Abstract：In the process of chicken egg hatching, some eggs can not be hatched successfully due to the absence of fertilization. These eggs not only cause a lot of waste, but also infect other normal eggs with bacteria. In the study, the fertilized eggs and clear eggs is identified by using the visible/near-infrared spectrum. It is of great necessity to get the best time of identifying the clear eggs in the early of hatching, so the variation of eggs’ quality in the condition of hatching over time is studied. The results show that eggs are fresh after 24 hours’ hatching and eggs can not be eaten after 72 hours’ hatching while the best time of identification is within 36 hours. Static acquisition system is developed based on visible/near-infrared transmission spectrum for acquiring spectrum. Comparing the effect of the model of the different samples of same breed and samples of different breed, the different part of spectrum among fertilized eggs and clear eggs is deleted which caused by the color of eggshell and yolk, the effective spectral band are 355～590 and 670～1 025 nm. Adopting the pretreatment of PCA and comparing the accuracy of the various mathematical models with different time and the number of principal components decide the best number of principal components. Considering the production efficiency and comparing the different pretreatment methods of spectrum, for examples, SNV, MSC, Derivative correction and PCA, and various mathematical models are combined to establish the most efficient discriminant model. The result shows that the most efficient discriminant model is established with Fisher and based on the pretreatment of PCA after 24 hours’ hatching. And the precision rate is 87.18%. The study provides a new way for nondestructive and online identification of the fertilized eggs and clear eggs.
[1] Elster R T, Goordurm J W. Transactions of the ASAE, 1991, 34(1): 307. [2] Das K, Evans M D. Transaction of the ASABE, 1992, 35(4): 1335. [3] Klein S, Rokitta M, Baulain U, et al. Worlds Poultry Science Journal, 2003, 59(1): 39. [4] SHEN Lin-sheng, CHEN Ning, WANG Guang-liang(沈林生，陈 宁，王光亮). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 1996, 3(12): 163. [5] Bamelis F R, Tona K, De Baerdemaeker J G, et al. British Poultry Sicece, 2002, 43(2): 204. [6] ZOU Xiu-rong, PAN Lei-qing, TU Kang, et al(邹秀容, 潘磊庆, 屠 康，等). Science and Technology of Food Industry(食品工业科技), 2010, 2(89): 342. [7] HUANG Wen-qian, CHEN Li-ping, LI Jiang-bo, et al(黄文倩, 陈立平, 李江波，等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2013, 29(1): 272. [8] Jie Dengfei, Xie Lijuan, Rao Xiuqin, et al. Postharvest Biology and Technology, 2014, 90: 1. [9] Xie Lijuan, Ying Yibin, Ying Tiejin. Chemometrics and Intelligent Laboratory Systems, 2009, 97: 141. [10] Nicolas A N, Michael N, Shiv P. Food Bioprocess Technol., 2009, (1): 265. [11] Monira K N, Salahuddin M, Miah G. International Journal of Poultry Science, 2003, 2(4): 261. [12] LIU Mei-yu, LIAN Hai-ping, REN Fa-zheng(刘美玉，连海平，任发政). Food Science(食品科学), 2011, 32(06): 270.
