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首页> 外文期刊>Chemometrics and Intelligent Laboratory Systems >Optimization and comparison of models for prediction of soluble solids content in apple by online Vis/NIR transmission coupled with diameter correction method
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Optimization and comparison of models for prediction of soluble solids content in apple by online Vis/NIR transmission coupled with diameter correction method

机译:在直径校正法耦合的在线VIS / NIR变速器通过直径校正方法对苹果中可溶性固体含量的模型的优化与比较

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摘要

The online system can achieve high efficiency towards fruit quality determination in postharvest period. Thus, developing online and nondestructive technology for inspecting and grading fruit is meaningful and profitable in the existing robotic sorting systems. In this study, the effect of fruit diameter differences on online prediction of soluble solids content (SSC) of 'Fuji' apples based on visible and near-infrared (Vis/NIR) spectroscopy was studied. Partial least square (PLS) regression was employed to establish calibration models based on three wavelength regions (675-1025, 710-980, 750-1025 nm) and two fruit orientations (stem-calyx axis vertical with stem upward (T1) and stem-calyx axis horizontal with stem towards light source (T2)), respectively. A novel diameter correction method was proposed to reduce the effect of fruit diameter differences on original spectra. Combined with pretreatment and effective wavelength (EWs) selection methods, models were optimized and compared to determine the best calibration strategy. Diffuse transmission spectra in 710-980 nm and diameter correction method with calculated attenuation coefficient were testified much better than other corresponding regions and correction methods, respectively. Baseline offset correction (BOC) and 7-point Savitzky-Golay smoothing (SGS) of pretreatments and competitive adaptive reweighted sampling (CARS) of EWs selection methods were proved to be outstanding among other methods. 59 and 63 EWs achieved the best detection accuracies with correlation coefficient of prediction (r(p)) and root mean square error of prediction (RMSEP) of 0.92 and 0.50 degrees Brix, 0.89 and 0.56 degrees Brix for T1 and T2, respectively. The overall results indicated that online Vis/NIR transmission spectra after BOC and 7-SGS with proposed diameter correction method can make the variation of fruit diameters a small interference for SSC determination, and CARS-PLS would be effective to simplify models and promote computing efficiency to make this nondestructive detection technique promisingly applied.
机译:在线系统可以在采后果实质量测定中实现高效率。因此,在现有的机器人分类系统中开发用于检查和分级果实的无损技术是有意义的,有利可图。在该研究中,研究了基于可见和近红外(VI / NIR)光谱法的果直径差异对“FUJI”苹果可溶性固体含量(SSC)的在线预测的影响。采用部分最小二乘(PLS)回归来建立基于三个波长区域(675-1025,710-980,750-1025nm)和两种果实取向(茎 - 花萼轴线垂直(t1)和茎 - 分别与茎朝向光源(T2)水平的Calyx轴。提出了一种新型直径校正方法,以减少果直径差异对原始光谱的影响。结合预处理和有效波长(EWS)选择方法,进行了优化的模型,以确定最佳校准策略。在710-980nm和具有计算衰减系数的直径校正方法中分别比其他相应的区域和校正方法更好地弥漫透射光谱。证明,EWS选择方法的预处理和竞争自适应重载(CARS)的基线偏移校正(BOC)和7点SAVITZKY-GOLAY平滑(SGS)在其他方法中被证明是出色的。 59和63 EWS实现了具有预测系数的最佳检测精度(R(P))和预测(RMSEP)的根均方误差分别为T1和T2的0.92和0.50度的Brix 0.89和0.56度。总体结果表明,BOC和7-SGS之后的在线VI / NIR传输光谱具有所提出的直径校正方法可以使水果直径的变化对SSC测定的小干扰,并且汽车-PLS将有效简化模型并促进计算效率使这种无损检测技术承诺应用。

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