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Assessment of firmness and soluble solids content of peaches by spatially resolved spectroscopy with a spectral difference technique

Computers and Electronics in Agriculture. · 1 Sept 2022 · 10.1016/j.compag.2022.107212

Abstract

Spatially resolved spectroscopy (SRS) provides a new approach to the measurement of optical scattering and absorption properties and quality assessment of horticultural products. In this research, spatially resolved (SR) spectra over 550 – 1,650 nm were acquired for 600 peaches using a recently developed SRS system covering the light source-detector (S-D) distances from 1.5 to 36 mm with 30 fibers of three sizes (i.e., 50 µm, 105 µm and 200 µm). A new method of calculating spectral differences, between the first S-D distance and the remaining 14 S-D distances was proposed to enhance firmness and soluble solids content (SSC) predictions. Partial least squares (PLS) regression models based on SR and difference reflectance (DR) spectra were developed and compared for firmness and SSC prediction. Results showed that when using SR spectra, prediction results for firmness and SSC varied greatly with the S-D distance; SSC prediction results became worse with the increasing S-D distance, while larger S-D distances of 12–32 mm resulted in better firmness predictions. DR spectra gave consistently better results for both firmness and SSC predictions than SR spectra, with the best correlation coefficients of 0.853 and 0.839 for firmness and SSC prediction, respectively. Overall, SRS coupled with the spectral difference technique can enhance the prediction of firmness and SSC for peach fruit.

Plant phenotyping relevance

桃果実の硬度と可溶性固形分という植物器官形質を、空間分解分光法と新規スペクトル差分手法で推定することが研究の中心であり、予測モデルの比較評価も行っている。

abstractA new method of calculating spectral differences, between the first S-D distance and the remaining 14 S-D distances was proposed to enhance firmness and soluble solids content (SSC) predictions.
abstractOverall, SRS coupled with the spectral difference technique can enhance the prediction of firmness and SSC for peach fruit.

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