Time series model in forecasting in agriculture basic to advanced

Abstract

Agriculture,the way of life, has advanced from ploughing soil with a stone fitted on a tree-branch drawn by a horse, to monitoring the entire filed with artificial intelligence and drone technology. Thus, the dimension of it has changed a lot during last couple of decades. Agriculture is not confined managing soils only rather understating what actually the factors going on behind producing the ultimate product, yield. Many new tools like biotechnology, nano-technology, machine learning in agriculture and so on have got their massive importance in the advancement of agriculture. Recently, climate change is one of the burgeoning issues in the agricultural sector. It is a big challenge to the scientists and the policy makers to develop a better resilient agriculture under changing climatic scenario. So, advanced agriculture must consider this aspect as well. Biotic stresses due to weeds, insect and diseases are highly responsible to reduce the crop yield. Better understanding the science behind these stresses and development of their management strategies accordingly is also very much needful. Now a days, horticulture sector has emerged out as an important and highly income generating option to the farmers. This particular sector of agriculture has got its advancement a lot in the recent past creating huge employment generations in the nation. A slogan called ‘waste to wealth’ is very much trendy now. In the agricultural sector, nothing is waste actually. The so called waste of agriculture mainly consists of crop residues which can be converted into wealth. In the light of advancement one must not overlook the goal of sustainable agricultural development. Any advancement must be nature and biodiversity saving. All these are the milieu of editing a book entitled, ‘Advanced Agriculture’ which includes the recent advances of agricultural sciences covering the aforementioned topics.