Agricultural Practices Research Articles

Characterization of Sprayer Rinsing Water in Rice Plots in the Yamoussoukro Region, Ivory Coast

The intensive use of pesticides in modern agriculture poses significant risks to the environment and human health. Sprayer rinsate is often overlooked as a potential source of contamination of soil and water resources. The objective of this study is to evaluate the total pesticide load in rinse water samples. Sprayer rinsate samples were collected and analyzed to determine the concentrations of different pesticides. The targeted substances included glyphosate, atrazine, 2, 4-D, chlorpyrifos, imidacloprid, mancozeb, and tebuconazole, among others. Total pesticide burden was also measured to assess variation between samples. Data were interpreted based on agricultural practices and flushing techniques. The results show high concentrations of some pesticides, including glyphosate (20 mg/L), chlorpyrifos (2.4 mg/L), and mancozeb (12 mg/L). Total pesticide load varies significantly, ranging from 20 mg/L to 100 mg/L, reflecting differences in agricultural practices and flushing effectiveness. In addition, herbicides were the most predominant, followed by fungicides and insecticides. These results highlight the environmental and health risks associated with the presence of these substances in rinsing waters. Hence, it’s processing by photochemical.

Integration of UAV Multispectral Remote Sensing and Random Forest for Full-Growth Stage Monitoring of Wheat Dynamics

Wheat is a key staple crop globally, essential for food security and sustainable agricultural development. The results of this study highlight how innovative monitoring techniques, such as UAV-based multispectral imaging, can significantly improve agricultural practices by providing precise, real-time data on crop growth. This study utilized unmanned aerial vehicle (UAV)-based remote sensing technology at the wheat experimental field of the Hebei Academy of Agriculture and Forestry Sciences to capture the dynamic growth characteristics of wheat using multispectral data, aiming to explore efficient and precise monitoring and management strategies for wheat. A UAV equipped with multispectral sensors was employed to collect high-resolution imagery at five critical growth stages of wheat: tillering, jointing, booting, flowering, and ripening. The data covered four key spectral bands: green (560 nm), red (650 nm), red-edge (730 nm), and near-infrared (840 nm). Combined with ground-truth measurements, such as chlorophyll content and plant height, 21 vegetation indices were analyzed for their nonlinear relationships with wheat growth parameters. Statistical analyses, including Pearson’s correlation and stepwise regression, were used to identify the most effective indices for monitoring wheat growth. The Normalized Difference Red-Edge Index (NDRE) and the Triangular Vegetation Index (TVI) were selected based on their superior performance in predicting wheat growth parameters, as demonstrated by their high correlation coefficients and predictive accuracy. A random forest model was developed to comprehensively evaluate the application potential of multispectral data in wheat growth monitoring. The results demonstrated that the NDRE and TVI indices were the most effective indices for monitoring wheat growth. The random forest model exhibited superior predictive accuracy, with a mean squared error (MSE) significantly lower than that of traditional regression models, particularly during the flowering and ripening stages, where the prediction error for plant height was less than 1.01 cm. Furthermore, dynamic analyses of UAV imagery effectively identified abnormal field areas, such as regions experiencing water stress or disease, providing a scientific basis for precision agricultural interventions. This study highlights the potential of UAV-based remote sensing technology in monitoring wheat growth, addressing the research gap in systematic full-cycle analysis of wheat. It also offers a novel technological pathway for optimizing agricultural resource management and improving crop yields. These findings are expected to advance intelligent agricultural production and accelerate the implementation of precision agriculture.

