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Prediction of internal compositions change in potato during storage using visible/near-infrared (Vis/NIR) spectroscopy

机译:使用可见/近红外线(VI / NIR)光谱法在储存期间预测储存过程中的内部组合物变化

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摘要

Visible/Near-infrared (Vis/NIR) spectroscopy at a range of 450-1000 nm was used to predict the values of three qualitative variables (starch, reducing sugar, and moisture content) on 200 potato tubers from 2 potato genotypes ('Agria' and 'Clone 397009-8') stored in both traditional and cold storages. After spectroscopy measurements, these variables were measured using reference methods. Then, Partial Least Square (PLS) models were developed. To evaluate developed models, Root Mean Square Error of calibration and cross validation (RMSEC and RMSECV), as well as coefficient of determination for calibration and cross validation (R-C(2) and R-CV(2)), and Residual Predictive Deviation (RPD) were used. The best prediction belonged to reducing sugar with statistical values of R-C(2) = 0.99, R-CV(2) = 0.98, RMSEC = 0.029, RMSECV = 0.037, and RPD = 7.57 in 'Clone' genotype stored under cold storage. The weakest prediction was related to moisture content with statistical values of R-C(2) = 0.93, R-CV(2) = 0.92, RMSEC = 0.268, RMSECV = 0.279, and RPD = 6.45 in stored 'Clone' genotypes under cold storage. Results of the study showed that, Vis/NIR spectroscopy as a non-destructive, fast, and reliable technique can be used for prediction of inner compositions of stored potatoes.
机译:在450-1000nm的范围内的可见/近红外(VI / NIR)光谱法用于预测来自2个马铃薯基因型的200个马铃薯块茎(淀粉,还原糖和水分含量)的值('Agria '和'克隆397009-8')存储在传统和冷库中。在光谱测量后,使用参考方法测量这些变量。然后,开发了部分最小二乘(PLS)模型。为了评估开发的模型,校准和交叉验证的根均方误差(RMSEC和RMSECV),以及校准和交叉验证的确定系数(RC(2)和R-CV(2))和残差预测偏差(使用RPD)。最佳预测属于R-C(2)= 0.99,R-CV(2)= 0.98,RMSEC = 0.029,RMSECV = 0.037和RPD = 7.57的还原糖,并在克隆的基因型下储存在冷藏下的RPD = 7.57。最弱的预测与具有R-C(2)= 0.93,R-CV(2)= 0.92,RMSEC = 0.268,RMSECV = 0.279的统计值的水分含量有关。在冷储存下储存的“克隆”基因型中的RPD = 6.45。该研究的结果表明,VI / NIR光谱作为非破坏性,快速和可靠的技术可用于预测储存土豆的内部组合物。

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