour mutants are considered an ideal material for studying photosynthesis.ResultsWe obtained a yellow-green leaf mutant jym165, using ethyl methane sulfonate (EMS) mutagenesis. Physiological and biochemical analyses indicated that the contents of chlorophyll a, chlorophyll b, carotenoids, and total chlorophyll in the jym165 mutant decreased significantly compared with those in Jiyu47 (JY47). The abnormal chloroplast development of jym165 led to a decrease in net photosynthetic rate and starch content compared with that of JY47. However, quality traits analysis showed that the sum of oil and protein contents in jym165 was higher than that in JY47. In addition, the regional yield (seed spacing: 5 cm) of jym165 increased by 2.42% compared with that of JY47 under high planting density. Comparative transcriptome analysis showed that the yellow-green leaf phenotype was closely related to photosynthesis and starch and sugar metabolism pathways. Genetic analysis suggests that the yellow-green leaf phenotype is controlled by a single recessive nuclear gene. Using Mutmap sequencing, the candidate regions related of leaf colour was narrowed to 3.44 Mb on Chr 10.ConclusionsAbnormal chloroplast development in yellow-green mutants leads to a decrease in the photosynthetic pigment content and net photosynthetic rate, which affects the soybean photosynthesis pathway and starch and sugar metabolism pathways. Moreover, it has the potentiality to increase soybean yield under dense planting conditions. This study provides a useful reference for studying the molecular mechanisms underlying photosynthesis in soybean.

Mitigation strategy of saline stress in Fragaria vesca using natural and synthetic brassinosteroids as biostimulants.

Bassinosteroids (BRs) can induce plant defence responses and promote plant growth. In this work, we evaluated the effect of a natural (EP24) and a synthetic (BB16) brassinosteroid on strawberry (Fragaria vesca ) plants exposed to saline stress. Treated plants showed higher shoot dry weight and root growth compared to untreated control plants. In BR-treated plants, crown diameters increased 66% and 40%, leaf area 148% and 112%, relative water content in leaves 84% and 61%, and SPAD values 24% and 26%, in response to BB16 and EP24, respectively. A marked stomatal closure, increased leaflet lignification, and a decrease in cortex thickness, root diameter and stele radius were also observed in treated plants. Treatments also reduces stress-induced damage, as plants showed a 34% decrease in malondialdehyde content and a lower proline content compared to control plants. A 22% and 15% increase in ascorbate peroxidase and total phenolic compound activities was observed in response to BB16, and a 24% increase in total flavonoid compound in response to both BRs, under stress conditions. These results allow us to propose the use of BRs as an environmentally safe crop management strategy to overcome salinity situations that severely affect crop yield.

Assessing the Synergistic Effects of Deficit Irrigation and Growth Retardants on Insitu Sprouting and Quality Parameters of Groundnut VRI 8

Background: Groundnut is a crucial oilseed crop cultivated year-round, with seed dormancy controlled by genetic and environmental factors. Preventing pre-harvest sprouting is essential, as it is a common issue. To study the effect of deficit irrigation management and foliar application of growth retardant chemicals on pre-harvest sprouting control efficiency to achieve higher yield of groundnut. Methodology: In a field experiment conducted during early summer 2024 at the Agricultural College and Research Institute, Madurai, the effectiveness of different growth retardant chemicals and deficit irrigation management on reducing in-situ sprouting of groundnut kernels was investigated. The experiment included three irrigation management strategies: conventional irrigation and two deficit irrigation treatments where irrigation was withheld from 90 to 105 DAS (Days After Sowing) and 85 to 100 DAS. Additionally, foliar sprays of growth retardant chemicals were applied at 75 and 90 DAS. The chemicals tested were maleic hydrazide (MH) @ 1250 ppm, cycocel (CCC) @ 1000 ppm, abscisic acid (ABA) @ 750 ppm, and salicylic acid (SA) @ 750 ppm. Proper agronomic practices were followed throughout the crop growth cycle. Results: Among the growth retardant chemicals tested, MH @ 1250 ppm proved effective in inducing dormancy. Withdrawal of irrigation from 90 to 105 DAS also significantly contributed to dormancy induction, extending dormancy by more than 5 days post-harvest as well as reduced the pod loss which significantly increased pod yield. It was because of the reduction in soil moisture content during harvest stage and alteration in the hormonal activities. Specifically, the combined treatment of foliar application of MH @ 1250 ppm and no irrigation from 90 to 105 DAS reduced germination percentage by 12.6%, 36.8% and 60.5% immediately 5, 10 and 15 days after harvest respectively. Conclusion: The reduction in soil moisture content during the harvest stage, coupled with changes in hormonal activities, significantly impacts seed sprouting. These factors can lead to stress conditions that hinder germination, ultimately affecting crop yields. Addressing these issues is crucial for ensuring optimal seed development and enhancing agricultural productivity.

