Results 131 to 140 of about 9,010 (214)

Agronomic performance, nitrogen fixation, and amino acid profile of different common bean genotypes in Germany

Agrosystems, Geosciences &Environment, Volume 9, Issue 2, June 2026.
Abstract Common beans (Phaseolus vulgaris L.) are a highly nutritious legume crop with global significance. However, their cultivation is limited in temperate regions like Germany due to climatic and agronomic constraints. The cultivation of beans has gained attention due to their potential contribution to climate change mitigation by reducing nitrogen
Antônia Finkler Dias Fernandes, Jens Hartung, Simone Graef‐Hönninger   +2 more
wiley   +1 more source

Improving maize LAI estimation by integrating multispectral imagery and digital surface models with ensemble learning. [PDF]

Front Plant Sci
Li W, Lou S, He J, Zhao J, Liu X, Fu G, Pan K, Li T.   +7 more
europepmc   +1 more source

Economic value of in‐season information from N‐rich strip‐based nitrogen recommendations for winter wheat

Agrosystems, Geosciences &Environment, Volume 9, Issue 2, June 2026.
Abstract Nitrogen overapplication remains a persistent challenge in winter wheat production, contributing to low nitrogen use efficiency (NUE), higher production costs, and increased environmental externalities. Sensor‐based nitrogen management systems, such as the nitrogen‐rich strip (NRS), were developed to provide in‐season information on crop ...
Enoch Adom, Dayton M. Lambert, Phillip D. Alderman, B. Wade Brorsen   +3 more
wiley   +1 more source

Effects of planting density and row spacing configuration on dry matter accumulation and distribution, nutrient content, and yield in cotton. [PDF]

Front Plant Sci
Bai Z, Cao N, Wen M, Hu Q, Wang Y, Lin J, Wan S.   +6 more
europepmc   +1 more source

Retrieval of rice biophysical parameters from Sentinel‑2 using parsimonious multi‑output machine learning

Agrosystems, Geosciences &Environment, Volume 9, Issue 2, June 2026.
Abstract Rice (Oryza sativa L.) crop monitoring in Africa requires efficient retrieval of biophysical parameters such as leaf area index (LAI) and leaf chlorophyll content (LCC), which are essential for crop stress detection and nutrient management.
Joseph Kagotho Muriithi, Collins Mito, Giovanni Laneve, John Buers, Elijah Cheruiyot, Jephter Ondieki   +5 more
wiley   +1 more source

Enhanced chickpea (<i>Cicer arietinum</i> L.) growth and yield attributes via agronomic modulation using nano-emulsion biofertilizer for sustainable crop productivity improvement. [PDF]

Front Microbiol
Sri Abisankar M, Augustine R, Jeshwin Giftson SP, Graceson RS, Ramesh Kumar P, Indira Petchiammal K, Praveena Katharine S, Dhivyalakshmi T, Santhosh Anto Kumar R.   +8 more
europepmc   +1 more source

Sources of Variation in Fecal Haptoglobin in a Population of Wild Capuchin Monkeys (Cebus imitator)

American Journal of Primatology, Volume 88, Issue 6, June 2026.
Fecal haptoglobin values show significant seasonal variation in wild capuchin monkeys. Values are highest, and most variable in the early‐mid dry season, when fruit is typically scarce and water sources are standing pools, which can accumulate pathogens.
Raquel Hernández‐Rojas, Hadjira Hamou, Ronald Lopez Navarro, Katharine M. Jack, Fernando A. Campos, Amanda D. Melin, James P. Higham   +6 more
wiley   +1 more source

Monitoring plant moisture content and optimizing irrigation prescriptions based on UAV multimodal data. [PDF]

Front Plant Sci
Fu W, Hou X, Wang D, Chen Z, Cheng Q, Li Y, Duan F.   +6 more
europepmc   +1 more source

Addressing Small Data Challenges in Biopharmaceutical Development and Manufacturing: A Mini Review of Multi‐Fidelity Techniques

Biotechnology and Bioengineering, Volume 123, Issue 6, Page 1465-1480, June 2026.
ABSTRACT The growing demand for biopharmaceutical products reflects their effectiveness in medical treatments. However, developing new biopharmaceuticals remains a major bottleneck, often taking up to a decade before market approval. Machine learning (ML) models have the potential to accelerate this process, but their success depends on access to large
Mohammad Golzarijalal, Uwe Aickelin, Ellen Otte   +2 more
wiley   +1 more source

UAV-Based Estimation of Tea Leaf Area Index in Mountainous Terrain: Integrating Topographic Correction and Interpretable Machine Learning. [PDF]

Sensors (Basel)
Lin N, Zhao J, Shao H, Wang M, Chen H.
europepmc   +1 more source