Investigation on metal sulfide reduced graphene oxide nanocomposites for energy storage and green vehicle applications

Abstract

A major issue in agriculture is the need to cope up with plant diseases. Adequate expertise and domain knowledge are required to handle diseases effectively in this field. The automatic detection of plant diseases is necessary, as it reduces the tedious work of monitoring large farms and detects the disease at an early stage of its occurrence to minimize further degradation of plants. The production of fruits and crops across the globe is highly influenced by various diseases. A decrease in production leads to an economic degradation of the agricultural industry worldwide. Apple trees are cultivated worldwide, and apple is one of the most widely eaten fruits in the world. The world produced an estimation of 86 million tons of apples in 2018, the production and consumption have increased ever since. However, the average national yield of apples is low in comparison to the potential yield of apples. The major factors for the low production of apples are ecological factors, poor post-harvest technologies, less thrust on basic research, inadequate supply of quality planting materials to farmers and socio-economic constraints, etc. Despite their high consumption and medicinal benefits, apple trees are prone to a variety of diseases caused due to insects and micro-organisms such as bacteria. There are several diseases which attack apple, the major ones are cedar apple rust, fireblight, scab and powdery mildew. The proper care of trees using fertilizers is thus an important step. A timely detection of such conditions in the leaves can help the farmers and prevent further losses by taking proper actions. Using just the traditional approaches for diagnosing the plant s disease, farmers often miss the ideal time for preventing such diseases, because the use of these conventional diagnostic approaches takes a lot of time. Currently, there are no automated procedures for such timely detection, and expert supervision is required frequently newline