Ganoderma boninense is a causal agent of basal stem rot (BSR) and is responsible for a significant portion of oil palm (Elaeis guineensis) losses, which can reach US$500 million a year in Southeast Asia. At the early stage of this disease, infected palms are symptomless, which imposes difficulties in detecting the disease. In spite of the availability of tissue and DNA sampling techniques, there is a particular need for replacing costly field data collection methods for detecting Ganoderma in its early stage with a technique derived from spectroscopic and imagery data. Therefore, this study was carried out to apply the artificial neural network (ANN) analysis technique for discriminating and classifying fungal infections in oil palm trees at an early stage using raw, first, and second derivative spectroradiometer datasets. These were acquired from 1,016 spectral signatures of foliar samples in four disease levels (T1: healthy, T2: mildly-infected, T3: moderately infected, and T4: severely infected). Most of the satisfactory results occurred in the visible range, especially in the green wavelength. The healthy oil palms and those which were infected by Ganoderma at an early stage (T2) were classified satisfactorily with an accuracy of 83.3%, and 100.0% in 540 to 550 nm, respectively, by ANN using first derivative spectral data. The results further indicated that the sensitive frond number modeled by ANN provided the highest accuracy of 100.0% for frond number 9 compared with frond 17. This study showed evidence that employment of ANN can predict the early infection of BSR disease on oil palm with a high degree of accuracy.

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In general, food packaging is aimed at preventing food degradation caused by physical and chemical processes or microbial contamination, thereby reducing aroma loss and maintaining product quality during its extended shelf life. To achieve this, the movement of water and gases must be restricted by the packaging material, which must simultaneously conform to the physicomechanical requirements (Talegaonkar, Sharma, Pandey, Mishra, & Wimmer, 2017). The petrochemical polymers currently utilized as food packaging are nonrenewable and nonbiodegradable, presenting remarkable threats such as natural resource depletion, energy crises, global warming, and ecological problems pertaining to waste generation and disposal (Sarwar, Niazi, Jahan, Ahmad, & Hussain, 2018). In recent decades, environmental concerns and increasing consumer demand for healthy and nutritious

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