Integration of Hyperspectral Imaging and Chemometrics for Internal Quality Evaluation of Packaged and Non-Packaged Fresh Fruits

Umuhoza Aline, Dennis Semyalo, Muhammad Fahri Reza Pahlawan, Tanjima Akter, Mohammad Akbar Faqeerzada, Seo-Young Kim, Dayoung Oh and Byoung-Kwan Cho ()
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Umuhoza Aline: Department of Agricultural Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, Yuseong-gu, Daejeon 34134, Republic of Korea
Dennis Semyalo: Department of Smart Agricultural Systems, College of Agricultural and Life Science, Chungnam National University, Yuseong-gu, Daejeon 34134, Republic of Korea
Muhammad Fahri Reza Pahlawan: Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, Daejeon 34134, Republic of Korea
Tanjima Akter: Department of Smart Agricultural Systems, College of Agricultural and Life Science, Chungnam National University, Yuseong-gu, Daejeon 34134, Republic of Korea
Mohammad Akbar Faqeerzada: Department of Smart Agricultural Systems, College of Agricultural and Life Science, Chungnam National University, Yuseong-gu, Daejeon 34134, Republic of Korea
Seo-Young Kim: Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, Daejeon 34134, Republic of Korea
Dayoung Oh: Department of Biosystems Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, Daejeon 34134, Republic of Korea
Byoung-Kwan Cho: Department of Agricultural Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, Yuseong-gu, Daejeon 34134, Republic of Korea

Agriculture, 2025, vol. 15, issue 16, 1-16

Abstract: Research on packaged fruits has seen a notable upturn primarily driven by consumers’ desire for fruit safety and quality across the distribution network. This study examined the effectiveness of hyperspectral imaging (HSI) combined with chemometrics to assess the internal quality of packaged and non-packaged fresh fruits. Visible–near-infrared (Vis-NIR; 400–1000 nm) and short-wave infrared (SWIR; 1000–2500 nm) hyperspectral images of apples and plums were captured using 200 samples for each fruit across three groups—plastic wrap (PW), polyethylene terephthalate (PET) box, and non-packaged (NP)—for the prediction of soluble solid content (SSC), moisture content (MC), and pH. A partial least square regression (PLSR) model demonstrated promising results on SSC and MC across all sample groups in both Vis-NIR and SWIR, with performance ranked NP > PW > PET. Calibration and prediction coefficients of determination (R 2 ) exceeded 0.82, 0.80, and 0.79, with root mean square errors (RMSE) less than 0.57, 0.59, and 0.59 for NP, PW, and PET, respectively. This research outcome confirmed the suitability of HSI as a critical instrument for predicting the composition of fresh fruits inside plastic packaging, offering a quick and non-invasive approach for quality evaluation in supply chains.

Keywords: hyperspectral imaging; chemometrics; quality; package; fresh fruits (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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