Vis/NIR estimation at harvest of pre- and post-storage quality indices for 'Royal Gala' apple
Vis/NIR estimation at harvest of pre- and post-storage quality indices for 'Royal Gala' apple
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DOI：
10.1016/s0925-5214(01)00180-6
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发表时间：
2002-06-01
影响因子：
7
通讯作者：
Martinsen, PJ
中科院分区：
文献类型：
--
作者：
McGlone, VA;Jordan, RB;Martinsen, PJ
用一台工作在500-1100 nm范围内的低成本快速多色光谱仪对‘皇家嘎拉’苹果进行了可见/近红外(VIS/NIR)光谱测量。光谱测量是对两个种植区的八个果园的水果进行的，在以商业采收期为中心的7周内的两个季节的每个季节。数据分析包括通过化学计量学建模，为收获后立即测量的各种质量指数和冷藏6周后测量的各种质量指数建立预测模型。品质指标包括背景色(BC)、淀粉图谱指数(SPI)、可溶性固形物含量(SSC)、渗透硬度、定量淀粉(QS)和可滴定酸度(TA)。预测模型在回归方面很重要，通常可以解释50%到80%的数据集方差，但它们在预测方面仍然非常差。对于每个品质指标，数据标准差与预测均方根误差的比率(RMSEP)总是远小于3；这个比率值被认为是仅对水果进行粗筛/分级的最小值。大多数预测模型似乎主要依赖于叶绿素吸收峰的变化，在整个采收期期间，叶绿素吸收峰的强度显著降低，而不是直接感兴趣的成分或性质。SSC预测模型是例外，它们在不同程度上依赖于相关的感兴趣的成分(可溶性碳水化合物)。贮藏后的SSC预测要比采收期好得多(RMSEP分别类似于0.50%和0.72%)，这表明，我们从理论上推测，采收期果实中存在的淀粉对SSC模型的混杂影响。(C)2002 Elsevier Science B.V.保留所有权利。
Visible/Near Infrared (Vis/NIR) spectrometric measurements, made with a fast low cost polychromatic spectrometer operating over the range 500-1100 nm, have been made on 'Royal Gala' apples (Malus domestica Borkh.). The spectral measurements were taken on fruit from eight orchards in two growing regions and in each of two seasons through a 7-week period centred around the commercial harvesting period. Data analysis involved creating predictive models, by chemometric modelling, for various quality indices measured both immediately after harvest and after 6 weeks cool storage. The quality indices included background colour (BC), starch pattern index (SPI), soluble solids content (SSC), penetrometer firmness, quantitative starch (QS) and titratable acidity (TA). The predictive models were significant in regression terms, typically explaining between 50 and 80% of the data set variance, but they were, nonetheless, very poor in prediction terms. For each quality index, the ratio of data standard deviation to the root mean square error of prediction (RMSEP) was always well less than 3; a ratio value considered the minimum for only coarse screening/grading of fruit. Most of the prediction models appear to be primarily dependent on changes in the chlorophyll absorbance peak, which dramatically reduces in intensity during the progression of the fruit through the harvest period, rather than on the constituent or property of direct interest. Exceptions were the SSC prediction models that are dependent, to varying degrees, on the relevant constituents of interest (soluble carbohydrates). The SSC predictions were much better post-storage than at harvest time (RMSEP similar to 0.50 and 0.72%, respectively) indicating, we theorise, the confounding influence of starch, present in the fruit at harvest time, on the SSC model. (C) 2002 Elsevier Science B.V. All rights reserved.