光谱学与光谱分析 |
|
|
|
|
|
Progress in Predicting Animal Feed Intake of Plant Secondary Compounds by Spectral Analysis |
WANG Yuan-su1,2, HONG Fu-zeng1, WANG Kun1* |
1. Institute of Grassland Science, College of Animal Science and Technology, China Agricultural University, Beijing 100094, China 2. Grass and Forage Service Station, Guizhou Province, Guiyang 550001, China |
|
|
Abstract Study on feed intake of phytophagic animals is a key issue in promoting animal productivity and conservation of wild life. However, how to accurately predict the feed intake of grazing animal and wild life is a long remaining problem. Under the mechanism of co-evolution, plant produces secondary compounds such as phenolics, terpenoids and nitrogen-containing compounds to avoid or reduce animal herbivorous damage as a defensive strategy, while animal attained detoxification capacity of bio-transforming and mineralizing the compounds by microbial activities and reactions such as hydrolysis and reduction. The attributes of feedstuff and the amount of a particular feed consumed by the animal affect directly the urinary excretion of secondary metabolites. Plant secondary compounds and their metabolites can be efficiently extracted, separated and structure-identified by spectroscopic analytic method. Then the feed intake of the animal can be accurately measured or predicted by the inference model of concentration-ratio that is based on the regression of correlating the secondary metabolites to the precursors in plant. Aromatic compounds, an universal occurrence in vascular plants, play an important role in predicting feed intake of ruminants. Progresses have been made all-around about the new method. Intensive studies have found that different species and developing stage of plant have varying kinds and levels of secondary compounds, and the age, gender and type of animal have different capacity of metabolizing the compounds. Increasing concentrations of the compounds in the diet led to a dose-dependent decrease in food intake best described as an exponential decay. Animals that had not previously been exposed to the compounds ate significantly more when first offered food containing the compound than on subsequent days. Advanced spectroscopic analytic method has been developed and widely applied in extraction (e.g. microwave assisted extraction and ultrasonic extraction), separation and purification (e.g. paper chromatography, VLC, GC, HSCCC, Micro-LC and HPLC), and structure-identification (e.g. Fourier transform infrared spectroscopy, ultraviolet spectroscopy, and nuclear magnetic resonance spectroscopy) of plant secondary compounds and their metabolites. Studies suggest that some aromatic compounds like phenolic alkaloids, flavonoids, tannins, lignin and N-alkane are suited internal markers and find that the method to predict animal feed intake of plant secondary compound by spectral analysis is quick, accurate and applicable. The further focus should be on selecting appropriate compounds and their fate in metabolizing and excretion, and the development of intelligentized spectroscopy equipments.
|
Received: 2007-01-10
Accepted: 2007-04-20
|
|
Corresponding Authors:
WANG Kun
E-mail: wangkun@cau.edu.cn
|
|
Cite this article: |
WANG Yuan-su,HONG Fu-zeng,WANG Kun. Progress in Predicting Animal Feed Intake of Plant Secondary Compounds by Spectral Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2007, 27(09): 1770-1774.
|
|
|
|
URL: |
https://www.gpxygpfx.com/EN/Y2007/V27/I09/1770 |
[1] LONG Rui-jun, DONG Shi-kui, WANG Yuan-su, et al(龙瑞军, 董世魁, 王元素, 等). Acta Prataculturas Sinica(草业学报), 2003, 12(6): 8. [2] Chung-MacCoubrey, Hagerman A E, Kirkap trick R L. Physiol. Zool., 1997, 7: 270. [3] Fraenkel G S. Science, 1959, 129: 1466. [4] LI Jun-nian, LIU Ji-ke(李俊年, 刘季科). Acta Ecologica Sinica(生态学报), 2002, 22(12): 2186. [5] Singleton V L, Kratzer F H. Journal of Agriculture and Food Chemistry, 1969, 17: 497. [6] Harborne J B. General Procedures and Measurement of Total Phenolics. In: Plant Phenolics, Methods in Plant Biochemistry(Harborne J B, Editor) London, UK: Academic Press, 1989. 1: 1. [7] LONG Rui-jun, WANG Yuan-su, DONG Shi-kui, et al(龙瑞军, 王元素, 董世魁, 等). Acta Prataculturae Sinica(草业学报), 2004, 13(2): 13. [8] Walker J R L. The Biology of Plant Phenolics. London, UK: Edward Arnold, 1975. 34. [9] Jung H G, Fahey G C Jr. Journal of Animal Science, 1983, 57: 206. [10] Yoshida S, Tazaki K, Minamikawa T. Phytochemistry, 1975, 14: 195. [11] Provenza F D, Villalba J J, Dziba L E, et al. Small Ruminant Research, 2003, 49(3): 257. [12] Stapley J, Filey W J, Cunningham R, et al. Journal of Comparative Physiology, 2000, 170(3): 211. [13] Lawler I R, Eschler B M, Schliebs D M, et al. Journal of Chemical Ecology, 1999, 25(11): 2561. [14] LONG Rui-jun, WANG Yuan-su, DONG Shi-kui, et al(龙瑞军, 王元素, 董世魁, 等). Acta Zoonutrimenta Sinica(反刍动物营养学报), 2004, 16(3): 13. [15] Brett A D, Hagerman A E, Barrett W. J. Mamm., 1994, 75: 880. [16] Hagerman A E, Robbins C T. Can. J. Zool., 1993, 71: 628. [17] Duncan A J, Frutos P, Young S A. British Journal of Nutrition, 2000, 83(1): 59. [18] Sorensen J S, Turnbull C A, Dearing M D. Physiological and Biochemical Zoology, 2004, 77(1): 139. [19] Matson K D, Millam J R, Klasing K C. Applied Animal Behaviour Science, 2004, 85(1-2): 141. [20] Wiggins N L, McArthur C, McLean S, et al. Journal of Chemical Ecology, 2003, 29(6): 1447. [21] Villalba J J, Provenza F D, Banner R E. Journal of Animal Science, 2002, 80(2): 3154. [22] Scott T W, Ward P F V, Dawson R M C. Biochemical Journal, 1964, 90: 12. [23] Martin A K. British Journal of Nutrition, 1973, 24: 943. [24] Schiemann R, Zelck U, Nehring K. Archives Für Tierernhrung, 1965, 15: 81. [25] Blaxter K L, Wainman F W, Davidson J L. Animal Production, 1966, 8: 75. [26] Vercoe J E. Journal of Agricultural Science, 1976, 86: 613. [27] Streeter C L. Journal of Animal Science, 1969, 29: 757. [28] Dove H, Mayes R W. Journal of Nutrition, 1996, 126: 13. [29] CHEN Ye-gao(陈业高). Plant Chemical Component(植物化学成分). Beijing: Chemical Industry Press(北京: 化工出版社), 2004. 41. [30] Utsumi S A, Cibils A F, Estell R E, et al. Rangeland Ecology and Management, 2006, 59(6): 668. [31] ZHAO Hong-wei, WANG Wen-feng, YAO Si-de(赵红卫, 王文锋, 姚思德). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2006, 26(11): 1969. [32] FENG Su-ling, TANG Jun-ming, FAN Jing(冯素玲,汤俊明,樊 静). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2003, 23(2): 322. [33] SHEN Qi-rong, XU Yong, YANG Hong, et al(沈其荣, 徐 勇, 杨 红, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2005, 25(2): 211. [34] LIU Xian, HAN Lu-jia(刘 贤, 韩鲁佳). Spectroscopy and Spectral Analysis (光谱学与光谱分析), 2006, 26(11): 2016. [35] WANG Qiang, MA Pei-sheng, TANG Hong-mei, et al(王 强, 马沛生, 汤红梅, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2006, 26(5): 899. [36] HUI Rui-hua, HOU Dong-yan, LI Tie-chun, et al(回瑞华, 侯冬岩, 李铁纯, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2006,26(9): 1753. [37] LIN Li-jun, ZHANG Ying-jun(林立军, 张英俊). Acta Prataculturae Sinica(草业学报), 2006, 15(4): 115. [38] ZHAO Xiao-hong, LIU Guang-ping, MA Ze-fang(赵晓虹,刘广平,马泽芳). Journal of Northeast Forestry University(东北林业大学学报), 2001, 29(2): 67. |
