Effectiveness of the Forest Pests and Diseases Control Methods on the Amount of Industrial Wood Production: A Deep Learning Analysis

Abstract

Abstract Industrial wood production is a critical component of many countries, providing raw materials for a range of products like construction materials, paper, and pulp. However, the industry faces various challenges, including the impact of forest pests and diseases on timber quality and yield. These threats can lead to significant economic losses for the wood products industry. Thus, effective pest and diseases control strategies are crucial for ensuring sustainable industrial wood production. These strategies typically involve a combination of preventative and control measures, including the use of mechanical, chemical, biotechnical, and biological control methods. The constructed deep learning model shows that all methods have enhancer effects on the amount of industrial wood, albeit at different levels. Thus, the most effective methods in terms of increasing industrial wood production are chemical control methods, while the second most effective methods are mechanical control methods. The third effective methods, on the other hand, are biological control methods. However, biotechnical methods were found to be the least effective methods compared to the other ones.