Rice yield predictions using remote sensing and machine learning algorithms: A review

Crop yield prediction is becoming increasingly crucial due to global food security concerns, as highlighted by recent reports from the World Health Organization. Accurate early predictions can mitigate famine risks by estimating food supply, which is essential for 820 million people facing hunger globally. Rice is the primary staple food consumed worldwide; therefore, global rice yield and rice area are monitored using emerging technologies such as remote sensing (RS) and machine learning (ML). These technologies provide valuable tools for enhancing rice yield predictions. RS includes critical information on crop health, soil conditions and weather patterns. In contrast, ML algorithms analyze these datasets to identify patterns and relationships that affect yield. Integrating these technologies offers promising improvements in yield forecasting accuracy, with applications showing successful yield predictions 1-3 months before harvest. Various ML techniques, including Random Forest, Support Vector Machines and deep learning models such as LSTM (Long-Short Term Memory), have been employed, often in combination with RS data. However, these models face challenges, such as data quality, managing high-dimensional RS data and accounting for spatial and temporal variability. Despite these challenges, integrating RS and ML has significant potential for advancing precision agriculture and achieving sustainable food production. This study explores the advancements, practical applications and challenges associated with using RS and ML for rice yield prediction, emphasizing the importance of these technologies in addressing global food security and promoting sustainable agricultural practices.

Impact of Manures, Fertilizers, and Rice Straw Allelopathy on T. aman Rice Yield

Nowadays, adopting agricultural practices that are sustainable and eco-friendly for crop production is a major concern. The present experiment was conducted at the AFLAB of BAU from June 2022 to November 2022 to estimate the combined effect of manures and fertilizers with rice straw allelopathy on the yield performance of transplant aman rice. The experiment consisted of two cultivars i.e.: BRRI dhan71 (V1) and BRRI dhan49 (V2) and eight treatments of the combination of rice straw, manures, and fertilizers such as Control (T1), Recommended doses of NPKS (T2), Rice straw @ 1.5 t ha-1 + Cow dung @ 5 t ha-1 (T3), Rice straw @ 1.5 t ha-1 + Cow dung @ 2.5 t ha-1 + 50% less of recommended doses of NPKS (T4 ), Rice straw @ 1.5 t ha-1 + Vermicompost @ 5 t ha-1 (T5) , Rice straw @ 1.5 t ha-1 + Vermicompost @ 2.5 t ha-1 + 50% less of recommended doses of NPKS (T6), Rice straw @ 1.5 t ha-1 + Trichocompost @ 10 t ha-1 (T7), Rice straw @ 1.5 t ha-1 + Trichocompost @ 5 t ha-1 + 50% less of recommended doses of NPKS (T8). The grain yield as well as the yield contributing characters such as the number of effective tillers hill-1, number of grains panicle-1, 1000-grain weight was highest at BRRI dhan71 with Rice straw @ 1.5 t ha-1 + Vermicompost @ 2.5 t ha-1 + 50% less of recommended doses of NPKS (T6) treatment, followed by Rice straw @ 1.5 t ha-1 + Trichocompost @ 10 t ha-1 (T7) treatment. BRRI dhan71 expressed superiority at yield and all the yield contributing characters than BRRI dhan49. This current study's results indicate that combining rice straw with manures and fertilizer could enhance the yield of transplant aman rice. As a result, mixing rice straws with manures and fertilizers could be a viable bundle of sustainable and eco-friendly ways for increasing crop productivity in the future.

The Role of Soil Microbiome in Enhancing Plant Nutrition and Promoting Soil Health

The soil microbiome, a complex community of microorganisms including bacteria, fungi, archaea, and protozoa, plays a pivotal role in sustaining plant nutrition and soil health. Through processes such as nutrient cycling, organic matter decomposition, and symbiotic relationships, soil microorganisms enhance the availability of essential nutrients like nitrogen, phosphorus, and potassium. Beneficial microbes such as plant growth-promoting rhizobacteria (PGPR) and mycorrhizal fungi improve plant growth by increasing nutrient uptake, producing growth hormones, and promoting disease resistance. Furthermore, the soil microbiome significantly contributes to soil structure, fertility, and resilience by aiding in soil aggregation, water retention, and stress tolerance. It also plays a critical role in suppressing plant pathogens and improving plant resilience to environmental stresses such as drought and heavy metal contamination. Despite its importance, conventional agricultural practices, including the overuse of chemical inputs and intensive tillage, often disrupt the balance of soil microbial communities, leading to soil degradation. Sustainable agricultural practices that incorporate organic amendments, crop rotations, and reduced chemical inputs are crucial for maintaining a healthy and diverse soil microbiome. This review highlights the essential functions of the soil microbiome in plant nutrition and soil health, emphasizing its potential to promote sustainable agricultural practices and ecosystem resilience.

