scholarly journals Optimum size and shape of plots based on data from a uniformity trial on Indian Mustard in Haryana

MAUSAM ◽  
2021 ◽  
Vol 68 (1) ◽  
pp. 67-74
Author(s):  
MUJAHID KHAN ◽  
R. C. HASIJA ◽  
NITIN TANWAR

The most obvious use of uniformity trial data is to provide information on the most suitable size and shape of plots, in which the field was planted to a single variety and harvested as small plots. Indian mustard (Brassica juncea L.) cultivar RH-749 was grown using uniform crop improvement practices during rabi season of 2013-14 at Research Farm of Oilseed section, Department of Genetics and Plant Breeding, CCSHAU, Hisar, Haryana state, India, to estimate optimum plot size and shape using yield data of the 48 m × 48 m (2304 basic units) recorded separately from each basic unit of 1 m × 1 m. The variability among plots of different sizes and shapes was determined by calculating coefficient of variation. It was observed that the coefficient of variation decreases as the plot size increases in case of both the directions i.e., when plots were elongated in N-S direction (88 per cent decrease) or elongated in E-W direction         (93 per cent decrease). Further it was observed that long and narrow plots elongated in E-W direction were more useful than the compact and square plots in controlling the soil heterogeneity. Based on the maximum curvature method the optimum plot size for yield trial was estimated to be 5 m2 with rectangular shape.  

2003 ◽  
Vol 128 (3) ◽  
pp. 409-424 ◽  
Author(s):  
George E. Boyhan ◽  
David B. Langston ◽  
Albert C. Purvis ◽  
C. Randell Hill

Five different statistical methods were used to estimate optimum plot size and three different methods were used to estimate optimum number of replications with short-day onions (Allium cepa L.) for yield, seedstem formation (bolting), purple blotch and/or Stemphylium (PB/S), botrytis leaf blight (BLB), and bulb doubling with a basic plot size unit of 1.5 × 1.8 m (length × width). Methods included Bartlett's test for homogeneity of variance, computed lsd values, maximum curvature of coefficient of variation plotted against plot size, Hatheway's method for a true mean difference, and Cochran and Cox's method for detecting a percent mean difference. Bartlett's chi-square was better at determining optimum plot size with transformed count and percent data compared with yield data in these experiments. Optimum plot size for yield of five basic units (7.5 m length) and four replications is indicated using computed lsd values where the lsd is <5% of the average for that plot size, which was the case in both years of this study. Based on all the methods used for yield, a plot size of four to five basic units and three to five replications is appropriate. For seedstems using computed lsd values, an optimum plot size of four basic units (6 m length) and two replications is indicated. For PB/S two basic units (3 m length) plot size with four replications is indicated by computed lsd values. For BLB a plot size of four basic units (6 m length) and three replications is optimum based on computed lsd values. Optimum plot size and number of replications for estimating bulb doubling was four basic units (6 m length) and two replications with `Southern Belle', a cultivar with a high incidence of doubling using computed lsd values. With `Sweet Vidalia', a cultivar with low incidence of bulb doubling, a plot size of four basic units (6 m length) and five replications is recommended by computed lsd values. Visualizing maximum curvature between coefficient of variation and plot size suggests plot sizes of seven to eight basic units (10.5 to 12 m length) for yield, 10 basic units (15 m length) for seedstems, five basic units (7.5 m length) for PB/S and BLB, five basic units (7.5 m length) for `Southern Belle' doubling, and 10 basic units (15 m length) for `Sweet Vidalia' doubling. A number of plot size-replication combinations were optimum for the parameters tested with Hatheway's and Cochran and Cox's methods. Cochran and Cox's method generally indicated a smaller plot size and number of replications compared to Hatheway's method regardless of the parameter under consideration. Overall, both Hatheway's method and computed lsd values appear to give reasonable results regardless of data (i.e., yield, seedstems, diseases etc.) Finally, it should be noted that the size of the initial basic unit will have a strong influence on the appropriate plot size.