The CsTIE1-CsAGL16 module regulates lateral branch outgrowth and drought tolerance in cucumber

Abstract Drought stress and lateral branch are both important factors affecting crop yield. Cucumber is a widely planted vegetable crop that requires a large amount of water during its production and prefers varieties with few lateral branches. However, the mechanism regulating cucumber drought tolerance and lateral branch development remain largely unclear. The MADS-box transcription factor AGAMOUS-LIKE 16 (CsAGL16) was recently found to be a key positive regulator in cucumber shoot branching through stimulating ABA catabolism. In this study, we demonstrated that cucumber TCP interactor containing EAR motif protein 1 (CsTIE1) directly interacts with CsAGL16 at protein level and promotes lateral branch outgrowth through the CsAGL16-CsCYP707A4 mediated ABA pathway in cucumber. Additionally, mutation of CsAGL16 resulted in decreased drought tolerance, while overexpression of CsAGL16 significantly enhanced drought tolerance in cucumber. Similarly, the drought resistance of Cstie1 mutants was significantly reduced. However, overexpression of CsAGL16 can enhance the drought tolerance of Cstie1 mutants and promote their lateral branch outgrowth. These results indicated that the CsTIE1-CsAGL16 module was crucial for both lateral branch development and drought response, providing a strategy for cultivating drought tolerant cucumber varieties with appropriate branch outgrowth.

Sensing at Your Fingertip: On-Glove Electrochemical Sensor for Copper Detection on Vine Leaves

Intensive use of copper-based pesticides in agriculture can impact human health and biodiversity: the accumulation of this metal in soil negatively affects crop yields. There is growing interest in developing new tools that are capable of monitoring copper occurrence in agricultural contexts through the use of quick and user-friendly approaches for non-specialists, e.g., farmers. This work focuses on the development of a glove-based electrochemical sensor, enhanced with gold nanoparticles, for the detection of copper ions on leaves. The developed device proved was capable of detecting copper ions contained in a copper-based pesticide commonly used in agriculture (Cupravit Bio Advanced). The on-glove analytical device was characterized using garden leaf as the model system and subsequently applied to on-site detection of copper ions on vine leaf treated with Cupravit Bio Advanced. The procedure was very facile: sampling was carried out by touching the leaf with the strip and the stripping-voltammetric measurement was performed by adding a few microliters of an acidic solution to the strip. The on-glove approach allowed evaluation of the level of copper-based pesticide used, avoiding complex and time-consuming tasks. Such operation opens up a wide range of possibilities for improving precision agriculture and sustainable development at the point-of-need for the use of non-specialists.

Water deficit and aphid resilience on wheat: examining Sitobion avenae F. and their bacterial symbionts interplay under controlled laboratory conditions.

Climate change has far-reaching effects on food security and agriculture, affecting crop yields and food distribution. Agriculture relies heavily on water for irrigation and production, making it vulnerable to water scarcity. Additionally, climate change can affect crop pest insects, leading to increased global crop losses, particularly in cereals, an important component of the human diet. Aphids are major crop pests and have a symbiotic relationship with bacterial endosymbionts that can contribute to their success as pests under a climate change scenario. To test the effect of drought on aphids, we examined varying levels of water deficit and endosymbiont composition on the grain aphid (Sitobion avenae) performance on wheat under controlled laboratory conditions. We measured the intrinsic rate of population increase (rm), the body weight of adult aphids, and the pre-reproductive period for different genotypes of the grain aphid (including Chilean superclones) under different irrigation regimes. We also analyzed the relative abundance of their endosymbionts under the different water treatments. Our findings revealed that water deficit affects each aphid genotype differently, impacting various traits. For instance, the body weight of adult aphids was notably affected by different water treatments, with aphids grown under intermediate water deficit (IW) being significantly bigger. The relative abundance of endosymbionts also varied among genotypes and water treatments-specifically Regiella insecticola had a noticeably higher abundance under IW (P < 0.05). This study provides valuable insights into the impact of water deficit on aphid performance and the role of endosymbionts in mitigating the effects of water deficit. © 2024 Society of Chemical Industry.