Sustainable Livelihood Options Adopted by Rural Communities in Response to Climate Change Dynamics: A Case Study Approach in Vhembe District, South Africa

The Vhembe district of South Africa is dominantly rural, with agricultural practice being the main major livelihood activity. Furthermore, many of the rural subsistence farmers rely on rain-fed agriculture, making them highly vulnerable to climate change, particularly high temperatures. Changes in climate cause extreme losses in agricultural productivity, increasing the level of vulnerability among rural subsistence farmers. The study examines the livelihood options adopted by rural communities in response to climate change dynamics in the Vhembe district. Using qualitative and quantitative approaches, both primary and secondary data from 365 rural community members were employed. Questionnaires and semi-structured interviews were administered using purposive sampling and employed statistical analysis techniques. The results revealed that livestock production was the most dominant livelihood-resilient activity at 30%, while vendor activity is common in Ṱhohoyanḓou at 29%. The findings indicated that the highest establishment of water tanks was in the Madimbo area, with 51% as a form of livelihood resilience. Further, 70% of respondents demonstrated livelihood sustainability activities such as agricultural forums, conferences, and the practice of indigenous activities. The proposed strategies can be used by policymakers to effectively consider the most vulnerable groups and articulate unique local vulnerabilities.

Phenobot: An Autodigital Modeling System for in situ Phenotyping in Horticulture

Accurate reconstruction of plant models for phenotyping analysis is critical for optimizing sustainable agricultural practices in precision agriculture. Traditional laboratory‐based phenotyping, while valuable, falls short of understanding how plants grow under uncontrolled conditions. Robotic technologies offer a promising avenue for large‐scale, direct phenotyping in real‐world environments. This study explores the deployment of emerging robotics and digital technology in plant phenotyping to improve performance and efficiency. Three critical functional modules, environmental understanding, robotic motion planning, and in situ phenotyping, are introduced to automate the entire process. Results demonstrate the effectiveness of the system in agricultural environments. The phenorobot system autonomously collects high‐quality data by navigating around plants. In addition, the in situ modeling model reconstructs high‐quality plant models from the data collected by the robot. The developed robotic system shows high efficiency and robustness, demonstrating its potential to advance plant science in real‐world agricultural environments.

Assessing the Technical Efficiency of Rice Producers in the Parsa District of Nepal

Rice is one of the primary staple foods in Nepal, and there has been a notable increase in the production of this crop over the past ten years. Nonetheless, there appears to be a growing tendency to import rice. The plain region (Terai) of Nepal produces more than two-thirds of the country’s total rice output, with the highest productivity found in Madhesh Province. However, because of the limited knowledge regarding the technical aspects of rice production, commercial rice growers are facing challenges in using resources to produce output as effectively as possible. There is a pressing need to maximize production based on a limited number of inputs. Thus, this study aimed to examine the technical efficiency of rice farmers and the factors affecting technical inefficiency in the Parsa district of Nepal. This study area is the major domain of the Prime Minister Agriculture Modernization Project (PMAMP), which supports farmers with necessary agricultural inputs, infrastructure development, and innovative practices. Data were collected from 215 rice farmers using multistage purposive sampling and were subjected to a Cobb–Douglas stochastic frontier production function. The results showed that rice producers had a technical efficiency of 0.862. Age and off-farm activities were found to significantly influence the technical efficiency of rice farmers. The technical efficiency of rice producers could be enhanced using a project approach, such as the PMAMP. It is important for the government to implement innovations and technologies in farms with the participation of older farmers because their ability to adapt to novel techniques and technologies is better than that of young farmers. Youth generally prefer off-farm employment opportunities, so domestic investment in agriculture should be promoted to make this sector more appealing. Further, policies and programs focusing on pooling small rice fields and subsidizing the price of tractors will help improve the yield of rice.

