Application of Near-Infrared Spectroscopy to Management of Vegetation for Natural Grassland
XU Dong-mei1,2,WANG Kun1*
1. Institute of Grassland Science, College of Animal Science and Technology, China Agricultural University, Beijing 100094, China 2. College of Agronomy, Ningxia University, Yinchuan 750021, China
Abstract：Vegetation is a major index for monitoring the grassland condition and productivity. The change in vegetation directly reflects degradation and restoration of grassland ecosystem. It is important to monitoring the information of vegetation changes to prevent degradation and realize sustainable development of grassland. Predication of vegetation was often completed by field investigation and laboratory analysis in the past, and could not satisfy the needs for inspecting of grassland degradation and restoration. Near-infrared spectroscopy (NIRS) is a rapid, convenient, high-efficiency, non-destructive and low-cost analytical technique, and has been widely used in various fields for quantitative and qualitative analysis. It has been one of the most important techniques for monitoring the succession of grassland ecosystem, and has great potential for applying in natural grassland management. Botanical composition is a major index of the vegetation community structure. The change in botanical composition indicates the developing stage of the plant community. Determining the botanical composition during vegetation succession can provide sound basis for establishing feasible measure of grassland management. NIRS can be successfully used as a rapid method to predict the grass, legume and other plant proportion in natural or semi-natural grasslands. The legume content in multi-species mixtures and the species composition in root mixtures can accurately be estimated by means of NIRS. Leaf/stem ratio of grass stands is an important factor affecting forage quality, diet selection, intake, and the intensity of photosynthesis. Estimates of leaf/stem ratios commonly are based on a labor intensive process of hand separating leaf and stem fractions. NIRS can be used successfully to predict leaf/stem ratios and mineral contents. The results of NIRS technique were well correlated with labor separating method. The decomposition of litter in grasslands is an important aspect of material cycle in grassland ecosystem. To study material cycling, especially mineral cycling in grassland ecosystems, it is essential to know the decomposition rate of the litter. NIRS technique can accurately predict the decomposition status of litter and the change of lignin, cellulose, nitrogen, ash and other nutrient contents during the decomposition of litter. NIRS has potential to provide rapid and effective estimates of material cycling in grassland ecosystems to assist managers in establishing application rates of grasslands that fall within productive and environmentally safe levels. The chemical composition of the plants in grassland is an important factor affecting herbivorous intake and material cycle, and is an important parameter in determining the status of degradation and restoration of grassland ecosystems. NIRS has been confirmed as a technique for reliably and accurately determining the dry matter, crude protein, acid detergent fibre, neutral detergent fibre, and certain microelement contents. With the development of spectral technique, the NIRS method will be more widely used in vegetation management.
[1] WANG Duo-jia, ZHOU Xiang-yang, JIN Tong-ming, et al(王多加, 周向阳, 金同铭, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2004, 24(4): 447. [2] Garcia C B, Garcia C A, Perez C M E. Journal of the Science of Food and Agriculture, 1991, 57(4): 507. [3] Locher F, Heuwinkel H, Gutser R, et al. Agronomy Journal, 2005, 97(1): 11. [4] Wachendorf M, Ingwersen B, Taube F. Grass and Forage Science, 1999, 54(1): 87. [5] Pitman W D, Piacitelli C K, Aiken G E, et al. Agronomy Journal, 1991, 83(1): 103. [6] Roumet C, Picon C C, Dawson L A, et al. New Phytologist, 2006, 170(3): 631. [7] Sheppard J K, Lawler I R, Marsh H. Estuarine Coastal and Shelf Science, 2007, 71(1-2): 117. [8] Atkinson M D. Aspects of Applied Biology, 1996, 44: 431. [9] Hill N S, Peterson J C, Stuedemann J A, et al. Crop Science, 1988, 28: 354. [10] Smart A J, Schacht W H, Moser L E, et al. Agronomy Journal, 2004, 96(1): 316. [11] Smart A J, Schacht W H, Pedersen J F, et al. Journal of Range Management, 1998, 51(4): 447. [12] Couteaux M M, McTiernan K B, Berg B, et al. Soil Biology & Biochemistry, 1998, 30(5): 597. [13] Gillon D, Joffre R, Ibrahima A. Ecology, 1999, 80(1): 175. [14] Bouchard V, Gillon D, Joffre R, et al. Journal of Experimental Marine Biology and Ecology, 2003, 290(2): 149. [15] McTiernan K B, Berg B, Berg M P, et al. Soil Biology and Biochemistry, 2003, 35(6): 801. [16] Aiken G E, Pote D H, Tabler S F, et al. Communications in Soil Science and Plant Analysis, 2005, 36(17/18): 2529. [17] Berardo N, Odoardi M, Scotton M. Rivistadi Agronomia, 1996, 30(3): 288. [18] Gislum R, Micklander E, Nielsen J P. Field Crop Research, 2004, 88: 269. [19] Cozzolino D, Labandera M D. Journal of the Science of Food and Agriculture, 2002, 82: 380. [20] Clark D H, Cary E E, Mayland H F. Agronomy Journal, 1989, 81(1): 91. [21] Vazquez de Aldana B R, Garcia Criado B, Garcia Ciudad A, et al. Communications in Soil Science and Plant Analysis, 1995, 26(9/10): 1383. [22] ZHAO Li-li, ZHANG Lu-da, SONG Zhong-xiang, et al(赵丽丽, 张录达, 宋忠祥, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2007, 27(1): 46. [23] 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
