摘要
本试验旨在研究应用近红外光谱技术(NIRS)快速测定玉米籽粒粉末CNCPS组分的可行性。试验中65个样品来自黑龙江省,选用偏最小二乘法(PLS)为建模方法,采用二阶导数和Norris导数滤波法处理光谱数据。建立了玉米籽粒粉末常规营养组分和CNCPS体系中各组分的近红外模型,结果如下:
分析常规组分包括:干物质(DM)、粗蛋白质(CP)、粗脂肪(Fat)、粗灰分(Ash)、淀粉(Starch)、中性洗涤纤维(NDF)、酸性洗涤纤维(ADF)、可溶性蛋白(SP)、酸性洗涤不溶蛋白(ADIP)和中性洗涤不溶蛋白(NDIP)。其中,DM、CP、Fat、Ash、Starch、NDF和ADF的决定系数分别为0.9743、0.9683、0.9478、0.9098、0.9777、0.9354和0.9269,标准差(SD)与预测均方根(RMSEP)的比值(SD/RMSEP)分别为3.96、4.78、3.75、4.25、4.13、3.88和3.12。SP的决定系数为0.8575,SD/RMSEP值为3.06。ADIP和NDIP的决定系数分别为0.5319和0.6833,SD/RMSEP值分别为5.50和2.85。
CNCPS体系中蛋白质各组分预测:非蛋白氮部分(PA)、不含非蛋白氮的可溶性粗蛋白(PB_1)、除PA、PB_1、PB_3及PC蛋白以外的粗蛋白(PB_2)、不含PC蛋白中性洗涤不溶蛋白(PB_3)和酸性洗涤不溶蛋白(PC)的决定系数分别为0.57、0.15、0.34、0.71和0.53,SD/RMSEP值分别为3.52、3.25、5.75、3.12、3.24。
CNCPS体系中碳水化合物各组分:快速降解糖(CA)、中速降解淀粉(CB_1)、慢速降解有效细胞壁部分(CB_2)和不可利用的细胞壁部分(CC)的决定系数分别为0.38、0.35、0.12和0.15,SD/RMSEP值分别为2.08、3.22、0.45和0.22。总的碳水化合物(CHO)的决定系数为0.84,SD/RMSEP值为3.83;非结构性碳水化合物(NSC)的决定系数为0.83,SD/RMSEP值为3.69。
以上结果表明,NIRS技术对玉米中常规营养组分有较高的预测能力,但ADL、NDIP和ADIP近红外模型的精度有待进一步提高;NIRS技术对玉米中CNCPS体系中总氮的含量有较高的预测能力,但是对于各个组分来说预测精度有待进一步提高:NIRS技术对玉米CNCPS体系中碳水化合物各组分的预测精度不高,但是对于总的碳水化合物以及非结构性碳水化合物有较高的预测能力。
The objective of this study was to investigate the feasibility of predicting the CNCPS composition of corn by near infrared reflectance spectroscopy. Sixty-five corn samples from Heilongjiang province were used. The partial least square (PLS) regression method, second derivative and Norris derivative filter were applied in the NIRS prediction of CNCPS.
Estimate of com conventional compositions: For Dry matter, Crude Protein, Ash, Fat, Starch, Neutral-detergent Fiber and Acid-detergent Fiber, the determination coefficients were 0.9743, 0.9683, 0.9478, 0.9098, 0.9777, 0.9354 and 0.9269, and the SD/RMSEP values for them were 3.96, 4.78, 3.75, 4.25, 4.13, 3.88 and 3.12, respectively. The determination coefficient and SD/RMSEP value were 0.8575 and 3.06 for soluble protein, but low determination coefficients of 0.5319 and 0.6833 with SD/RMSEP values of 5.50 and 2.85 were observed for acid-detergent insoluble protein and neutral-detergent insoluble protein.
Crude protein is partitioned into five fractions in CNCPS. Fraction A is NPN (PA); Fraction C is unavailable or protein to cell wall (PC); Fraction B_2 is true protein with an intermediate degradation rate (PB_2); Fraction B_1 is rapidly degraded true protein (PB_1); Fraction B_3 is slowly degraded true protein (PB_3). the determination coefficients were 0.57、0.15、0.34、0.71 and 0.53, respectively. The SD/RMSEP value were 3.52、3.25、5.75、3.12 and 3.24, respectively.
Carbohydrates can then be classified according to degradation rate in CNCPS system. Fraction A is fast and is sugars (CA); Fraction B_1 is intermediate and is starch (CB_1); Fraction B_2 is slow and is available cell wall (CB_2); and Fraction C is unavailable cell wall (CC). the determination coefficients were 0.38、0.35、0.12 and 0.15, respectively. The SD/RMSEP value were 2.08、3.22、0.45 and 0.22, respectively. the total carbohydrate (CHO) content in the feedstuff can be estimated (100 - CP - fat - ash), the determination coefficients and the SD/RMSEP value were 0.84 and 3.83, respectively. Nonstructural carbohydrate (NSC) was estimated by NIRS. The determination coefficients and the SD/RMSEP value were 0.83 and 3.69, respectively.
The results of this study indicated that corn nutritive values could be fast and accurately predicted by NIRS. However, this model of ADL, ADIP and NDIP need improve further. The total CP of corn could be quite accurately estimated by NIRS technology. But probably as a consequence of the accumulative errors concerning the different laboratory procedures involved, NIRS technology did not provide accurate estimations of the five CNCPS fractions. As well, the total CHO and NSC of corn could be quite accurately estimated by NIRS technology. However, NIRS technology did not provide accurate estimations of the four CNCPS fractions.
引文
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