The effect of perennial forage crop on grain yields in submontane regions

Plant, Soil and Environment

Novák D.¹  Pulkrábek J.¹  Faměra O.:¹  Šroller J.¹ 

关键词: marginal regions;    grain yields;    NPK fertilization;    percentage of perennial forage crops;   

DOI  :  

学科分类：农业科学（综合）

来源: Czech Academy of Agricultural Sciences

【 摘 要 】

The structure of crop production (areas under crops, crop yields, fertilization) in 15 agricultural farms in potato-production and mountain regions of the Czech Republic was analyzed to evaluate the relations between NPK fertilization level, percentage of perennial forage crops on arable land and grain yields as the basic indicator of crop production output. A multifactor analysis based on simple regression equations indicated direct relations between the two above-mentioned factors and yield. Correlation and regression analyses demonstrated a close correlation between grain yields and percentage of perennial forage crops on arable land especially when lower nutrient rates in fertilizers were used (below 100 kg NPK.ha arable land). This relation was expressed for the whole set of initial data by the equation: Grain yield t.ha�?1 = log2 (NPK rate in kg.ha�?1 arable land + X% of perennial forage crops). The coefficient of perennial forage crop effect (X) in the range of 0�?1.47 can be explained by soil enrichment with nitrogen, mobilization of other nutrients, improvement of soil structure and reduction in the weed infestation of soil. The effect of perennial forage crops on grain yield increase was quantified (estimated) from the whole set of data using the above equation at X = 0 by the value +0.42 t.ha�?1. The yield increase per 1 kg NPK.ha�?1 of arable land amounts to 0.0501 t.ha�?1, i.e. every 1% of forage crops on arable land increases the grain yield by 0.023 t.ha�?1 within the set. The relation between actual and theoretical yield of the whole set is demonstrated by correlation coefficient (r = 0.9332) if the effect of perennial forage crops is estimated by coefficient X = 0.95, if the effect is estimated by coefficient X = 1.47, the correlation coefficient is even higher (r = 0.9977).

【 授权许可】

Unknown