Artificial Neural Network Identification of the Chemical and Crystallinity of Pine Needle Fiber at Different Altitudes in India's Garhwal Region

Pine needles are found at various altitudes in the Himalayas' Garhwal region. This study examined how altitude affects the chemical composition and crystallinity of pine needle fibre. Multiplelocations in the Garhwal area of Uttarakhand were chosenwith an elevation from600to 2,000 metres above sea level (masl). The pine needle fiber (PNF) was collected from these locations using an altimeter, and their chemical composition, crystallinity index (CI) and crystal size (CS) were investigated. It was found that fibers grown at higher altitude locations exhibited improved properties compared to those grown at lower altitude locations. Moreover, the degree of crystallinity of the fibers increased with altitude, indicating that pine needle fibers collected from higher altitudes may have a more significant potential for use in various applications. Artificial Neural Networks (ANN) based model is developed to predict the properties of fibers from various altitudes. According to the findings, the ANN model successfully predicted the occurrence of chemical composition and crystallinity shifts in the fibers as a function of altitude. The findings of this study provide insights into the potential of pine needle fibers as a sustainable and renewable material and highlight the value of artificial neural networks for determining how natural fibers will perform.