Upcycling trace amounts of biomass waste into flash graphene can boost crop yields by more than a quarter and offer climate benefits

Excessive N loading from subsurface tile drainage has been linked to water quality degradation. Controlled tile drainage (CTD) has the potential to reduce N losses via tile drainage and boost crop yields. While CTD can reduce N loss from tile drainage, it may increase losses through other pathways. A multiple-year field-scale accounting of major N inputs and outputs during the cropping season was conducted on freely drained and controlled tile drained agricultural fields under corn ( L.)-soybean [ (L.) Merr.] production systems in eastern Ontario, Canada. Greater predicted gaseous N emissions for corn and soybean and greater observed lateral seepage N losses were observed for corn and soybean fields under CTD relative to free-draining fields. However, observed N losses from tile were significantly lower for CTD fields, in relation to freely drained fields. Changes in residual soil N were essentially equivalent between drainage treatments, while mass balance residual terms were systematically negative (slightly more so for CTD). Increases in plant N uptake associated with CTD were observed, probably resulting in higher grain yields for corn and soybean. This study illustrates the benefits of CTD in decreasing subsurface tile drainage N losses and boosting crop yields, while demonstrating the potential for CTD to increase N losses via other pathways related to gaseous emissions and groundwater seepage.

Background and Aims Cotton-peanut rotation is a sustainable farming practice that enhances land utilization and promotes the sustainable development of agriculture. Crop rotation can reduce the occurrence of pests and diseases, as different crops have varying levels of resistance to such threats. Additionally, by alternating the types of crops grown, the soil environment is changed, which can lead to the elimination of favorable conditions for pathogens and pests, thereby alleviating the impact of these issues. Furthermore, cotton-peanut rotation can improve soil fertility.To investigate the effects of different crop rotation systems on crop yield, soil nutrients, and soil microbial communities. Methods: Using high-throughput sequencing technology, investigate the soil microbial diversity in the root zone after cotton-peanut rotation.Various planting patterns, including cotton continuous cropping (MC), peanut continuous cropping (HC), peanut-cotton-peanut rotation (HR), and fallow (X), were established to assess variations in crop yield, soil nutrients, and soil microbial diversity. Results: Significant differences were observed in crop yield, soil nutrients, and soil microbial community structure among different planting patterns. The HR system significantly increased the output compared with the HC and MC systems. Additionally, HR exhibited significantly lower total nitrogen (N) and basic nitrogen (BN) contents than HC and MC, whereas MC showed lower total potassium (K) and available potassium (AK) contents. HR led to a decrease in soil bacterial diversity but an increase in fungal diversity, with Ascomycota and Mortierellomycota being dominant. Various bacteria (Chloroflexi, Bacteroidota, and Actinobacteriota) associated with organic matter degradation and nutrient cycling were found across different planting systems, enhancing material cycling efficiency. Furthermore, Planctomycetota bacteria related to crop nutrient synthesis and Glomeromycota bacteria aiding plant nutrient absorption were significantly higher in the MC system than in the HR or HC systems. Redundancy analysis indicated a significant negative correlation between crop rotation and soil fungal community, whereas Ascomycota exhibited a significant negative correlation with organic matter.Conclusion: Peanut-cotton rotation can mitigate soil nutrient loss, enhance beneficial microorganism diversity, suppress harmful bacterial populations, stabilize ecosystems, and boost crop yield.

Land-use change is one of the main indicators of soil quality. Soil physical and chemical properties vary with land use change and altitude as inferred from transect surveys and toposequences. Soil nitrogen, phosphorus, and potassium (NPK) are essential macronutrients for plant growth and soil nutrient balance. Their presence in the soil in appropriate quantities is important for maintaining crop yields and farmers income, particularly in developing countries where resources of soil chemical additives may be limited. This paper assesses the effects of land cover/use change and altitude on soil NPK nutrients in plots of 30 m2 in the North West Region of Cameroon for maintaining soil NPK levels and boosting crop yields. A total of 60 soil samples were collected at the 0-20 cm depth from the plots with various land cover/use types (eucalyptus plantation, farmland, grazing land, and natural forest). Soil samples were analyzed for nitrogen (N), phosphorus (P), and potassium (K) contents based on standard procedures. The concentrations of soil NPK nutrients were below the critical values for different land use types and the studied sites. The decline in soil NPK nutrient contents is partly linked to land use change, long-term nutrient mining through crop harvest, and rainfall-induced leaching of N and K nutrients. To increase food crop yields and sustain the livelihood of farmers, appropriate nature-based solutions of manure application, mulching, the intercropping of legumes, and sustainable use of appropriate chemical NPK fertilizers will help restore the soils and increase crop yields.

