1162 papers
This study demonstrates that sorghum–soybean intercropping enhances soybean salt tolerance by remodeling the rhizosphere bacterial community to enrich beneficial genera like *Bacillus* and *Pseudomonas*, which optimizes the saline soil microenvironment and alleviates oxidative stress.
This study demonstrates that a deep learning framework combining 1D-CNN and SMOTE with NIR spectroscopy can accurately and rapidly classify soil organic matter and total carbon in northern Thailand, offering a non-destructive, high-performance alternative to conventional laboratory methods for precision agriculture and sustainable land management.
This study systematically evaluated hyperspectral imaging workflows to identify optimal combinations of sample partitioning, spectral preprocessing, feature selection, and machine learning models for non-destructively predicting pigment and nutrient traits in tomato leaves, revealing that while nitrogen-related traits were reliably predicted using CNNs, chlorophyll prediction remained limited and that workflow optimization must be tailored to specific target traits.
This study demonstrates that citric acid-mediated microwave extraction (CAM-MAE) significantly outperforms conventional heating methods by rapidly yielding high-purity, high-molecular-weight polysaccharides from *Centella asiatica* with potent antidiabetic and antioxidant activities.
This critical review argues that agroforestry and rainforestation are complementary, not interchangeable, strategies for reducing tropical deforestation pressure, emphasizing that their success depends on a landscape hierarchy prioritizing intact forest protection and natural regeneration alongside context-specific implementation, tenure security, and robust monitoring.
This study presents a machine learning-based framework that transitions from high-resolution laboratory spectroscopy to a deployable robotic LiDAR system, successfully achieving non-contact, high-precision estimation of volumetric water content in soilless rockwool substrates for automated irrigation in controlled-environment agriculture.
This study demonstrates that a novel low-dose resveratrol-loaded bionanocomposite coating composed of carboxymethyl cellulose, nanochitosan, and green pomelo essential oil effectively extends the shelf life and preserves the quality of fresh mushrooms by reducing weight loss, maintaining firmness, and retaining aromatic compounds during cold storage.
This study characterizes the nutritional and bioactive properties of *Rhynchophorus phoenicis* and *Oryctes rhinoceros* larvae consumed in the Democratic Republic of Congo, revealing their rich mineral profiles, phytochemical diversity, and potent antioxidant activities as a scientific basis for their integration into functional food strategies to address food insecurity and oxidative stress in sub-Saharan Africa.
This systematic review synthesizes global evidence on physiological, genetic, and socioeconomic strategies for developing drought-resilient soybean genotypes, identifying key molecular mechanisms and breeding technologies while highlighting critical gaps and a tailored roadmap for enhancing soybean productivity and climate resilience in Tanzania.
This paper introduces SoyNodules, a FAIR-compliant dataset containing 1,701 annotated images of soybean roots and isolated nodules with 49,210 bounding boxes, designed to facilitate the development of deep learning models for automated nodule detection and biological nitrogen fixation assessment in precision agriculture.