Inheritance of Northern Corn Leaf Blight Resistance in Advanced Generations of Maize (Zea mays L.)

Developing genetically resistant maize varieties to mitigate yield losses would reduce reliance on chemical control measures. This study underlines the substantial genetic variability and heritability of northern corn leaf blight (NCLB) resistance within a recombinant inbred line (RIL) population, highlighting the genetic basis of the trait. ANOVA revealed highly significant genetic variability among families at the 1% level, confirming the presence of sufficient variability for effective selection. The progression from F5 to F6 generations demonstrated the effectiveness of selection, as seen from reduced AUDPC scores in the F6 generation. A genetic gain of -7.74 and a heritability estimate of 48% further validated the success of selection based on lower AUDPC scores. The regression analysis supported by the significant positive correlation (r = 0.65) revealed a significant association between F5 selections and the F6 AUDPC scores, as seen from an R2 value of 0.42 and a moderate predictive slope of 0.52. These associations suggest that while selection is effective in predicting advanced-generation performance, the residual variability points to the need for incorporating additional genetic or environmental factors to improve predictive accuracy. These findings emphasize the predominance of genetic factors in NCLB resistance and the stability of resistance traits across the two generations, offering insights into the genetic control of the trait. By providing a solid foundation for breeding efforts targeting durable resistance, this study contributes to the development of maize varieties with enhanced NCLB resistance and supports sustainable agricultural practices.

Properties of Soils of Medak District in Telangana State, India

For the management of soil and plant growth the physicochemical study of parameters are crucial.The objective of this study is to do the physical and chemical analysis of soil samples collected from agricultural fields of Medak district and to provide information to the farmers. Soil samples collected from twenty mandals at three samples per mandal from 0-15 cm depth. Soil parameters like soil texture, pH, EC, organic carbon available nitrogen, phosphorus, potassium and Sulphur tested and recorded. Results shows texture varies from sandy clay loam to sandy loam. pH shows slightly acidic, neutral to slightly alkaline. Electric conductivity remains within the safe limits. The organic carbon recorded maximum low to medium in content, low in nitrogen content, medium to high range in phosphorous, potassium. The available sulphur recorded deficient to sufficient values. The findings suggest that farmers should adopt appropriate soil management techniques, such as crop rotation and conservation tillage which will add to maintain the soil physical characteristics to ensure the sustainability of agricultural practices and the long-term health of the soil.

Enhancing multi-season wheat yield through plant growth-promoting rhizobacteria using consortium and individual isolate applications.

In recent decades, there has been a growing interest in harnessing plant growth-promoting rhizobacteria (PGPR) as a possible mechanism to mitigate the environmental impact of conventional agricultural practices and promote sustainable agricultural production. This study investigated the transferability of promising PGPR research from maize to another Poaceae cereal crop, wheat. This multi-seasonal study evaluated the wheat grain yield effect of Lysinibacillus sphaericus (T19), Paenibacillus alvei (T29) when applied i. individually, ii. as a consortium with Bacillus safensis (S7), and iii. at a 75% reduced fertilizer rate. Whole genome sequencing allowed annotation of genes linked to plant growth promotion, providing potential genomic explanations for the observed in-field findings. Application of the consortium compared to a commercial PGPR showed significantly increased wheat yield by 30.71%, and 25.03%, respectively, in season one, and 63.92% and 58.45%, respectively, under reduced fertilizer rates in season two. Individual application of T19 and T29 showed varying results, with T19 increasing wheat yield by 9.33% and 16.22% during seasons three and four but a substantial reduction (33.39%) during season five. T29 exhibited yield increases during season three (9.31%) and five (5.61%) but led to a significant reduction (21.15%) in season four. Genomic analysis unveiled a spectrum of plant growth-promoting genes including those associated with ammonification, phosphate solubilization, ethylene, siderophore, catalase, and superoxide dismutase production. These findings offer valuable insights into the mechanisms behind observed field results, with potential implications for advancing sustainable agriculture and crop productivity in evolving agricultural landscapes.

