An inexpensive and precise crop yield prediction technology is required for facilitating
precision agriculture for Asian countries in which small-scale fields are primarily managed …

This study explores crop yield forecasting through weight agnostic neural networks (WANN)
optimized by a modified metaheuristic. WANNs offer the potential for lighter networks with …

As the largest cotton-growing region in China, **njiang has contributed more than 80% of
the total national cotton production in recent years. Timely and accurate estimation of cotton …

Rice grain yield prediction with UAV-driven multispectral images are re-emerging interests
in precision agriculture, and an optimal sensing time is an important factor. The aims of this …

Solar-induced chlorophyll fluorescence (SIF), as a direct probe of vegetation photosynthesis,
has recently been an effective indicator for crop yield estimation in late-season. Spatio …

Cotton is a major economic crop predominantly cultivated under rainfed situations. The
accurate prediction of cotton yield invariably helps farmers, industries, and policy makers …

Soil moisture content plays a vital role in agricultural production, significantly influencing
crop growth, development, and yield. Thoroughly understanding the specific soil moisture …

Lint yield in cotton is governed by light intercepted by the canopy (IPAR), radiation use
efficiency (RUE), and harvest index (HI). However, the conventional methods of measuring …

To elucidate the variation characteristics of nitrogen (N), phosphorus (P), and potassium (K)
content and accumulation in cotton at different yield levels, a two-year experiment was …

In the context of climate change, in-season and longer-term yield predictions are needed to
anticipate local and regional food crises and propose adaptations to farmers' practices …