Jute holds significant importance as a cash crop in Bangladesh and was once renowned as
the country's" golden fiber." Before embarking on a comprehensive strategy, it is crucial to …

Accurate yield forecasts can assist decision-makers in develo** plans to bridge the food
demand gap in the context of changing climatic conditions. Literature shows a variety of …

Management of agri-residues generated in large quantities necessitates for its accurate
estimation. Data analysis using machine learning methods can predict the agri-residues …

Discriminant function analysis has been used for forecasting of Sugarcane yield of
Coimbatore district in Tamilnadu. Crop yield has been classified into two and three groups …

The COVID-19 pandemic is wreaking havoc on society and the current situation the country
is in now clearly shows the failure of predicting the second wave in India. Several variants of …

Purpose The internal (farmer-controlled) and external (non-farmer-controlled) factors affect
crop yield. However, not a single study has identified and analyzed yield predictors in India …

Wheat is the most important source of food on earth and vital for food safety. It contains 75–
80% carbohydrates, 9–18% protein, fiber, many vitamins (especially B vitamins), calcium …

With the growing complexity of modern vehicle system, the capability of modeling the
behavior of different subsystems and predicting their forthcoming patterns become vital. It …

Agriculture is important to the Indian economy and employment; India is the world's second-
largest producer of sugarcane, which is a key cash crop in Bihar. The main objectives of this …

The present study is focused to develop pre-harvest forecast models for rice yield based on
meteorological parameters in Haryana. The discriminant function analysis (DFA) technique …