Effects of nitrogen fertilizer basal-to-top-dressing ratios on maize straw decomposition, soil carbon and nitrogen, and bacterial community structure in different soil textures on the north china plain

Straw return is a recognized agricultural practice that improves soil quality, reduces reliance on chemical fertilizers, and supports sustainable agriculture. Its effectiveness is influenced by microbial changes under varying soil properties and fertilization practices. In a wheat–maize rotation system, field experiments were conducted over 2 years in loam and clay loam soils with five fertilizer (N) application treatments (i.e., no N fertilizer (N0) and N fertilizer basal-to-top-dressing ratios of 3:7 (N3:7), 4:6 (N4:6), 5:5 (N5:5), and 6:4 (N6:4)) to investigate the dynamics of maize straw decomposition, changes in soil organic carbon (SOC) and total nitrogen (TN) concentrations, soil bacterial diversity and abundance, and their interactions. Our results showed that the optimization of N fertilizer basal-to-top-dressing ratios enhanced SOC and TN by accelerating maize straw decomposition and nutrient release, as well as increasing plant carbon and nitrogen inputs. At the wheat maturity stage, the decomposition rate of maize straw reached 69.48–75.04%. The N4:6 and N5:5 ratios exhibited higher decomposition rates and C and N release rates in both soil textures. Compared to N0, N application treatments increased SOC and TN concentrations by 7.90–14.17% and 7.94–33.60%, respectively. The effects were most pronounced with the N4:6 ratio in loam and the N5:5 ratio in clay loam. Both soil textures had the same dominant bacterial phyla, but species abundance differed significantly. Loam had a significantly higher relative abundance of Proteobacteria and lower relative abundances of Gemmatimonadetes, Actinobacteria, and Chloroflexi than clay loam. N application significantly influenced bacterial diversity, with higher diversity observed with the N4:6 ratio in loam and the N5:5 ratio in clay loam. Structural equation modeling indicated that different N application treatments in loam influenced maize straw decomposition by altering the soil C/N ratio and bacterial community diversity, while in clay loam, N application treatments influenced maize straw decomposition mainly by altering the soil C/N ratio. Overall, the N4:6 treatment in loam and the N5:5 treatment in clay loam accelerated the decomposition and nutrient release of maize straw, enhanced SOC, TN, and bacterial community abundance, and provided a scientific basis for efficient straw utilization and sustainable agricultural development in the North China Plain region.

Construction of a CRISPR-Cas9-Based Genetic Editing Tool for Serratia marcescens Using a Stationary Phase Promoter and Its Application in Putrescine Production.

Putrescine plays a significant role in green food production and agriculture by promoting plant growth and enhancing crop quality. Its application reduces the reliance on chemical fertilizers and pesticides, thereby supporting the advancement of sustainable agricultural practices. This study achieved efficient production of putrescine in Serratia marcescens. S. marcescens has been extensively used to synthesize antimicrobial substances and express proteins, but its application has been limited by the lack of efficient genome-editing tools. This study presents a CRISPR-Cas9-based tool for gene editing in S. marcescens. A dual-plasmid system was constructed, incorporating an editing template into the plasmid pEdit with target-specific sgRNA. A stationary phase promoter was used to express Cas9 from Streptococcus pyogenes protein, avoiding the need for additional inducers and ensuring efficient one-step gene knockout and integration. The tool demonstrated over 80% editing efficiency across various S. marcescens strains and enabled successful single-base mutations. Using this tool, we enhanced putrescine production in S. marcescens HBQA7, optimizing the expression of ornithine decarboxylase from Clostridium aceticum DSM1496 with the P2 promoter and identifying the optimal integration site. Putrescine production reached 8.46 g/L within 48 h. This study significantly advances S. marcescens gene editing and metabolic engineering.