[1] |
FAN Ping-ping,LI Xue-ying,QIU Hui-min,HOU Guang-li,LIU Yan*. Spectral Analysis of Organic Carbon in Sediments of the Yellow Sea and Bohai Sea by Different Spectrometers[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 52-55. |
[2] |
YANG Chao-pu1, 2, FANG Wen-qing3*, WU Qing-feng3, LI Chun1, LI Xiao-long1. Study on Changes of Blue Light Hazard and Circadian Effect of AMOLED With Age Based on Spectral Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 36-43. |
[3] |
BAO Hao1, 2,ZHANG Yan1, 2*. Research on Spectral Feature Band Selection Model Based on Improved Harris Hawk Optimization Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 148-157. |
[4] |
HAO Zi-yuan1, YANG Wei1*, LI Hao1, YU Hao1, LI Min-zan1, 2. Study on Prediction Models for Leaf Area Index of Multiple Crops Based on Multi-Source Information and Deep Learning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3862-3870. |
[5] |
LI Qi-chen1, 2, LI Min-zan1, 2*, YANG Wei2, 3, SUN Hong2, 3, ZHANG Yao1, 3. Quantitative Analysis of Water-Soluble Phosphorous Based on Raman
Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3871-3876. |
[6] |
LIANG Jin-xing1, 2, 3, XIN Lei1, CHENG Jing-yao1, ZHOU Jing1, LUO Hang1, 3*. Adaptive Weighted Spectral Reconstruction Method Against
Exposure Variation[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3330-3338. |
[7] |
ZHANG Jun-he, YU Hai-ye, DANG Jing-min*. Research on Inversion Model of Wheat Polysaccharide Under High Temperature and Ultraviolet Stress Based on Dual-Spectral Technique[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2705-2709. |
[8] |
MA Qian1, 2, YANG Wan-qi1, 2, LI Fu-sheng1, 2*, CHENG Hui-zhu1, 2, ZHAO Yan-chun1, 2. Research on Classification of Heavy Metal Pb in Honeysuckle Based on XRF and Transfer Learning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2729-2733. |
[9] |
HUANG Chao1, 2, ZHAO Yu-hong1, ZHANG Hong-ming2*, LÜ Bo2, 3, YIN Xiang-hui1, SHEN Yong-cai4, 5, FU Jia2, LI Jian-kang2, 6. Development and Test of On-Line Spectroscopic System Based on Thermostatic Control Using STM32 Single-Chip Microcomputer[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2734-2739. |
[10] |
ZHENG Yi-xuan1, PAN Xiao-xuan2, GUO Hong1*, CHEN Kun-long1, LUO Ao-te-gen3. Application of Spectroscopic Techniques in Investigation of the Mural in Lam Rim Hall of Wudang Lamasery, China[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2849-2854. |
[11] |
WANG Jun-jie1, YUAN Xi-ping2, 3, GAN Shu1, 2*, HU Lin1, ZHAO Hai-long1. Hyperspectral Identification Method of Typical Sedimentary Rocks in Lufeng Dinosaur Valley[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2855-2861. |
[12] |
WANG Jing-yong1, XIE Sa-sa2, 3, GAI Jing-yao1*, WANG Zi-ting2, 3*. Hyperspectral Prediction Model of Chlorophyll Content in Sugarcane Leaves Under Stress of Mosaic[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2885-2893. |
[13] |
LI Xin-xing1, 2, ZHANG Ying-gang1, MA Dian-kun1, TIAN Jian-jun3, ZHANG Bao-jun3, CHEN Jing4*. Review on the Application of Spectroscopy Technology in Food Detection[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2333-2338. |
[14] |
LIU Zhao1, 2, LI Hua-peng1, CHEN Hui1, 2, ZHANG Shu-qing1*. Maize Yield Forecasting and Associated Optimum Lead Time Research Based on Temporal Remote Sensing Data and Different Model[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(08): 2627-2637. |
[15] |
FENG Ying-chao1, HUANG Yi-ming2*, LIU Jin-ping1, JIA Chen-peng2, CHEN Peng1, WU Shao-jie2*, REN Xu-kai3, YU Huan-wei3. On-Line Monitoring of Laser Wire Filling Welding Process Based on Emission Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1927-1935. |
|
|
|
|