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Utilizing Near-Infrared (NIR) Technology to Predict the Quality Index (Qi) Model of Barhi Dates Fruit at Khalal Stage Stored in a Controlled Environment
Alhamdan, A.M. Utilizing VIS-NIR Technology to Generate a Quality Index (Qi) Model of Barhi Date Fruits at the Khalal Stage Stored in a Controlled Environment. Foods2024, 13, 345.
Alhamdan, A.M. Utilizing VIS-NIR Technology to Generate a Quality Index (Qi) Model of Barhi Date Fruits at the Khalal Stage Stored in a Controlled Environment. Foods 2024, 13, 345.
Alhamdan, A.M. Utilizing VIS-NIR Technology to Generate a Quality Index (Qi) Model of Barhi Date Fruits at the Khalal Stage Stored in a Controlled Environment. Foods2024, 13, 345.
Alhamdan, A.M. Utilizing VIS-NIR Technology to Generate a Quality Index (Qi) Model of Barhi Date Fruits at the Khalal Stage Stored in a Controlled Environment. Foods 2024, 13, 345.
Abstract
Saudi Arabia is a prominent producers of dates, with 1.6 million tons annually. There is a need to evaluate physical properties and quality of fruits non-destructively and then be modeled and predicted throughout the storage period. The aim of the current study was to generate a quality index (Qi) and Near-infrared spectra (NIR) models non-destructively to predict properties of Barhi dates fruits including objective and sensory evaluations. The engineering properties of Barhi dates were measured and modeled with quality index (Qi) based on NIR of fresh Barhi fruits (hardness, color, TSS, pH, and sensory evaluations) and during storage in cold, ambient, and controlled at-mosphere (CA) for up to four months. The prediction of Qi is non- destructively based on NIR utilizing PLSR and ANN data analysis. The results showed that the Qi generated corresponds with high precision to the characteristics of the examined fruits through the duration of the storage period with R2 of 0.96. The NIR spectrum proves to be an efficient method to evaluate the Barhi fruits' quality index. where ANN was found to be more suitable than PLSR analysis. Thus, NIR can be utilized to accurately predict the Qi of fruits quality effectively throughout the handling, processing, transporting, storage, and retail sector supply chain.
Biology and Life Sciences, Food Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
