Purpose This study analyses the literature on artificial intelligence (AI) and its implications
for the agri-food sector. This research aims to identify the current research streams, main …

Abstract Machine learning (ML) algorithms perform better than classical statistical
approaches to explore hidden nonlinear relationships. In this context, the goal of this …

Food insecurity has become one of the major global issues in present times. To overcome
this, national and international communities have taken various strategies to ensure …

Pea (Pisum sativum L.) is a legume valued mainly for its high seed protein content. The
protein content of pea is characterized by a high lysine content and low allergenicity. This …

Abstract Machine learning (ML) can make use of agricultural data related to crop yield under
varying soil nutrient levels, and climatic fluctuations to suggest appropriate crops or …

Land suitability assessment, as an important process in modern agriculture, involves the
evaluation of numerous aspects such as soil properties, climate, relief, hydrology and socio …

An experiment was conducted during rabi season of 2021-2022 at the Agronomy Research
Farm, Department of Agronomy, Faculty of Agriculture, University of Agriculture, Faisalabad …

Many large dams built on the Çoruh River have resulted in the inundation of olive groves in
Artvin Province, Turkey. This research sets out to identify suitable locations for olive …

The purpose of this special issue is to contribute to the growing body of literature on the
externalities of information technology within the specific remit of the relationship between …

Sequential minimal optimization (SMO) method is an algorithm for solving optimization
problems arising from the training process of support vector machines (SVM). The SMO …