INTRODUCTION: Potatoes and tomatoes are important Solanaceae crops that require effective disease monitoring for optimal agricultural production. Traditional disease monitoring methods rely on manual visual inspection, which is inefficient and prone ...
Climate change poses significant challenges to global food security by altering precipitation patterns and increasing the frequency of extreme weather events such as droughts, heatwaves, and floods. These phenomena directly affect agricultural produc...
As the source of data acquisition, sensors provide basic data support for crop planting decision management and play a foundational role in developing smart planting. Accurate, stable, and deployable on-site sensors make intelligent monitoring of var...
Genomic prediction is a powerful approach for improving genetic gain and shortening the breeding cycles in animal and crop breeding programs. A series of statistical and machine learning models has been developed to increase the prediction performanc...
This study aimed at quantifying the potential effects of plant and soil microbial interaction on selenium (Se) volatilization, with the specific objectives of identifying soil bacteria associated with rabbitfoot grass () and demonstrating the enhance...
Nitrogen is essential for rice growth and yield formation, but traditional methods for assessing nitrogen status are often labor-intensive and unreliable at high nitrogen levels due to saturation effects. This study evaluates the effectiveness of fla...
Understanding the early interactions between plants and endophytes will contribute to a more systematic approach to enhancing endophyte-mediated effects on plant growth and environmental stress resistance. This study examined very early growth and as...
Estimation of forest biomass at regional scale based on GEDI spaceborne LiDAR data is of great significance for forest quality assessment and carbon cycle. To solve the problem of discontinuous data of GEDI footprints, this study mapped different ech...
How to evaluate the accuracy of quantitative trait prediction is crucial to choose the best model among several possible choices in plant breeding. Pearson's correlation coefficient (PCC), serving as a metric for quantifying the strength of the linea...