Crop yield prediction before harvest is a key issue in managing agricultural policies and making the best decisions for the future. Using remote sensing techniques in yield estimation studies is one of the important steps for many countries to reach their agricultural targets. However, crop yield estimates rely on labor-intensive surveys in Ethiopia. To solve this, we used Sentinel-2, crop canopy analyzer, and ground-truthing data to estimate grain yield (GY) and aboveground biomass (AGB) of two major crops, teff and finger millet, in 2020 and 2021 in Ethiopia’s Aba Gerima catchment. We performed a supervised classification of October Sentinel-2 images at the tillering stage. Among vegetation indices and leaf area index (LAI) used to predict teff and finger millet GY and AGB, the enhanced vegetation index (EVI) and normalized-difference VI (NDVI) provided the best fit to the data. NDVI and EVI most influenced teff AGB (R2 = 0.87; RMSE = 0.50 ton/ha) and GY (R2 = 0.84; RMSE = 0.14 ton/ha), and NDVI most influenced finger millet AGB (R2 = 0.87; RMSE = 0.98 ton/ha) and GY (R2 = 0.87; RMSE = 0.22 ton/ha). We found a close association between GY and AGB and the satellite EVI and NDVI. This demonstrates that satellite images can be employed in yield prediction studies. Our results show that satellite and crop canopy analyzer-based monitoring can facilitate the management of teff and finger millet to achieve high yields and more sustainable food production and environmental quality in the area. The results could be reproducible under similar study catchment conditions and boost crop yield. Extrapolation of the models to other areas requires local validation. To improve crop monitoring for farmers and reduce expenses, we suggest integrating time series Sentinel-2 images along with LAI obtained from crop canopy analyzers collected during the cropping season.

A resilient agricultural sector is essential for food security, particularly in the face of increasing climate risks. Research demonstrates that improving soil health through sustainable agricultural practices can enhance soil organic carbon, boost crop yields, increase resilience to extreme weather events, and strengthen farm economics. However, limited research has explored the impacts of diversified agricultural systems—those that implement multiple soil health practices—on soil carbon, soil health, and productivity. This paper synthesizes findings from a comprehensive literature review evaluating the effects of diversified agricultural systems in the United States. Key trends include higher soil carbon levels in diversified systems, regionally variable effectiveness, and improvements in crop yields and soil health through enhanced drought resilience, nutrient cycling, and erosion control. Despite promising outcomes, significant knowledge gaps remain. Many studies lack baseline measurements, making it difficult to determine whether soil carbon differences are due to sequestration or reduced losses. Limited geographic and temporal data also constrain our ability to generalize findings or optimize practice combinations. To address these challenges, we propose policy recommendations which include extending participation in the CSP and the EQIP, funding regionally targeted research through USDA ARCS and NRCS, refining NRCS ranking criteria, and improving USDA data reporting. With long-term investment and policy support, diversified agricultural systems have the potential to enhance sustainability and climate resilience in U.S. agriculture.

The growing global population and increasing agricultural demands have made nitrogen fertilizers essential for modern agriculture. However, nearly 50% of applied nitrogen fertilizers are lost to the environment, causing pollution and greenhouse gas (GHG) emissions. Biochar-based fertilizers (BBFs), combining biochar with chemical fertilizers, enhance nutrient efficiency, boost crop yields, and reduce N2O emissions. However, comprehensive field studies on BBF impacts remain limited. This study uses a global dataset of BBF field experiments to build predictive models with three machine learning algorithms for crop yields and N2O emissions, and to assess BBFs’ potential to increase yields and mitigate emissions in China’s major crops. The artificial neural network (ANN) model outperformed random forest (RF) and support vector machine (SVM) in predicting N2O emissions (R2: 0.99; EF: 0.99), while all models showed high accuracy for crop yields (R2, EF: 0.98–0.99). Variable importance analysis revealed that BBF C/N and BBF N/Mineral N explained 4.25% and 3.95% of yield variation, and 3.19% and 0.55% of N2O emission variation, respectively. BBFs could increase China’s major crop yields by 4.3–5.0% and reduce N2O emissions by 3.7–6.3%, based on simulations. Challenges like high costs and limited adaptability persist, necessitating optimized production, standardized protocols, and expanded trials.

