Abstract Machine learning has proven to be technically flexible in recent years, which allows
it to be successfully implemented in problems in various areas of knowledge. Carbon …

Simple Summary Worldwide, honeybees (Apis mellifera L.) are involved in pollinating both
wild and economically useful plants, while their products are also used by the food and …

This study investigates the adoption of Digital Beehive Monitoring Technology (DBMT)
based on a survey with 844 beekeepers across 18 European countries, shedding light on …

The number of pollen-bearing honey bees serves as a vital indicator for assessing colony
balance and health. Despite its significance, prevailing detection techniques still rely heavily …

The characterization of soil variations crucial for agriculture is challenging due to soil having
different mineral composition and particle-size distribution. Traditional methods are costly …

Abstract Machine Learning (ML) is the study and the usage of the mathematical algorithms
which can improve their performance without the need for human interaction. These …

Honey bees are not only the fundamental producers of honey but also the leading
pollinators in nature. While honey bees play such a vital role in the ecosystem, they also …

Highlights•An accurate machine learning model to predict temperature droo**
occurrence.•It can be adjusted and calibrated to be applied on different contexts of …

The performance of a classification model in machine learning is affected by many factors,
such as the method of splitting the dataset and the type of machine learning technology …

The bee Apis mellifera plays an important role in the balance of the ecosystem. New
technologies are used for the evaluation of hives, and to determine the quality of the honey …