Systems Modeling

Abstract

The agricultural systems have complex interactions with the surrounding environment and soil, and better understanding is possible through computer application. The interactions between systems and environment are so complex that one cannot quantify their cumulative affects without application of latest computing tools. The solar radiations, temperature, photoperiod, humidity, and wind are some of the important environmental variables which interact with agricultural system. These variables should be considered with importance for understanding the agricultural system on scientific basis. The light required is for photosynthesis and photoperiod, humidity for determination of water loss, and wind to transfer water vapors and gases to and from plants. The model converts qualitative data into quantitative to give out quantitative predictions to the theories which can be compared very easily in the real world. There is rich future for systems modeling, and it can open new frontiers and helps in the agroecological transitions of agriculture. Plants and crops should be considered as holobionts (individual host and its microbial community). In system modeling, the environmental variables are linked to various physiological processes to predict the crop responses with a given set of environmental conditions. The increased ozone concentration in the environment also damages the crop, and these impacts should be considered during model development. Similarly, application of different models at different scales is presented which could help to understand the mechanisms in qualitative and quantitative way. Last but not least, the concept of digital agriculture and its linkage with modeling were elaborated. In general the chapter discusses in detail the type, methods of measurement along with mathematical representation, terminologies, and their impact on the various processes of the plants.