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MODELO DE PREDICCIÓN DE LA DIGESTIBILIDAD DE PASTURAS HERB�CEAS NATURALES EN LAS ISLAS CANARIAS

Authors: Luis Alberto Bermejo; Javier Mata; Lea de Nascimento;

MODELO DE PREDICCIÓN DE LA DIGESTIBILIDAD DE PASTURAS HERB�CEAS NATURALES EN LAS ISLAS CANARIAS

Abstract

Knowing the energy content of pastures is necessary in order to estimate the livestock carrying capacity of grasslands. Taking into account the high cost of analyses for determining the digestibility of herbaceous biomass as an estimate of its energy content, this study proposes a model for predicting digestibility values on the basis of the most significant factors. For that purpose a multifactorial univariate analysis of variance (ANOVA) was carried out on digestibility to find out which factors, being easy to obtain, will allow to predict it with accuracy. From this analysis, we searched for a model which would allow predicting the energy content of samples taken in the field, on the basis of easily collected variables. There are three factors (plant group, vegetation type and month) which determine the digestibility of the herbaceous production in the areas of study, and therefore can be used to predict the quality of herbaceous primary productivity in the calculation of livestock carrying capacity. The model resulted of high predictability value (R2 = 0.76), permitting the estimation of the digestibility of dry matter in a simple way. Using this model the costs of determination of livestock carrying capacity will be considerably reduced, therefore facilitating the development of grazing management in relation to land use zoning, especially in new areas that has not been examined yet.

Keywords

plant group., digestibility, S, Agriculture (General), carrying capacity, Agriculture, grazing management, energy, S1-972

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold