Researchers at Cornell University have developed a framework to predict crop yield using satellite images of solar-induced chlorophyll fluorescence. This approach could help farmers react to changing conditions, improve crop health, and reduce poverty. By leveraging satellite data, the method is cheaper and faster than traditional yiel...
Researchers engineered increased mesophyll conductance in a model crop, improving CO2 diffusion and uptake. The study showed an 8% increase in photosynthesis in the field, demonstrating potential for improved crop production and sustainable water use.
Targeted genome editing tools have revolutionized crop breeding methods, significantly improving breeding efficiency and precision. The latest advances in base editing, prime editing, and precise manipulation tools are expected to become critical foundational technologies for future crop research and breeding applications.
The review highlights the transformative impact of gene-based breeding on improving crop and livestock genetics, enabling molecular precision agriculture and medical science. GBB has been instrumental in enhancing fiber length and grain yield in cotton and maize, achieving high prediction accuracy and reliability.
A research team proposes a method to quantify the 'golden-hour water use efficiency' (GHW) trait, aiming to breed high-yielding and water-efficient crop varieties. The study focuses on the importance of balancing water conservation with biomass output in crops, offering a greener alternative for agricultural productivity.
The Yangtze River Basin faces severe water quality issues due to excessive fertilizer and pesticide use, as well as the inappropriate disposal of agricultural waste. The study highlights the need for balancing green agriculture with development to ensure food security and water quality.
A study explores multi-objective nitrogen management in the food system, focusing on Quzhou County in China. The researchers found significant N losses to the environment, mainly from crop and animal production, and developed a framework for reducing these losses while promoting food security and economic sustainability. The study sugg...
Researchers found that adjusting crop loads to specific levels for different rootstock types can optimize tree growth and fruit quality. Chemical thinning agents like carbaryl and 6-BA were effective in managing crop load, with best practices involving specific concentrations and application timings.
Over the past five years, China's Agriculture Green Development (AGD) program has made significant progress in developing innovative crop production methods and technologies. The program aims to promote sustainable agriculture by reducing agrochemical inputs and environmental impacts.
The GreenLab model simulates plant growth with accuracy, capturing nuanced effects of environmental factors on structure and yield. Its integration with cutting-edge technologies enables rapid phenotyping and yield prediction to support sustainable agricultural practices.
Researchers developed synthetic microbial communities to control weeds while promoting crop growth, reducing herbicide consumption and enhancing wheat yields. The study found that combining these microbial communities with low-dose herbicides can rescue up to 22% of lost grain yield under weed-infested conditions.
Smallholder farmers in four African countries experienced reduced crop losses and higher incomes after receiving pest alerts generated using earth observation data. The Pest Risk Information Service (PRISE) project demonstrated a positive impact on farmers' livelihoods, with benefits more pronounced for male-headed households.
New research reveals that domestication impacts the microbial communities associated with crops. The study found consistent effects on the plant microbiota across independently domesticated crop species in Mesoamerica and South America. Changes in seed mineral content were linked to changes in microbiome composition.
Research reveals that aquifer depletion can curb crop yields even when it appears saturated enough to continue meeting irrigation demands. As groundwater dwindles, agricultural losses escalate, especially for corn and soybean yields.
The study explores the historical development of crop-livestock integration in China, identifying four distinct stages from traditional subsistence production to contemporary pollution control. It highlights the significance of this practice in fostering a circular economy and promoting rural development.
Research by The Jones Center at Ichauway found that hurricanes increase cone production in longleaf pine by 31% and 71% two years after the event, suggesting a possible explanation for the masting phenomenon. This discovery sheds light on the role of weather conditions in triggering seed germination.
A global study reveals that farmworkers in major crop regions are facing increasing exposure to extreme heat and humidity, which can impair their ability to function. The most affected crops are rice and maize, with nearly half of the world's rice cropland already experiencing extreme conditions during the planting and harvest seasons.
A new study reveals that C4 crops are significantly less sensitive to ozone pollution than C3 crops, with potential implications for improving crop productivity and resilience. The research suggests that C4 bioenergy feedstocks can maintain performance in regions with high ozone levels.
Researchers have created high-resolution maps showing the potential for biochar to sequester large amounts of carbon, with Bhutan and India leading the way in reducing their greenhouse gas emissions. The study suggests that biochar production can remove up to one billion metric tons of carbon from the atmosphere annually.
The study found that soil biota and their networks are easily altered by the soil environment, cultivation history, and crops. The research team applied DNA metabarcoding to analyze changes in soil organisms associated with crop growth, revealing distinct prokaryotic and eukaryotic communities and networks.
Researchers from Aarhus University found that current inventory methods rely solely on nitrogen content, neglecting degradability and leading to misleading inventories. The study suggests a distinction between mature and immature crop residues could improve accuracy and target mitigation strategies.
A new study by University of Illinois researchers found that management zone maps, which aim to optimize crop yields based on soil and landscape conditions, are unreliable. The most significant factor affecting crop responses is weather, with yields varying significantly from year to year.
Earthworms play a significant role in global food production, contributing approximately 6.5% of grain yield and 2.3% of legumes produced worldwide annually. The research highlights the importance of soil biodiversity and its impact on crop productivity, suggesting that earthworms can increase plant growth by up to 25%.
A new system using satellite data improves crop area and yield estimates, providing critical information for food security and sustainability planning. The WorldCereal project offers a cloud-based platform with diverse operational models to cater to various user communities.
Researchers developed a method to predict rice yield using smartphone photos, showing 68% accuracy and comparable results to satellite data. The model's simplicity makes it suitable for mobile devices and can be easily transferred to other crops.
Researchers found that behaviors nourishing individual plant fitness can be detrimental to the whole community in high-density stands. Simulated shade may improve breeding for high-yielding cultivars by understanding molecular and genetic components of interactions between wheat plants.
Scientists create a pH-controlled oxidation-resistant ferrous foliar fertilizer delivery system that adheres efficiently to hydrophobic leaf surfaces. The innovative technology enhances crop yield and alleviates iron deficiency, offering a viable approach for improving crop nutrition and productivity.
The study found that fruits pollinated by animals are 23% higher in quality, with benefits independent of geographical regions and pollinator species. This suggests that crop quality depends significantly on the presence of pollinating animals.
A new study by the University of Illinois and USDA-Agricultural Research Service has identified the key factors influencing sweet corn yield. The analysis found that seed source is a significant variable, with processors having a choice over which hybrids to use, and high nighttime temperatures also impact yield.
A research group at Kyoto University has successfully developed a self-fertile buckwheat variety and a new type of the crop with a sticky texture. This breakthrough could contribute to the efficient breeding of less-common orphan crops, addressing the world's growing food demands.
Research suggests that involving women more in agricultural decision-making can lead to a wider variety of crops being grown, improving nutritional value and environmental benefits. This finding supports the importance of women's empowerment in improving global food supply and protecting low-income farming communities.
Researchers found that cultivating reed grass on undrained peat soil or wet meadows can significantly reduce greenhouse gas emissions compared to traditional potato crop rotation. This approach also offers potential economic benefits and can help restore the original ecosystem with high biodiversity.
A new study suggests that while winter cover crops can reduce nitrogen pollution by up to 30%, their effectiveness will decrease under future climate scenarios. Illinois' corn yields are expected to suffer more than soybean yields, especially in southern regions, as warmer temperatures and changing rainfall patterns impact crop growth.
A meta-analysis reveals that birds generally have a net benefit on production for some crops by controlling pests. Non-lethal measures to deter birds are effective in reducing crop losses. The study found that around 10% of bird species consume crops, with 65% showing a positive effect on woody crop yield.
A new computer model forecasts yield for four key crops in the southeastern US, drawing on climate, groundwater, and agricultural data. The tool helps farmers and water resource managers identify ways to maximize crop yields while efficiently utilizing water and energy.
A new study by University of Delaware researchers assesses the effects of climate variability on crop production in the US. The study reveals that fluctuations in planted and harvested areas contribute significantly to crop production shocks, which can have severe impacts on food stability.
Researchers have unlocked the large-scale genomic analysis of foxtail millet, an important cereal crop that has been grown for roughly 11,000 years. The study identified key genes and marker-panels for its evolution and improvement in different environments.
The FAO's AquaCrop model has been updated to simulate alfalfa yield with precision, offering valid predictions for different climates and zones. The new feature was developed by the University of Córdoba and IAS-CSIC, using data from Belgium, Turkey, and Canada.
A new study by CABBI researchers has identified the types of microbes associated with engineered oilcane, revealing diverse microbial associations that could increase oil yields for sustainable bioenergy production. The findings suggest that plant-microbial interactions play a key role in determining the composition of the microbiome.
Researchers used an advanced ecosystem model to assess the impacts of winter cover cropping on soil organic carbon accumulation. They found that growing cover crops can increase SOC by 0.33 megagrams per hectare per year and that SOC benefits can be improved through increasing cover crop biomass.