Integrated Iot Approaches for Crop Recommendation and Yield-Prediction Using Machine-Learning

In this study, we present an integrated approach utilizing IoT data and machine learning models to enhance precision agriculture. We collected an extensive IoT secondary dataset from an online data repository, including environmental parameters such as temperature, humidity, and soil nutrient levels, from various sensors deployed in agricultural fields. This dataset, consisting of over 1 million data points, provided comprehensive insights into the environmental conditions affecting crop yield. The data were preprocessed and used to develop predictive models for crop yield and recommendations. Our evaluation shows that the LightGBM, Decision Tree, and Random Forest classifiers achieved high accuracy scores of 98.90%, 98.48%, and 99.31%, respectively. The IoT data collection enabled real-time monitoring and accurate data input, significantly improving the models’ performance. These findings demonstrate the potential of combining IoT and machine learning to optimize resource use and improve crop management in smart farming. Future work will focus on expanding the dataset to include more diverse environmental factors and exploring the integration of advanced deep learning techniques for even more accurate predictions.

Assessment of waterlogging hazard during maize growth stage in the Songliao plain based on daily scale SPEI and SMAI

Waterlogging is one of the major disasters affecting crop yield and food security. The Songliao Plain, located in the mid-latitude region and known as the "Golden Maize Belt," is severely impacted by waterlogging, which significantly affects maize yield. Therefore, it is essential to conduct a detailed assessment of the waterlogging hazard for maize in the Songliao Plain and to apply the results to agricultural meteorological disaster prevention and mitigation measures. In this study, a comprehensive waterlogging hazard assessment index was constructed by combining environmental factors conducive to disaster and disaster-causing factors. Environmental factors included terrain slope, distance from rivers, and soil clay content, while disaster-causing factors included daily SPEI and SMAI during the maize growing season in the Songliao Plain from 1982 to 2020. The results indicate that: (1) The spatial distribution of waterlogging hazard in the Songliao Plain ranges from extremely high to extremely low, showing a gradual decrease from west to east. The western and southern parts of the Songliao Plain, such as Baicheng, Songyuan, Changchun, and Fuxin, are more prone to waterlogging disasters. (2) During different maize growth stages, the spatial distribution of high and extremely high levels of waterlogging hazard exhibited significant heterogeneity. There were notable differences in the duration of waterlogging around the year 2000, with a reduction in the duration of extremely high and high levels of waterlogging after 2000. (3) A Pearson correlation analysis was conducted between the comprehensive waterlogging hazard index and SIF (Solar-Induced Fluorescence) data during different maize growth stages. The results showed a strong correlation between the comprehensive waterlogging hazard index and SIF data, with the highest correlation coefficient reaching −0.9 and a p-value less than 0.05. The comprehensive maize waterlogging hazard index can be used for precise and timely assessment of waterlogging hazard during different growth stages of maize, and it has a positive impact on improving the ability to prevent and mitigate waterlogging risks.

FINE CULM1 Encoding a TEOSINTE BRANCHED1-like TCP Transcription Factor Negatively Regulates Axillary Meristem Formation in Rice.

Shoot branching is a critical determinant of plant architecture and a key factor affecting crop yield. The shoot branching involves two main processes: axillary meristem formation and subsequent bud outgrowth. While considerable progress has been made in elucidating the genetic mechanisms underlying the latter process, our understanding of the former process remains limited. Rice FINE CULM1 (FC1), which is an ortholog of teosinte branched1 in maize (Zea mays) and BRANCHED1/2 in Arabidopsis (Arabidopsis thaliana), is known to act in the latter process by repressing bud outgrowth. In this study, we found that FC1 also plays a role in the former process, i.e. axillary meristem formation, in rice. This study was triggered by our unexpected observation that fc1 mutation suppresses the loss of axillary meristems in the loss-of-function mutant of the rice WUSCHEL gene TILLERS ABSENT1 (TAB1). In tab1 fc1, unlike in tab1, both stem cells and undifferentiated cells were maintained during axillary meristem formation, similar to the wild type. Morphological analysis showed that axillary meristem formation was accelerated in fc1, compared to the wild type. Consistent with this, cell proliferation was more active in the region containing stem cells and undifferentiated cells during axillary meristem formation in fc1 than in the wild type. Taken altogether, these findings suggest that FC1 negatively regulates axillary meristem formation by mildly repressing cell proliferation during this process.