Vermicomposting provides a green alternative to composting, which can reduce greenhouse gas emissions and improve soil health. As a result of existing waste management practices, greenhouse gases are released into the environment. Still, vermicomposting offers a sustainable solution by recycling organic waste into a soil amendment that improves soil health and increases crop yields. This study provides an in-depth overview of the benefits of vermicomposting, a practice that recycles organic waste materials into a nutrient-rich soil amendment called vermicompost, which can reduce greenhouse gas emissions, improve soil fertility, and boost crop yields by enhancing soil structure and microbial activity, thereby presenting vermicomposting as a sustainable way to recycle organic waste, while mitigating climate change, protecting soils, and boosting agriculture. This overview examines how vermicomposting organic waste lowers greenhouse gas emissions from landfills, improves crop yields through improved soil structure and fertility, and enriches soils by increasing microbial biodiversity and nutrient availability. Vermicomposting provides degradation and detoxification of organic waste with some nutrient-rich castings. The potential of these castings to improve soil health sparked interest among agricultural researchers. Crops fertilized with vermicompost thrived, producing higher yields and the nutrient density of the plants increased significantly. Emerging research reveals that vermicompost can fight against climate change. As an organic fertilizer, it enhances the ability of plants and soil to sequester carbon, decreasing greenhouse gases and also reducing emissions of methane and nitrous oxide compared to conventional fertilizers. With broader implementation, vermicomposting offers a meaningful path to combat climate change through regenerative agriculture.

Agriculture plays a crucial role in a nation's economy by significantly contributing to its Gross Domestic Product (GDP). Improved methods of farming not only benefit farmers by lowering their workload but also boost crop yields. Identifying the optimal soil for each crop is essential for producing harvests of the highest quality and quantity. Precision farming in agriculture uses Internet of Things (IoT) technology to ensure the most efficient use of available resources to increase crop yields and reduce operational costs. It reduces instances of crop failure and aids in averting catastrophic losses. Variations in soil temperature and soil moisture have the most significant influence on crop yield. The Soil Moisture Sensors calculate the soil's total volumetric water content. Using the BMP280 absolute barometric pressure sensor, it is possible to get accurate temperature and air pressure measurements. In the paper, the primary purpose of precision agriculture usage is to determine the optimal soil characteristics for the production of Barely, Maize and Sugarcane crops.

The main economic activity is agriculture. It is necessary for maintaining the ecosystem. Almost every element of people's life is dependent on a vast range of agricultural products. In addition to responding to climate change, farmers must handle the rising need for more food of higher quality. Farmers must be aware of the weather conditions in order to boost agricultural output and growth because this will allow them to choose the best crop to sow in those conditions. Smart farming powered by IOT improves the entire agricultural system with real-time field monitoring. It displays numerous parameters in crystal-clear real-time, including temperature, humidity, and soil, among others. It is possible to recommend crops by using the right algorithms on sensed data. The project intends to develop a system that predicts agricultural productivity using Internet of Things sensors that collect data on numerous environmental factors, such as temperature, rainfall, and pH. The suggested method seeks to help farmers boost agricultural productivity while decreasing waste and boosting profitability. The project's provision of reliable and timely information about crop yields is one of its primary goals. Farmers now make manual estimates of agricultural production, which can be tedious and imprecise. The proposed system might employ IoT sensors to collect data in real-time, giving farmers precise and current information on crop yields. One of the other objectives of the project is to deal with the unpredictable nature of weather patterns. Weather patterns have become more erratic as a result of climate change, making it difficult for farmers to schedule when to plant and harvest their crops. By examining current practises and adapting them to the current weather patterns, farmers can boost crop yields and decrease waste with the help of the suggested approach. Using machine learning algorithms and environmental data gathered by IoT sensors, the suggested method forecasts crop output. Machine learning algorithms can analyse large datasets and generate precise projections that assist farmers in making decisions. The system can be used by farmers with any degree of technological competency because it is accessible and user-friendly. Farmers may easily access and examine the data collected by the Internet of Things sensors thanks to the userfriendly system interface. Additionally, the system has the ability to provide farmers with immediate feedback, allowing them to alter their agricultural practises in reaction to the current environmental conditions.

