Integrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integ...

A feedback control method for regulating crop growth in advanced life support systems is presented. Two models for crop growth are considered, one developed by the agricultural industry and used by the Ames Research Center, and a mechanistic model, termed the Energy Cascade model. Proportional and pointwise-optimal control laws are applied to both models using wheat as the crop and light intens...

Agricultural Extension services are among the most important rural services in developing countries. The services are considered to be a key driver of technological change and productivity growth in agriculture. In Kenya, like in the rest of the developing economies, agricultural extension has largely been delivered through supply–driven approaches. Due to perceived low impact of agricultural e...

The concept of "Plant factory" could realize the multiple targets of high yield, high quality, high efficiency and security. It had become the trend of agricultural development. It solved the growing contradiction between people's increasing demand for green, organic food and the diminishing agricultural arable area in China. According to the research on the key technologies of plant factory, a...

Modeling of longitudinal data from agricultural experiments using growth curves helps understand conditions conducive or unconducive to crop growth. Recent advances in Geographical Information Systems (GIS) now allow geocoding of agricultural data that help understand spatial patterns. A particularly common problem is capturing spatial variation in growth patterns over the entire experimental d...

Modelling of longitudinal data from agricultural experiments using growth curves help understand conditions conducive or unconducive to crop growth. Recent advances in Geographical Information Systems (GIS) now allow geocoding of agricultural data that help understand spatial patterns. A particularly common problem is capturing spatial variation in growth patterns over the entire experimental d...

There is a growing need to increase global crop yields, whilst minimising use of resources such as land, fertilisers and water. Agricultural researchers use ground-based observations to identify, select and develop crops with favourable genotypes and phenotypes; however, the ability to collect rapid, high quality and high volume phenotypic data in open fields is restricting this. This study dev...