Agriculture Equipment's Rental System - Agri Rent

The agricultural sector faces numerous challenges, particularly for smallholder farmers who often struggle with limited access to the tools and equipment necessary for efficient farming. The high costs associated with purchasing and maintaining modern farming machinery can be prohibitive, hindering productivity and the adoption of advanced agricultural practices. This gap in accessibility not only affects individual farmers but also impacts the broader agricultural ecosystem, contributing to lower yields, inefficiencies, and ultimately, food insecurity. Agri Rent is a groundbreaking solution designed to address these challenges by democratizing access to agricultural tools and equipment. The platform functions as an online marketplace where farmers can rent essential farming machinery and tools on a short-term or long-term basis. By offering a flexible, cost-effective alternative to ownership, Agri Rent empowers farmers to utilize modern equipment without the financial strain of purchasing and maintaining these assets. The platform is user-friendly, with a simple interface that allows farmers to search for, compare, and book equipment that suits their specific needs. Agri Rent connects tool owners, such as larger farms or equipment suppliers, with farmers who need access to these resources. This model fosters a collaborative economy, where resources are shared more efficiently, reducing idle time for equipment and maximizing their usage. The platform also incorporates features that ensure the safety and reliability of transactions. Reviews, ratings, and a secure payment system build trust among users, while a robust customer support team is available to assist with any issues that arise. Agri Rent is continuously evolving, with plans to integrate advanced technologies such as IoT-based equipment tracking and AI driven recommendations to further enhance the user experience. In conclusion, Agri Rent represents a significant step forward in the effort to modernize agriculture, particularly for smallholder farmers. By providing affordable and convenient access to essential tools and equipment.

Assessment of the Effectiveness of Vermicomposts Derived from Agri-Food Sector Waste in Wheat Cultivation (Triticum aestivum L.)

Purpose of the study: The study aimed to evaluate the effectiveness of vermicomposts derived from agri-food sector waste in wheat cultivation (Triticum aestivum L.). The research focused on the impact of various types of vermicompost on plant growth, development, yield, and root system structure. Methodology: The research was conducted under controlled laboratory conditions. Vermicomposts were obtained through the biological processing of organic waste using earthworms (Dendrobaena veneta). The experiment involved six substrate variants with varying proportions of garden soil, rapeseed meal (DMRE), and cattle manure (DCE). The effectiveness of the substrates was assessed based on wheat germination rates, biomass, and root system development. Main findings: Vermicomposts enriched with cattle manure, particularly at a 25% DMRE proportion, provided the best conditions for wheat growth, enhancing germination rates, biomass, and root system development. Pure rapeseed meal (DMRE) was the least effective, highlighting its limited utility as a standalone fertilizer. The results suggest that moderate use of vermicomposts combined with cattle manure benefits yield and plant health. Application of the study: The findings can be applied in agricultural practices to develop effective wheat fertilization strategies while ensuring sustainable organic waste management. The use of vermicomposts may increase agrarian production efficiency and promote sustainable farming. Originality/Novelty of the study: This study contributes significantly to research on using vermicomposts derived from agri-food waste as eco-friendly and efficient fertilizers, offering innovative solutions for sustainable wheat production.