Predicting climatic changes is considered one of the most important economic parameters as it remains a catalyst for the agricultural system of any country. Climatic data and services are crucial for agriculturalists to withstand the rising frequency of strong meteorological conditions, which negatively impact crop yields. Weather forecasts play a key role in managing resources for agricultural operations, enabling farmers to plan and protect their crops from natural disasters. In addition, global warming has fueled climatic unpredictability, creating challenges like hurricanes that damage the foundational roots of agricultural production. In recent times, Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) techniques have been predominantly adopted for daily forecasting climatic conditions, including rainfall, maximum temperature, and humidity. However, the existing models for climatic prediction require improvements in computational complexity and performance. This research article proposes the ensemble Residual Long Short-Term Memory (R-LSTM) along with Artificial Gorilla Troops Optimized Deep Learning Networks (AGTO-DLN) as a solution for climatic condition prediction to boost crop–yield production. Performance metrics for the proposed model examining precision, F1 score, accuracy, specificity, and recall operate through evaluation using 5,04,647 climatic parameters with various advanced learning techniques. The proposed method achieved 97.2% accuracy and 96.9% precision together with 96.5% recall and 96.6% specificity and 97.5% F1 score. The research proves that the proposed model demonstrates high potential for climate forecast in agricultural production environments consequently boosting crop yields to enhance farmer incomes.

In modern agriculture, enhancing soil health and crop productivity is essential to meet rising food demands. Various soil amendments, such as manure, chemical fertilizers, compost, and lime, are traditionally used to improve soil properties and boost crop yields. However, the effectiveness and sustainability of these amendments vary, highlighting the need for a comprehensive assessment to identify the most effective solution. This study investigates the potential of biochar as a soil amendment, comparing it with manure, chemical fertilizers, compost, and lime. The research aims to identify a soil treatment that not only improves crop yields but also enhances soil health and promotes long-term sustainability. The methodology involves a comparative analysis of these amendments, evaluating their impact on crop productivity, soil pH levels, water retention capacity, and nutrient content. Data was collected from experimental plots treated with each amendment. The results indicate that biochar significantly outperforms the other treatments across all measured parameters. Plots treated with biochar exhibited higher crop yields, improved soil pH balance, enhanced water retention, and increased nutrient content. These findings suggest that biochar is a superior soil amendment, offering both immediate and long-term benefits for soil health and agricultural productivity .In conclusion, the study demonstrates that biochar is the most effective soil amendment among those tested, making it a promising solution for sustainable farming. The results provide a strong foundation for further research and practical applications of biochar in diverse agricultural settings.

Agriculture is the most significant and stable economic sector in the world because it both directly and indirectly produces and supplies food for people. The demands of a growing population are beyond the capacity of global agriculture production to meet. The world has experienced varying degrees of food crises at different times. To ensure food security and meet the demands of an expanding population, pressure is being applied to the agriculture sector. Chemical fertilizers are therefore viewed as an essential source of plant nutrition for improving crop yields. Farmers began to believe that applying more chemical fertilizers results in increased crop yield. However, less than half of the fertilizer applied will be absorbed by the crop, with the surplus either leaching into water sources or becoming immobilized in the soil. With innovative nano-technological strategies that enhance precision farming methods, improve plant nutrient absorption, support land and water conservation, boost crop yield, and develop uses for nano-fertilizers (NFs), nanotechnology has enormous potential to improve agricultural practices.