Halving Environmental Impacts of Diverse Crop Production in Fujian, China through Optimized Nitrogen Management

Nitrogen (N) fertilizer is essential for agricultural production as it is the main nutrient driving crop growth. However, in China, only one-third of applied N fertilizer is effectively absorbed by crops, while the rest leads to significant environmental impacts. In this study, we introduced a nitrogen threshold boundary (NTB) approach to establish different thresholds for N use efficiency (NUE) and N surplus without affecting crop yield. We also developed an integrated assessment framework to systematically evaluate the potential for improving N utilization and reducing environmental impacts in the production of grain crops (rice, wheat, maize, and soybeans) and cash crops (tea, fruits, and vegetables) at the county level in Fujian Province. Three N management strategies were evaluated: a scenario with reduced N surplus (S1), a scenario with increased NUE (S2), and a combined scenario that simultaneously reduces N surplus and increases NUE (S3). The predictions indicate that, under the aforementioned scenarios, there will be a decrease of 66%, 58%, and 71% in N application without affecting crop yields, respectively. Correspondingly, N surplus will decrease by 65%, 56%, and 67%, while greenhouse gas (GHG) emissions will decrease by 54%, 48%, and 57%. In addition, NUE will increase by 23%, 17% and 25%, respectively. It is notable that scenario S3 demonstrated the greatest potential for improvement. For cash crops, N application will decrease by 65–78%, NUE will increase by 13–21%, N surplus will decrease by 63–74%, and GHG emissions will reduce by 66–78%. In contrast, for grain crops, N application will decrease by 27–38%, NUE will increase by 9–13%, N surplus will decrease by 26–37%, and GHG emissions will reduce by 24–28%. Overall, the potential for improvement is greater for cash crops compared to grain crops. The application of the assessment framework in this study demonstrates its effectiveness as a valuable tool for promoting green and sustainable development in conventional agricultural regions.

First Investigation of Secondary Metabolites from Aspergillus xerophilus Reveals Compounds with Inhibitive Effects against Three Phytopathogenic Fungi of Agrarian Crops.

Fungal secondary metabolites play a highly significant role in crop protection, which is related to their antifungal activity against agriculturally important phytopathogens. In fact, plant diseases caused by fungi including species belonging to the genera of Alternaria, Botrytis, and Fusarium have become increasingly serious affecting crop yield and quality. Hence, there is increasing awareness by the scientific community of the importance of exploiting fungal products for finding new compounds able to inhibit phytopathogens. In this study several drimane-type sesquiterpenes have been detected for the first time as products of Aspergillus xerophilus by GC-MS analysis of the organic extracts obtained from the mycelia and culture filtrates of the fungus grown on two different substrates. Seven pure drimane-type sesquiterpenes were also isolated and identified by spectroscopic methods. The inhibitory effects of the pure compounds have been investigated against three phytopathogenic fungi of agrarian crops (i.e., Botrytis cinerea, Alternaria alternata, and Fusarium oxysporum f. sp. pisi). Among the drimane-type sesquiterpenes isolated in this study, 9,11-dihydroxy-6-oxodrim-7-ene is the most active against the three phytopathogens. Our findings also reveal the high sensitivity of A. alternata to the isolated compounds. These results pave the way for future applications in agriculture of both A. xerophilus and its metabolites.

Language Barriers, Technology Adoption and Productivity: Evidence from Agriculture in India

Abstract We study the effect of language barriers on the ability of farmers to access information about agricultural technologies in rural areas of India. We use the introduction of government-sponsored call centers (Kisan Call Centers) which offer agricultural advice in the official language of each Indian state. For identification, we compare geographically contiguous areas that sit across state borders, and exploit differences in the language spoken by farmers and call center advisors. We document that language barriers limit the adoption of modern agricultural technologies – such as high-yielding variety seeds – and negatively affect crop yields.

Molecular Regulation of Shoot Architecture in Soybean.

Soybean (Glycine max [L.] Merr.) serves as a major source of protein and oil for humans and animals. Shoot architecture, the spatial arrangement of a plant's above-ground organs, strongly affects crop yield and is therefore a critical agronomic trait. Unlike wheat and rice crops that have greatly benefitted from the Green Revolution, soybean yield has not changed significantly in the past six decades owing to its unique shoot architecture. Soybean is a pod-bearing crop with pods adhered to the nodes, and variation in shoot architecture traits, such as plant height, node number, branch number and number of seeds per pod, directly affects the number of pods and seeds per plant, thereby determining yield. In this review, we summarize the relationship between soybean yield and these major components of shoot architecture. We also describe the latest advances in identifying the genes and molecular mechanisms underlying soybean shoot architecture and discuss possible directions and approaches for breeding new soybean varieties with ideal shoot architecture and improved yield.