The Role of Soil Health in Enhancing Agricultural Profitability: An Economic Perspective

This paper also demonstrates that the health of the soil is central to improving the profitability of agricultural enterprises in economic terms. Hence, sustainable agriculture practices like conservation tillage and other compatible practices, organic farming and more techniques like vermicomposting and biochar application etc. have become inevitable in the Indian Scenario for maintaining resilience of the soil and for enhancing productivity. Out of the Government of India’s Soil Health Card launched in 2015, one can see how the use of soil test-based fertilizers is greatly encouraged, improving further the profitability of agriculture. Such as in Andhra Pradesh, evaluating various aspects of the enhanced method of monitoring of soil health and its parameters reveals promising results which have a positive impact on the state’s agriculture and farmers. A study identifies reduction in minimum soil tillage, retention of crop residue, and differential nitrogen replacement on the yield and profitability of crops. Moreover, initiatives like Agrivoltaics have started to surface in the effective management of Climate Smart Agriculture in diverse climates and uncertain monsoons. Signing legislation and applying the concepts of the market incentive affect the improvement of the soil quality for the enhancement of sustainable agricultural production and income. When such practices are adopted, the Indian farmers and the country in general will be in a better position to improve fertility of the soils, increasing crop yields and equally resulting to better positioned economic stability to the backbone of the economy the agricultural industry.

Application of omics technology in ecotoxicology of arthropod in farmland

Abstract Arthropods, abundant in farmland, have unique biological traits that make them valuable for studying the ecotoxicological impacts of pollutants. Recent advancements in multi-omics technologies have enhanced their use in assessing pollution risks and understanding toxicity mechanisms. This paper reviews recent developments in applying omics technologies—genomics, transcriptomics, proteomics, metabolomics and meta-omics to ecotoxicological research on farmland arthropods. Agricultural arthropods manage genes and proteins like metallothioneins (MTs), antioxidant enzyme systems, heat shock proteins, cytochrome P450 (CYP450), carboxylesterases (CarEs), and glutathione S-transferases (GSTs), for detoxification and antioxidant purposes. They adjust amino acid, sugar, and lipid metabolism to counteract pollutant-induced energy drain and modify gut microbiota to aid in detoxification. This study advocates for enhanced analysis of compound pollution and emerging pollutants using multi-omics, especially meta-omics, to clarify the toxicological mechanisms underlying arthropod responses to these pollutants. Furthermore, it underscores the urgent need for subsequent gene function mining and validation to support biological control strategies and promote sustainable agricultural practices. The findings of this research provide significant insights into the toxicological impacts and mechanisms of pollutants within farmland ecosystems, thereby contributing to the preservation of arthropod diversity.

Integrating Artificial Intelligence in agricultural higher education: Transforming learning and research

The integration of Artificial Intelligence (AI) in agricultural higher education is transforming the landscape of agricultural practices and research. This paper explores the multifaceted applications of AI technologies in the curriculum and pedagogical approaches of agricultural institutions. By enhancing data analysis, predictive modeling, and decision-making processes, AI empowers students and researchers to tackle complex agricultural challenges such as crop management, pest control, and resource optimization. Furthermore, the study examines the implications of AI on student engagement, skill development, and interdisciplinary collaboration. As agricultural sectors increasingly rely on data-driven solutions, the incorporation of AI in higher education not only prepares future professionals with essential competencies but also fosters innovation in sustainable agricultural practices. This article underscores the critical role of AI in shaping the future of agricultural education and its potential to revolutionize the industry.

