Data on effect of NPSB fertilizer rates on growth and yield of carrot (Daucus carrota L.) varieties in Gondar district, Northwestern Ethiopia

埃塞俄比亚西北部贡德尔地区非磷化硅肥施用量对胡萝卜(Daucus carrota L.)品种生长和产量的影响数据

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Abstract

Carrot (Daucus carota L.) is one of the most important root crops grown worldwide and in Ethiopia. However, its production and productivity are low due to a lack of improved varieties and unbalanced fertilizer rates, among other factors. The field experiment was, therefore, conducted to improve the productivity of carrot varieties through blended fertilizer rates at the horticulture demonstration site of the College of Agriculture and Environmental Sciences, University of Gondar. Treatment consisted of NPSB nutrient levels (0:0:0:0, 21.3:15.3:2.80:0.04, 42.6:30.6:5.60:0.08, 64:46:8.41:0.12, 85.3:61.2:11.2:0.16, and 106.7:76.7:14.03:0.20 kg ha(-1)), which were laid out in a randomized complete block design with three replications. Data were collected on crop phenology, growth and root yield (marketable, unmarketable, and total root yield) parameters and subjected to analysis of variance using SAS computer software version 9.4. As described in Montgomery, the residuals were examined to verify the normal distribution and homogeneous variance model assumptions on the error terms for each response variable. Because the twelve treatment combinations were randomized within each block, the independence assumption is valid. When a treatment effect was significant, multiple means comparison was performed at a 5% level of significance using the least significant difference (Fisher's LSD) method to generate letter groupings, and correlation analysis was performed using the Pearson correlation procedure found in SAS. This dataset article, therefore, gives information about the effects of NPSB on the productivity of carrot varieties. The experiment also determines the optimal NPSB fertilizer rate for maximizing carrot root yield in comparable agro-ecological regions, offering valuable insights for researchers to analyze and potentially sparking new research directions. This data can foster collaborations and enhance the visibility of research within the scientific community, enabling widespread access for further exploration and application in related fields.

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