Seki Hayato, Murakami Haruko, Ma Te, Tsuchikawa Satoru, Inagaki Tetsuya
Institute of Agricultural Machinery, National Agricultural and Food Research Organization, 1-40-2, Nisshin-Cho, Kita-Ku, Saitama City 331-8537, Japan.
Graduate School of Bioagricultural Sciences, Nagoya University, Furo-Cho, Chikusa, Nagoya 464-8601, Japan.
Foods. 2024 Jul 19;13(14):2274. doi: 10.3390/foods13142274.
In recent years, due to breeding improvements, strawberries with low anthocyanin content and a white rind are now available, and they are highly valued in the market. Strawberries with white skin color do not turn red when ripe, making it difficult to judge ripeness. The soluble solids content (SSC) is an indicator of fruit quality and is closely related to ripeness. In this study, visible-near-infrared (Vis-NIR) spectroscopy and near-infrared (NIR) spectroscopy are used for non-destructive evaluation of the SSC. Vis-NIR (500-978 nm) and NIR (908-1676 nm) data collected from 180 samples of "Tochigi iW1 go" white strawberries and 150 samples of "Tochigi i27 go" red strawberries are investigated. The white strawberry SSC model developed by partial least squares regression (PLSR) in Vis-NIR had a determination coefficient of 0.89 and a root mean square error prediction (RMSEP) of 0.40%; the model developed in NIR showed satisfactory estimation accuracy with an of 0.85 and an RMSEP of 0.43%. These estimation accuracies were comparable to the results of the red strawberry model. Absorption derived from anthocyanin and chlorophyll pigments in white strawberries was observed in the Vis-NIR region. In addition, a dataset consisting of red and white strawberries can be used to predict the pigment-independent SSC. These results contribute to the development of methods for a rapid fruit sorting system and the development of an on-site ripeness determination system.
近年来，由于育种改良，现在已有花青素含量低且果皮为白色的草莓，它们在市场上备受青睐。白皮草莓成熟时不会变红，因此难以判断其成熟度。可溶性固形物含量（SSC）是果实品质的一个指标，与成熟度密切相关。在本研究中，可见 - 近红外（Vis - NIR）光谱和近红外（NIR）光谱用于对SSC进行无损评估。研究了从180个“枥木iW1号”白草莓样品和150个“枥木i27号”红草莓样品收集的Vis - NIR（500 - 978 nm）和NIR（908 - 1676 nm）数据。通过偏最小二乘回归（PLSR）在Vis - NIR中建立的白草莓SSC模型的决定系数为0.89，预测均方根误差（RMSEP）为0.40%；在NIR中建立的模型显示出令人满意的估计精度，决定系数为0.85，RMSEP为0.43%。这些估计精度与红草莓模型的结果相当。在Vis - NIR区域观察到了白草莓中花青素和叶绿素色素产生的吸收。此外，由红草莓和白草莓组成的数据集可用于预测与色素无关的SSC。这些结果有助于快速水果分选系统方法的开发以及现场成熟度测定系统的开发。
