1958 papers
This study develops a practical three-parameter predictive model that effectively forecasts *Cryptolestes ferrugineus* infestations in bulk wheat by integrating population history with thermal exposure metrics, such as effective degree-days and temperature fluctuations.
This study demonstrates that a Random Forest model utilizing spectral data at 1320 nm and various indices can accurately estimate crop residue cover across diverse wheat straw management scenarios, providing a reliable foundation for future large-scale remote sensing monitoring.
This two-year study in the Vindhyan Zone demonstrates that sowing wheat on November 20 with four irrigations and 160 kg N ha⁻¹ maximizes yield and profitability, while the calibrated DSSAT-CERES-Wheat model accurately simulates these outcomes, validating its utility as a decision-support tool for regional wheat management.
This study mathematically modeled the thin-layer drying of nance pulp in a convective tunnel dryer at 60–80°C, identifying the Midilli et al. and Alonso et al. models as the best fits and determining an effective moisture diffusivity range of 2.4842 to 4.0409 × 10⁻⁹ m²/s with an activation energy of 23.62 kJ/mol.
An analysis of over 1.2 million households across 57 low- and middle-income countries reveals that aquatic foods are the most accessible and budget-significant animal-source food for the poorest households, serving as a critical nutritional foundation that is often replaced by other meats and dairy only as household welfare improves.
This review evaluates the potential and current limitations of integrating microalgae into recirculating aquaculture systems, concluding that while they offer significant benefits for water quality, nutrition, and sustainability, their commercial scalability remains hindered by high energy costs, harvesting difficulties, and operational instability, restricting adoption largely to pilot-scale and niche applications.
This study demonstrates that smoke water derived from paddy straw, neem, and mango significantly influences the germination and early seedling vigor of buckwheat (Fagopyrum esculentum) in a manner that is strongly dependent on both the plant source and the treatment concentration.
This study establishes a retrospective genomic analysis framework using expected progeny distributions to quantitatively decode historical Japanese citrus breeding strategies, revealing how selection intensity and dominance effects shaped modern cultivars and highlighting the pivotal role of the 'Kiyomi' parent despite its unfavorable trait values.
This study investigates the thin-layer drying kinetics of *Matricaria pubescens* leaves at varying temperatures and air velocities, identifying the Midilli and Kucuk model as the most accurate predictor and revealing a temperature-dependent drying process with an activation energy of 80.18 kJ/mol.
This study presents a deep learning framework for detecting peach leaf diseases under real field conditions, demonstrating that an Inception-V4 model trained from scratch achieves superior accuracy (97.50%) compared to transfer learning-based architectures like ResNet-50 and VGG-16.