Quantitative evaluation of food-waste components in organic fertilizer using visible–near-infrared hyperspectral imaging

Authors: KIM, GEONWOON - Us Forest Service (FS); LEE, HOONSOON - Chungbuk National University; CHO, BYOUNG-KWAN - Chungnam National University; BAEK, INSUCK - Orise Fellow; Kim, Moon

Submitted to: Applied Sciences
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/1/2021
Publication Date: 9/3/2021
Citation: Kim, G., Lee, H., Cho, B., Baek, I., Kim, M.S. 2021. Quantitative evaluation of food-waste components in organic fertilizer using visible–near-infrared hyperspectral imaging. Applied Sciences. 11(17):8201. https://doi.org/10.3390/app11178201.
DOI: https://doi.org/10.3390/app11178201

Interpretive Summary: Recycling food waste (FW) as a component of organic fertilizer (OF) is one means of reducing food waste volumes to be incinerated or dumped in landfills while reclaiming nutrients useful for agricultural soils. However, excessive amounts of FW in OF can cause imbalances that harm plant growth. South Korea has established maximum allowable FW content in OF, in part due to the high concentrations of sodium chloride in many traditionally fermented and preserved foods commonly used in Korean cuisine. Enforcing such restrictions requires methods of evaluating food waste components (FWC) in OF. This study developed a method based on visible/near-infrared hyperspectral imaging to evaluate FWC levels in OF. The resulting high correlation between predicted and actual values of FWC demonstrate the potential of the method for quantitative evaluation of FWC content of organic fertilizers, for benefits in waste reduction for the environment, quality control for fertilizer producers, and plant health for agricultural producers.

Technical Abstract: Excessive addition of food waste fertilizer to organic fertilizer (OF) is forbidden in the Republic of Korea because of high sodium chloride and capsaicin concentrations in Korean food. Thus, rapid and nondestructive evaluation techniques are required. The objective of this study is to quantitatively evaluate food-waste components (FWCs) using hyperspectral imaging (HSI) in the visible–near-infrared (Vis/NIR) region. A HSI system for evaluating fertilizer components and prediction algorithms based on partial least squares (PLS) analysis and least squares support vector machines (LS-SVM) are developed. PLS and LS-SVM preprocessing methods are employed and compared to select the optimal of two chemometrics methods. Finally, distribution maps visualized using the LS-SVM model are created to interpret the dynamic changes in the OF FWCs with increasing FWC concentration. The developed model quantitatively evaluates the OF FWCs with a coefficient of determination of 0.83 between the predicted and actual values. The developed Vis/NIR HIS system and optimized model exhibit high potential for OF FWC discrimination and quantitative evaluation.