期刊
JOURNAL OF AGRICULTURAL SCIENCE
卷 153, 期 5, 页码 891-906出版社
CAMBRIDGE UNIV PRESS
DOI: 10.1017/S0021859614000653
关键词
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资金
- French Ministry of Agriculture
- CAS DAR programme
To upgrade the use of permanent grasslands in livestock farming systems for their economic and environmental utility, their value needs better assessment in terms of both quantity (biomass production) and quality (nutritive value: organic matter digestibility (OMD) and crude protein content (CP)). The wide variability in permanent grassland botanical composition makes it important to understand the links between vegetation characteristics and permanent grassland value, and how far environmental factors influence this value. The current work investigated how vegetation characteristics and weather explained the variability of the biomass production and nutritive value of permanent grasslands. Two models were used to determine the best vegetation characteristics for the prediction: (i) plant functional types (PFT), proportions of grasses, legumes and forbs and weather, and (ii) two proxies for PFT (dry matter content (DMC) and phenological development at medium plant stage (MPS)), proportion of grasses, legumes and forbs, and weather. The study was conducted on a set of 190 permanent grasslands distributed over a wide range of soil, climatic and management conditions, and lasted 2 years (2009/10). For each of the permanent grasslands, climatic data, values of vegetation characteristics, biomass production and nutritive value were collected at the beginning and end of spring, and during summer and autumn regrowths. Contribution of weather was important and particularly for regrowths. Composition in terms of botanical families, plant stage and sward DMC was the common variables that explained both biomass production and nutritive value during the growing season. Biomass production was mainly explained by the proportion of legumes and forbs, MPS and DMC considering both models. Grass nutritive value was linked to the same factors, including PFT. However, the contribution of grass PFTs was lower in models. Both models could be used to predict biomass production and nutritive value: R-2 of the two models are quite similar. Over a wide range of environmental and management conditions, vegetation characteristics and climatic data explained almost half of the variance of forage quality and 20-40% of the variance of biomass production.
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