An increase in crop yield is essential to reassure food security to meet the accelerating global demand. Several genetic modifications can increase organ size, which in turn might boost crop yield. Still, only in a few cases their performance has been evaluated under stress conditions. MicroRNA miR396 repress the expression of GROWTH-REGULATING FACTOR (GRF) genes that codes for transcription factors that promote organ growth. Here, we show that both Arabidopsis thaliana At-GRF2 and At-GRF3 genes resistant to miR396 activity (rGRF2 and rGRF3) increased organ size, but only rGRF3 can produce this effect without causing morphological defects. Furthermore, introduction of At-rGRF3 in Brassica oleracea can increase organ size, and when At-rGRF3 homologs from soybean and rice are introduced in Arabidopsis, leaf size is also increased. This suggests that regulation of GRF3 activity by miR396 is important for organ growth in a broad range of species. Plants harboring rGRF3 have larger leaves also under drought stress, a condition that stimulates miR396 accumulation. These plants also showed an increase in the resistance to virulent bacteria, suggesting that the size increment promoted by rGRF3 occurs without an obvious cost on plant defenses. Our findings indicate that rGRF3 can increase plant organ size under both normal and stress conditions and is a valuable tool for biotechnological applications.

Nitrogen fertilizers used to grow crops around the globe have a problem. More than three-quarters of their nutrients get washed away before plants can absorb them, wasting money and creating environmental messes downstream. Now, researchers have developed nanoparticle fertilizers that release nutrients slowly over a week, giving crops more time to take them up (ACS Nano 2017, DOI: 10.1021/acsnano.6b07781). Conventional slow-release fertilizers consist of urea coated in water-insoluble sulfur or polymers. Such fertilizers reduce runoff that can lead to harmful algal blooms in waterways, says Gehan Amaratunga of the University of Cambridge. But these fertilizers are expensive and haven’t been shown to increase crop yield. Amaratunga and his colleagues decided to try a new strategy: They attached nitrogen-laden urea molecules to nanoparticles of hydroxyapatite, a naturally occurring form of calcium phosphate. In water, the urea-hydroxyapatite combination released its nitrogen payload over the course of a wee...

The area of land viable for agriculture is diminishing each year due to topsoil erosion, loss of soil fertility, water insecurity and climatic change, factors which limit productivity and threaten crop yields. The changing climate will exaggerate the existing differences between developed and developing countries and may also see pests and diseases infiltrating wider geographical zones, further threatening productivity. These factors are particularly important for many countries in Latin America and the Caribbean (LAC). Hence, with the current range of agricultural land having reached a supply threshold and limited prospects of increasing the area, the rate of increase in food production will not keep pace with the rate of population growth. Modern biotechnology offers a means of delivering sustainable agricultural practices and this chapter provides an overview of the institutions and research projects in LAC countries, whose objective is to provide more food in a safe, sustainable way. There is a wealth of research being undertaken in Latin America on both commodity crops and locally‐important staples. Molecular breeding, genetic engineering, in vitro micropropagation, germplasm screening and conservation projects are being used to identify useful traits, improve resistance to a variety of abiotic and biotic factors and boost crop yields throughout the region. An overview of the current status of GM crops–research, approval and commercialisation status–demonstrates that these biotechnological methods, together with the development of novel bioproducts and integrated pest management strategies, are facilitating an environmentally conscious attitude to crop protection and enabling more sustainable agricultural practices in a number of countries from the LAC region. Engineering crops that are tailored to the environment, so as to resist climate change and environmental stress, may permit marginal lands to be brought into agricultural use to produce locally‐important crops and commercially relevant crops for a growing population, as well as feed for the livestock on which the population depends. Some countries in Latin America, such as Costa Rica and Colombia, have a particularly rich biodiversity so changing agricultural practices and the adoption of genetically modified (GM) varieties in such regions must not pose a threat to local biodiversity. Projects to assess the likelihood of GM traits passing into weedy and wild relatives are being conducted in centres of biodiversity for key crops within Latin America. Agriculture in Latin America will come under increasing pressure to provide food, income and livelihoods for current and future generations. Its success will depend on the appropriate integration of traditional methods with contemporary technologies to enhance productivity in a sustainable way, without jeopardising ecological security.