A new machine learning model called DeepCrop was developed to predict plant growth with greater efficiency and accuracy. It can accommodate several input variables and has fewer limitations on data processing, making it suitable for various applications.
Researchers develop imaging-based computer algorithms to boost crop-breeding data using self-supervised contrastive learning methods, outperforming conventional supervised approaches. The study uses wheat as a model crop and finds that these new methods can improve plant phenotyping accuracy and scalability.
Researchers at the University of Liverpool have improved photosynthesis by engineering a faster Rubisco enzyme into tobacco plant cells. This breakthrough aims to support global food production and address climate change by increasing crop productivity.
Researchers developed a new deep learning algorithm that restores motion-blurred images and improves crop and weed segmentation. The WRA-Net method outperformed other databases in terms of segmentation accuracy, making it a promising solution for efficient weed control.
A new University of Illinois study suggests that widespread planting of cereal rye could significantly reduce nitrate levels in Illinois' tile drainage water. The research found that adopting winter cover crops, such as cereal rye, can help minimize nitrogen loss and improve water quality.
A new phenotyping approach analyzes crop traits at the 3D level using a rail-based field phenotyping platform with LiDAR and an RGB camera. The method provides accurate quantification of crop traits such as plant height, leaf shape, and leaf color.
A new study reveals that Indian farmers have adapted to climate change by changing management practices and using hardier crop varieties. However, the impact of climate change on crop yields varies across crops and regions, with some areas experiencing greater benefits than others.
A research team developed an AI approach to automate crop head counting, using synthetic annotated datasets to train deep learning models. The technique demonstrates improved accuracy and can be applied to other applications with dense repeating patterns.
A comprehensive study across six continents found intercropping to be effective against pests, with cabbage and squash showing the strongest resistance. The analysis of 44 field studies revealed that interspersed planting schemes were more effective than border plantings.
A new soil sensor has been developed to accurately measure temperature and nitrogen levels in soil, enabling farmers to optimize fertilizer use and reduce environmental pollution. The sensor can decouple temperature and nitrogen signals, allowing for precise monitoring of crop health and growth.
A team of MIT researchers has created an 'unclonable' label system to combat counterfeit seeds in Africa, where fake seeds can cost farmers up to two-thirds of expected crop yields. The system uses biodegradable silk-based tags with unique codes that cannot be replicated.
A North Carolina State University study found that cover crop adoption can reduce crop insurance losses due to prevented planting in the US Midwest. Longer term use of cover crops also leads to larger reductions in prevented-planting risk, with a 1% increase translating to nearly $40 million in reduced indemnities.
A University of Illinois project uses AI-powered object recognition to quantify kernel damage in wheat, enabling faster disease analysis and improved resistance. The technology has shown promising results, with potential for an online portal to automate scoring and support breeders in their efforts to eliminate fusarium head blight.
The giant faba bean genome has been successfully sequenced, offering insights into its traits such as drought tolerance and protein content. This breakthrough has the potential to improve crop yields and reduce reliance on artificial fertilizers, making faba bean a more attractive crop for sustainable agriculture.
A study published in PLOS Climate suggests that climate change is significantly affecting land where coffee is cultivated, particularly due to synchronous climate hazards occurring in multiple areas. The researchers found an increase in climate hazards and compound events threatening coffee crops globally between 1980 and 2020.
A new method involving drones and deep learning has been developed to replace manual rice counting with higher accuracy. The RiceNet network architecture can identify plant density, location, and size with good signal-to-noise ratio, producing quality maps for future automated crop management techniques.
A $5 million grant from the USDA Natural Resources Conservation Service supports a Climate-Smart Sustainability Certificate program for small-scale farmers. The program aims to improve crop production while reducing greenhouse gas emissions and increasing carbon removal.
The study identifies challenges in ensuring crop monitoring data reliability, including the lack of standard categorized methods for assessing crop conditions. A novel method using artificial intelligence and computer vision has been developed to collect field yield data, reducing labor intensity and costs.
George Mason University researchers are developing a digital twin system to provide farmers with real-time data on crop conditions, soil, weather, and markets. The CropSmart Digital Twin (CSDT) aims to support the USDA's goal of increasing U.S. agricultural production by 40% while reducing its environmental footprint by half by 2050.
Researchers at the University of Turku found that reducing pesticide pollution and harvesting intensity can increase crop yields and contribute to climate change mitigation. By optimizing carbon sequestration and storage in soils, farmers can improve plant resilience and productivity, while minimizing environmental harm.