摘要
梨是生活中非常常见的水果,梨的糖度、酸度(pH)、硬度是评价梨品质的重要指标。近红外光谱技术因快速、无损和高效等优点,广泛应用于检测水果品质指标。手持式近红外光谱仪可以应用于现场无损检测梨品质,梨的大小不同会对梨的光谱和建模产生一定影响。因此,采集大小不同的5个品种梨果(雪梨、红香酥、蜜梨、红肖梨、酸梨)的近红外光谱,最大的雪梨平均赤道周长27.64 cm,重量为362.84 g,最小的蜜梨平均赤道周长18.35 cm,重量为112.67 g,共197个样品。光谱范围为900~1700 cm^(-1),并在梨的赤道上选取三个点测量梨果的可溶性固形物、酸度(pH)与硬度三个化学指标。采集光谱发现,小梨吸光度较大,而大梨吸光度较小。采用三点平均光谱代表样品光谱和一阶导预处理,改善了光谱的一致性,解决了样品不均匀性、不同梨大小不同等因素的影响。线性回归模型PLS可溶性固形物、酸度(pH)和硬度的校正集决定系数依次为0.7394、0.9335、0.8866,预测集决定系数依次为0.7559、0.8734、0.7874,校正集RMSEC依次为0.5504、0.1941、0.5181。预测集RMSEP依次为0.6564、0.2420、0.6692。非线性回归LSSVM模型可溶性固形物、酸度(pH)和硬度的校正集决定系数依次为0.9763、0.9999、0.9960,预测集决定系数依次为0.9234、0.9777、0.9394,校正集RMSEC依次为0.1949、0.0033、0.0894。预测集RMSEP依次为0.3169、0.1089、0.3613。对比线性算法和非线性算法,LS-SVM建模效果明显优于PLS,LS-SVM算法适用于更多的品种、更宽的品质指标范围的样品预测,模型的准确度和稳定性有了显著提高,可以建立不同品种大小的梨的通用模型。手持式近红外光谱仪可用于梨果的糖度、硬度和pH值的快速无损高效检测,并摆脱了实验室的限制,可以实现现场快速检测。
Pear is a very common fruit in life and one of the three major fruits in China.The sugar content,acidity(pH)and hardness of the pear are important indexes to evaluate the quality of the pear.Near infrared spectroscopy(NIR)is widely used to detect the quality of fruits because of its fast,non-destructive and high efficiency advantages.The hand-held near-infrared spectrometer can be applied to the on-site nondestructive testing of pear quality.Different pear sizes will have a certain impact on the spectrum and modeling of pears.The near-infrared spectra of five pear varieties(Sydney,Hongxiangsu,Honey pear,Hongxiao pear and Sour pear)with different sizes are collected.The largest pear,Sydney has an average equatorial circumference of 27.64 cm and a weight of 362.84 g.The smallest pear has an average equatorial circumference of 18.35 cm and a weight of 112.67 g.A total of 197 samples.The spectral range is 900~1700 cm^(-1),three points were selected on the equator of the pear to measure the three chemical indexes of the pear fruit:soluble solids,acidity(PH)and hardness.It was found that the absorbance of small pear was higher than that of large pears.The three-point average spectrum is used to represent the spectrum of the sample and the first-order derivative pretreatment,which improves the consistency of the spectrum,and solves the influence of factors such as sample heterogeneity and different pear sizes.The determination coefficients of the correction set of the linear regression model PLS for soluble solids,acidity(pH)and hardness were 0.7394,0.9335,0.8866,0.7559,0.8734,0.7874,and 0.5504,0.1941,0.5181,respectively.The RMSEP of the prediction set is 0.6564,0.2420 and 0.6692 respectively.The determination coefficients of the calibration set of the nonlinear regression model LSSVM for soluble solids,acidity(pH)and hardness are 0.9763,0.9999 and 0.9960 respectively,the determination coefficients of the prediction set are 0.9234,0.9777 and 0.9394 respectively,and the RMSEC of the calibration set is 0.1949,0.0033 and 0.0894 respectively.The RMSEP of the prediction set is 0.3169,0.1089 and 0.3613 in order.Compare linear algorithm with the nonlinear algorithm;the LS-SVM modeling effect is better than PLS.The LS-SVM algorithm ensures that the model is applicable to the prediction of more varieties and a wider quality index range.The accuracy and stability of the model have been significantly improved.It can establish a general model for pears of different varieties and sizes.The handheld near-infrared spectrometer can be used for the rapid,non-destructive and efficient detection of sugar,hardness and pH value of pear fruits,and it has got rid of the limitations of the laboratory.It can realize on-site rapid detection.
作者
毛欣然
夏静静
徐惟馨
韦芸
陈玥瑶
陈月飞
闵顺耕
熊艳梅
MAO Xin-ran;XIA Jing-jing;XU Wei-xin;WEI Yun;CHEN Yue-yao;CHEN Yue-fei;MIN Shun-geng;XIONG Yan-mei(College of Science,China Agricultural University,Beijing 100193,China)
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2024年第2期406-412,共7页
Spectroscopy and Spectral Analysis
基金
国家自然科学基金项目(31301685)资助。
关键词
手持式近红外仪
梨
偏最小二乘法
最小二乘支持向量机
Portable near-infrared spectrometer
Pear
Partial least square
Least squares-support vector machine