Responses of a soil-inhabiting collembolan (Entomobrya proxima Folsom) to organic fertilizer addition illustrated by functional traits and gut bacterial community

IntroductionOrganic fertilizer offers significant advantages for sustainable agricultural development compared to inorganic fertilizers and is increasingly becoming the predominant fertilizer strategy. Functional traits and gut microbiota of soil fauna are recognized as potential indicators of environmental changes. However, there is a dearth of research examining the correlation between functional traits and intestinal microorganisms in response to organic fertilizer.MethodsIn this study, we selected Entomobrya proxima Folsom, a predominant soil collembolan species found in cropland across North China, as our subject of study. We set treatments with no organic fertilizer (CK) and three different concentrations of organic fertilizer at 1% (O1), 6% (O2), and 10% (O3). Stereomicroscopy and high-throughput amplicon sequencing were employed to elucidate the response of soil fauna to organic fertilizer through host functional traits and associated gut microbial communities.ResultsThe results indicated that the impact of organic fertilizer on the functional traits of collembolans was closely linked to the input concentration. Specifically, low input concentrations positively influenced all functional traits of Entomobrya proxima Folsom; conversely, higher input concentrations exerted an overall detrimental effect. For the gut bacterial community, the addition of organic fertilizer resulted in a significant decrease in abundance, adversely affected α-diversity, and significantly altered the structure of the gut bacterial community compared to CK. However, there was no significant effect of fertilizer concentration on these three parameters. The composition of the gut bacterial community varied due to the addition of organic fertilizer, with significant changes observed in the relative abundances of six phyla and three genera. Furthermore, body length and foreleg length may serve as potential indicators for characterizing the proportions of Alcanivorax and Sphingobacterium of gut bacterial community. Additionally, the assembly process of the gut bacterial community was strongly influenced by the amount of organic fertilizer added; this led to a narrowing niche width that is believed to contribute to an increase in species richness.DiscussionIn conclusion, adding organic fertilizer exerted multiple impacts on soil fauna, with effect sizes related to its concentration. These findings provide insights for conserving soil animals while maximizing their ecological functions and offer perspectives on optimizing sustainable agricultural management practices.

Herbicide resistance in Leptochloa chinensis (L.) Nees populations from different regions of Jiangsu Province, China: sensitivity differences and underlying mechanisms

Leptochloa chinensis (L.) Nees, a noxious weed species commonly found in rice fields, has become a significant challenge in Jiangsu Province, China, as it has developed resistance to multiple herbicides due to extensive and continuous herbicide use in recent years. Therefore, this study was conducted to elucidate sensitivity differences and the mechanisms underlying the resistance of L. chinensis (L.) Nees populations to commonly used herbicides across different regions of Jiangsu Province, China. A whole-plant bioassay was used to assess the sensitivity of 46 L. chinensis populations collected from various areas within Jiangsu to several herbicides frequently applied in paddy fields, including: cyhalofop-butyl, fenoxaprop-P-ethyl, pyraclonil, benzobicyclon, anilofos, and oxaziclomefone. After treatment with cyhalofop-butyl, 38 out of 46 populations showed relative resistance-index values that were over four times that of the controls, indicating significant resistance to cyhalofop-butyl. All 41 cyhalofop-butyl-resistant populations showed cross-resistance to fenoxaprop-P-ethyl but remained susceptible to pyraclonil, benzobicyclon, anilofos, and oxaziclomefone. The proportion of populations resistant to acetyl-CoA carboxylase (ACCase)-inhibiting herbicides increased progressively from the south to the north of Jiangsu. Cross-resistance was evident between cyhalofop-butyl and fenoxaprop-P-ethyl; however, all resistant populations were susceptible to pyraclonil, benzobicyclon, anilofos, and oxaziclomefone. Furthermore, mutations in the ACCase gene were identified as a crucial mechanism for cyhalofop-butyl resistance. Specifically, we found ACCase mutations I1781L, W1999C, W2027C/L/S, I2041N, and D2078G in cyhalofop-butyl-resistant L. chinensis populations, among which, W1999C and W2027C accounted for a relatively high proportion, while I1781L, W2027L/S, I2041N, and D2078G were found in one population each. ACCase gene mutations are seemingly a key mechanism for the development of resistance to cyhalofop-butyl, thus, our study provides useful information for developing effective weed-management strategies for controlling this noxious weed species, while ensuring sustainable agricultural practices.