Plot size and number of replications in Sudan grass

Author:

Cargnelutti Filho AlbertoORCID,Bandeira Cirineu TolfoORCID,Chaves Gabriela GörgenORCID,Kleinpaul Jéssica AndiaraORCID,Pezzini Rafael VieiraORCID,Neu Ismael Mario MárcioORCID,Procedi AndréiaORCID,Thomasi Rosana MarzariORCID

Abstract

The aim of this study was to determine the optimal plot size and the number of replications to evaluate fresh weight in Sudan grass [Sorghum sudanense (Piper) Stapf.]. Twenty-six uniformity trials were carried out in two cultivars (BRS Estribo and CG Farrapo), in four sowing seasons (20 Dec, 20 Jan, 7 Feb and 24 Feb) and two methods for evaluating fresh weight (cutting and at flowering). The fresh weight was evaluated in 936 basic experimental units (BEU) (26 trials × 36 BEU per trial). One BEU comprised three rows of plants, 1 m in length (1.2 m2). The optimal plot size was determined using the maximum curvature method of the model of the coefficient of variation. For experiments in a completely randomised or randomised block design, in combinations of number of treatments and levels of experimental precision, the number of replications was determined by an iterative process. The optimal plot size to evaluate fresh weight in Sudan grass is 7.95 m2. Eight replications, to evaluate up to 50 treatments in a completely randomised or randomised block design, are sufficient to identify as significant at 0.05% probability by Tukey’s test, differences between the mean value of each treatment of 30.2% of the mean value of the experiment.

Publisher

Universidade Estadual de Londrina

Subject

General Agricultural and Biological Sciences

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3