Abstract:
Watermelon is an important horticultural crop which is grown in warm climate worldwide. However, its production and productivity is low owing to lack of high yielding improved varieties and poor knowledge of using mulches. Therefore, a field experiment was conducted in west Dembia district under irrigation from January to April 2021 to investigate the effect of mulches on growth and fruit yield of watermelon varieties. Factorial combinations of two varieties of watermelon (Crimson Sweet and Sugar Baby) and four types of mulches (black plastic, white plastic, grass mulch and no mulch as control) were arranged in a randomized complete block design with three replications. The remaining necessary agronomic practices and crop management activities were undertaken uniformly. The data presented under this dataset article includes phenological parameters (i.e. Days to 50 % germination, Days to 50 % flowering, and Days to 50 % maturity), growth parameters (i.e. main vine length, number of lateral branches per vine, number of nodes on main vine, and number of leaves on the main vine) and yield and yield component parameters (i.e. Number of total fruit plant-1, number of marketable fruit plant-1,number of unmarketable fruit plant-1, fruit length, fruit diameter, average fruit weight, marketable fruit yield, unmarketable fruit yield and total fruit yield). All the collected data were subjected to analysis of variance (ANOVA) and the analysis was carried out using the SAS version 9.4 software computer program\'s General Linear Model (GLM) procedure [1]. As described in Montgomery [2], the residuals were examined to verify the normal distribution and homogeneous variance model assumptions on the error terms for each response variable. Because the eight 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 mulching on productivity of watermelon varieties. Additionally, it provides the appropriate and economically feasible type of mulching material for maximized fruit yield of watermelon varieties in the study area or other areas having similar agro ecology. Hence, this information can allow other researchers to review the supplement data, methods, and make detailed analysis, which possibly giving rise to new lines of inquiry. This can also give rise to new collaborations and boost the reputation of the present research data within the scientific community and to make it available to everyone around the subject matter to use as they wish.
摘要:
西瓜是一种重要的园艺作物,在世界范围内气候温暖。然而,由于缺乏高产改良品种和使用地膜的知识不足,其产量和生产率很低。因此,于2021年1月至4月在西Dembia地区进行了田间试验,以研究覆盖对西瓜品种生长和产量的影响。两种西瓜(深红甜糖宝贝)和四种覆盖物(黑色塑料,白色塑料,草覆盖物和无覆盖物作为对照)以随机完整的区组设计排列,重复三次。其余必要的农艺实践和作物管理活动均统一进行。本数据集文章下提供的数据包括物候参数(即发芽天数至50%,天到50%开花,以及到期日至50%的天数),生长参数(即主藤长度,每棵藤蔓的侧枝数量,主藤上的节点数,和主藤上的叶数)以及产量和产量构成参数(即总果实数-1,可销售的果实数-1,不可销售的果实数-1,果实长度,果实直径,平均水果重量,适销对路的水果产量,无法销售的水果产量和水果总产量)。所有收集的数据进行方差分析(ANOVA),并使用SAS9.4版软件计算机程序的通用线性模型(GLM)程序进行分析[1]。如蒙哥马利[2]所述,检验残差以验证正态分布和齐次方差模型对每个响应变量误差项的假设。因为八种治疗组合在每个区块中是随机的,独立性假设是有效的。当治疗效果显著时,使用最小显著性差异(Fisher'sLSD)方法,在5%的显著性水平下进行多均值比较,以产生字母分组,并使用SAS中的Pearson相关程序进行相关分析.这篇数据集文章,因此,提供有关覆盖对西瓜品种生产力的影响的信息。此外,它为研究区或其他具有类似农业生态的地区西瓜品种的最大产量提供了合适且经济可行的覆盖材料类型。因此,这些信息可以让其他研究人员查看补充数据,方法,并进行详细分析,这可能会引发新的调查。这也可以引起新的合作,并提高科学界目前研究数据的声誉,并使其可供主题周围的每个人使用。