Establishment of Quantitative Model for Six Chemical Compositions in Crassostrea Angulata by Near Infrared Spectroscopy
HUANG Guan-ming1, GUO Xiang2, QI Jian-fei2, NING Yue2, WU Qi-sheng2, WANG Xiao-qing1*, ZENG Zhi-nan2*, ZHU Li-yan3
1. College of Animal Science and Technology, Hunan Agricultural University, Changsha 410128, China
2. Fisheries Research Institute of Fujian, Xiamen 361013, China
3. Central Laboratory, Fujian Anjoy Foods Holdings Co., Ltd., Xiamen 361028, China
Abstract：Crassostrea angulata is the main variety of marine aquaculture in southern China. Due to long-term artificial breeding with no germplasm protection measures, its germplasm resources are declining, which has a negative impact on the oyster consumption market. Therefore, it is urgent to develop breeding of Crassostrea angulata (C. angulata). The selection for C. angulata with good nutrition and good flesh quality requires a large number of samples in the nutrient analysis. Traditional laboratory chemical method is time-consuming and costly, so we are looking for an efficient method for determining the chemical content of C. angulata. The spectroscopic scan was carried out using 105 frozen-dried and grinded C. angulata samples (removed the adductor muscle) from six regions with the Fouriernear-infrared spectrometer (Thermo Fisher, USA) in this study. By comparing the spectroscopic scan data to the chemical values, the accuracy of the content predictions of protein, glycogen, taurine, zinc, selenium and calcium in C. angulata obtained by near-infrared spectroscopy (NIRS) was studied. Using TQ Analyst (Thermo Fisher, USA) software, and selecting partial least squares (PLS), spectral preprocessing method like multiplication scattering correction (MSC), 1st derivative, and Norris derivative filter, the near-infrared models of the six components were established. And 1/3 of the total samples were selected as validation samples. The models were validated by external and cross validation. The correlation coefficients of calibration (RC) of the six models of protein, glycogen, taurine, zinc, selenium and calcium were 0.985 3, 0.965 1, 0.950 4, 0.955 4, 0.920 0 and 0.925 2, respectively. The correlation coefficients of prediction (RP) were 0.985 1, 0.963 6, 0.944 1, 0.946 1, 0.919 0 and 0.924 1, respectively. The correlation coefficients of cross validation (RCV) were 0.981 7, 0.946 1, 0.900 5, 0.897 5, 0.875 3 and 0.829 2, respectively. The results showed that the predicted values of the models had a high correlation with the chemical values, which indicated the NIRS could accurately predict the contents of protein, glycogen, taurine, zinc, selenium and calcium in C. angulata. The samples in this study had good representativeness. The collection time was long. The production area was wide and the quantity was large. The samples were frozen-dried, which reduced the influence of water on the spectral quality. Thus, the accuracy and stability of the models were improved. Spectroscopic scan and analysis based on NIRS was very efficient with no chemical reagents and low cost. The established quantitative model for 6 chemical compositions in C. angulata by NIRS would have a great significance for large-scale analysis of the nutritional compositions and for the selection of new strains with good flesh quality in C. angulata.
黄冠明，郭 香，祁剑飞，宁 岳，巫旗生，王晓清，曾志南，朱礼艳. 葡萄牙牡蛎（Crassostrea angulata）六种化学成分近红外定量模型的建立[J]. 光谱学与光谱分析, 2020, 40(05): 1509-1513.
HUANG Guan-ming, GUO Xiang, QI Jian-fei, NING Yue, WU Qi-sheng, WANG Xiao-qing, ZENG Zhi-nan, ZHU Li-yan. Establishment of Quantitative Model for Six Chemical Compositions in Crassostrea Angulata by Near Infrared Spectroscopy. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(05): 1509-1513.
[1] ZENG Zhi-nan, NING Yue(曾志南, 宁 岳). Marine Sciences(海洋科学), 2011, 35(9): 112.
[2] SU Jia-qi, WANG Zhao-ping, ZHANG Yue-huan, et al(苏家齐, 王昭萍, 张跃环，等). Journal of Fisheries of China(水产学报), 2015, 39(3): 353.
[3] ZHENG Huai-ping, WANG Di-wen, LIN Qing, et al(郑怀平, 王迪文, 林 清，等). Journal of Fisheries of China(水产学报), 2012, 36(2): 210.
[4] ZENG Zhi-nan, NING Yue, QI Jian-fei, et al(曾志南, 宁 岳, 祁剑飞，等). Cultivation of a New Strain of Crassostrea Angulata with Golden Yellow Sheel(一种贝壳金黄色速长葡萄牙牡蛎新产品系的培养方法). Chinese Patent(中国专利): ZL 2014 1 0197671. 1 [P]. 2015-08-26.
[5] QI Jian-fei, WU Qi-sheng, NING Yue, et al(祁剑飞, 巫旗生, 宁 岳，等). Journal of Xiamen University·Natural Science(厦门大学学报·自然科学版), 2019, 58(2): 276.
[6] WANG Wei-jun, YANG Jian-min, DONG Ying-hui, et al(王卫军, 杨建敏, 董迎辉，等). Oceanologia et Limnologia Sinica(海洋与湖沼), 2015, 46(4): 845.
[7] Zhou L J, Wu H, Li J T, et al. Meat Science, 2012, 90(3): 658.
[8] Zang H C, Li L, Wang F S, et al. Journal of Pharmaceutical and Biomedical Analysis, 2012, 61: 224.
[9] Rosales A, Galicia L, Oviedo E, et al. Journal of Agricultural & Food Chemistry, 2011, 59(20): 10781.
[10] Wang W J, Yang J M, Li Q, et al. Journal of Shellfish Research, 2015, 34(2): 303.
[11] Tögersen G, Arnesen J F, Nilsen B N, et al. Meat Science, 2003, 63(4): 523.
[12] WANG Xiao-xiao, LI Jun-tao, SUN Xiang-li, et al(王潇潇, 李军涛, 孙祥丽，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2018, 38(1): 58.
