| Popis: |
The use of technology for the purpose of improving crop yields, quality and quantity of the harvest, aswell as maintaining the quality of the crop against adverse environmental elements (such as rodent orinsect infestation, as well as microbial disease agents) is becoming more critical for farming practiceworldwide. One of the technology areas that is proving to be most promising in this area is artificialintelligence, or more specifically, machine learning techniques. This chapter aims to give the reader anoverview of how machine learning techniques can help solve the problem of monitoring crop quality anddisease identification. The fundamental principles are illustrated through two different case studies, oneinvolving the use of artificial neural networks for harvested grain condition monitoring and the otherconcerning crop disease identification using support vector machines and k-nearest neighbor algorithm. |
