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Validation of short wave near infrared calibration models for the quality and ripening of 'Newhall' orange on tree across years and orchards

机译:验证近年果树橙色树木橙色橙色近红外校准模型的短波验证

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摘要

The aim of this research was to test the viability of short wave near infrared spectroscopy (SW-NIRS) for the monitoring of fruit quality and ripening evolution in Algarve Citrus orchards (Citrus sinensis L. Osbeck 'Newhall'). Specifically, we have investigated the robustness of SW-NIRS calibration models in real conditions, that is: i) measurements were performed on tree, at a single location in the fruit equator, in the sunlight and with no temperature equilibration; and ii) with validation through independent data obtained in different years and/or orchards. Calibration models for soluble solids content (SSC), juice pH, titratable acidity (TA), firmness and maturation index (MI = SSC/TA) were built from the spectral data obtained in two orchards with different edaphoclimatic conditions, and in two consecutive years, corresponding to four independent datasets. We propose a method to assess model robustness through the comparison of internal validation (IV: calibration and validation data sets homogeneously sampled from the whole data set) and external validation (EV: calibration and validation data sets corresponding to different orchards and/or years). The method is based on the statistics of the results obtained by either IV and EV when applied to all the possible combinations of the four datasets. The results show that IV overestimates the models' performance relatively to the realistic exercise of EV. Globally, SSC and juice pH were the best performing models, with fair performances in IV and poor performances in EV (example for SSC: (IV/EV): rmsep = 1.00/1.15%, SDR = 1.40/1.13, R-2 = 0.49/0.34). Firmness yielded the worse models, while TA and MI yielded intermediate performances. However, the plots derived from the comparison method suggest a convergence of IV and EV performances for larger numbers of samples, and thus the potential for future continuous model improvement.
机译:该研究的目的是测试短波近红外光谱(SW-NIRS)的活力,以监测果仁果园的水果质量和成熟演变(柑橘Sinensis L. Osbeck'NoWhall')。具体地,我们研究了实际条件下的SW-NIRS校准模型的鲁棒性,即:i)在树木赤道中的单个位置进行测量,在阳光下,没有温度平衡; II)通过在不同年份和/或果园中获得的独立数据进行验证。可溶性固体含量(SSC)的校准模型,果汁pH值,可滴定的酸度(TA),固定和成熟指数(MI = SSC / TA)由两种果园在两种具有不同胶木状况的果园中获得的光谱数据构建,并且连续两年,对应于四个独立数据集。我们提出了一种通过对内部验证的比较来评估模型稳健性的方法(IV:校准和从整个数据集的校准和验证数据集)和外部验证(EV:校准和验证数据集对应于不同的果园和/或/或年) 。该方法基于在应用于四个数据集的所有可能组合时由IV和EV获得的结果的统计数据。结果表明,IV估计了对EV现实运动的模型的性能。在全球范围内,SSC和果汁pH是最好的表现模型,在IV中具有公平性能和EV的差的性能(SSC示例:(IV / EV):RMSEP = 1.00 / 1.15%,SDR = 1.40 / 1.13,R-2 = 0.49 / 0.34)。坚固性产生了更糟糕的型号,而TA和MI则产生中间性能。然而,来自比较方法的地块表明了IV和EV表演的收敛性,用于更大数量的样本,因此是未来连续模型改进的可能性。

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