Premium
Development of near‐infrared online grading device for long jujube
Author(s) -
Wang Ancheng,
Sheng Ren,
Li Huanhuan,
Agyekum Akwasi Akomeah,
Hassan Md Mehedi,
Chen Quansheng
Publication year - 2020
Publication title -
journal of food process engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.507
H-Index - 45
eISSN - 1745-4530
pISSN - 0145-8876
DOI - 10.1111/jfpe.13411
Subject(s) - grading (engineering) , sugar , computer science , artificial intelligence , engineering , chemistry , food science , civil engineering
Aims Soluble solids content (SSC) is an essential indicator for evaluating the internal quality of fresh jujube, which can be used to classify the quality grade of fresh jujube. Methods In this study, SSC was determined as the research index of the internal quality in Lingwu long jujube to classify their quality grade. The online rapid nondestructive grading device for jujube quality was designed, including the design of the hardware system and a software system. The performance of the device was evaluated by additional samples. Results By grading external samples, the correct rate of classification of SSC was 86.7% (the first, second, and third grade were 100, 85.7, and 71.4%, respectively), and the residual predictive deviation (RPD) value of optimal model was 2.8 (>2.5). Conclusions The acquired results revealed that, the device could be used in production. Practical Applications In this study, we developed an online nondestructive sugar grading device for fresh jujubes, including the design of hardware systems, the development of software systems. NIR spectroscopy technique coupled with chemometric selection method of characteristic variables were used to build a prediction model for SSC in fresh jujubes. In addition, the model and device were evaluated by external samples, the accuracy of the result was high, and it could be used for the grading of the sugar content of fresh jujube and could potentially extend the quality parameter grading applied to other fruit. This study provided the basis for the development of nondestructive rapid grading system related to the quality of fruit and vegetable.