2021 ◽  
Vol 39 (2) ◽  
pp. 334-349
Author(s):  
Bruno Vinícius Castro GUIMARÃES ◽  
Sérgio Luiz Rodrigues DONATO ◽  
Ignacio ASPIAZÚ ◽  
Alcinei Místico AZEVEDO ◽  
Abner José de CARVALHO

This study aimed to determine the size and shape of experimental plots that provide maximum precision using relative information method. This trial was conducted at the Federal Institute of Bahia. Plant height, cladode length, cladode width, cladode thickness, cladode area, cladode area index, number of cladodes, cladode total area and yield were measured in the third production cycle, 930 days after planting. The plants, defined as basic units, were arranged in 39 plot sizes so that the crop would fill the whole experimental area. Then, plot shapes with higher relative information and equal plot size in basic units were selected. The experimental plot with eight basic units in size ensures higher efficiency in the experimental evaluation. This combination between size and shape, besides meeting all evaluation requirements of the characteristics normally assessed in studies with forage cactus pear, has the maximum control of soil heterogeneity, thereby decreasing experimental error and significantly increasing precision.


2005 ◽  
Vol 62 (6) ◽  
pp. 585-589 ◽  
Author(s):  
Sérgio José Ribeiro de Oliveira ◽  
Lindolfo Storck ◽  
Sidinei José Lopes ◽  
Alessandro Dal'Col Lúcio ◽  
Sandra Feijó ◽  
...  

Quality of field experiments data dependent upon adequate experimental design. This study investigated the relationship between the size of the basic unit for exploratory experiments and the optimum plot size, and the experiment precision with potato crop. Tuber yield of 24 rows, 144 mounds, were used to arrange experimental units of one, two, three, four, six, eight and 12 mounds. Tuber yield data of different mounds were used to arrange plot sizes with different numbers of basic units. The model CV(x)=A/X B was adjusted, in which CV(x) was the coefficient of variation among plots with different numbers of basic units. Optimum plot size was estimated with the modified maximum curvature method of the function CV(x)=A/X B, allowing completely random design. Experimental precision was estimated though the Hatheway method for different experimental arrangements. Based upon the modification of the maximum curvature method, for a fixed total experimental area, experimental unit size of potato initial experiments affects optimum plot size estimations with the same experimental precision and variable number of treatments.


1973 ◽  
Vol 9 (1) ◽  
pp. 63-71 ◽  
Author(s):  
W. C. James ◽  
C. S. Shih

SUMMARYData from uniformity trials on healthy and diseased wheat and oat crops showed that the coefficient of variation for yield decreased as plot size increased and became nearer to square in shape. Infection with Septoria leaf blotch of oats and powdery mildew of wheat did not appear to affect yield variability. Plots larger than rod row size (where 16 ft of the centre row of 3 rows is harvested) are recommended to detect differences of 10 per cent in yield between two treatments.


1964 ◽  
Vol 44 (1) ◽  
pp. 57-65 ◽  
Author(s):  
I. L. Nonnecke ◽  
K. W. Smillie

Uniformity trial data together with certain cost assumptions for potatoes indicate that long narrow plots are the most efficient. The basic unit was 4 ft long and 3 ft wide. A minimum of two basic units would be necessary for most potato studies with a maximum of six basic units depending upon the requirements for each experiment. Thus the optimum plot size could range from 3 ft wide and 8 to 18 ft long. Where smaller size becomes optimum more replications are required. Long narrow replicates likewise appear to be more efficient than either wide or square ones.The logical analysis and a generalized flow diagram for digital computer calculation of these data are presented.


1963 ◽  
Vol 55 (2) ◽  
pp. 197-199 ◽  
Author(s):  
Julian W. Crews ◽  
Guy L. Jones ◽  
D. D. Mason

2019 ◽  
Vol 22 (1) ◽  
pp. 35-43
Author(s):  
MZ Islam ◽  
T Chakrabarty ◽  
N Akter ◽  
ESMH Rashid ◽  
M Khalequzzaman ◽  
...  

The success of varietal development programmme largely depends on the nature and magnitude of genetic variability, heritability and characters association of the crop. The objective of the present study was to estimate the extent of genetic variability and relation between yield and related characters of rice. Forty Boro rice germplasm were evaluated in a randomised complete block design with three replications. Analysis of variance indicated significant differences among the genotypes for 14 quantitative characters. The presence of slightly higher phenotypic coefficient of variation than genotypic coefficient of variation indicated the negligible influence of environment on the expression of yield and its component traits. Leaf length, days to flowering, days to maturity and 1000 grain weight showed highly positive significant correlation present with yield hill-1. High heritability had been observed for yield contributing traits during the study, suggested that these traits would respond to selection owing to their high genetic variability and transmissibility. Therefore, a thorough understanding of the inheritance of traits, their heritability and relationship with other important characteristics is important for the choice of breeding and selection methods for crop improvement. Bangladesh Rice j. 2018, 22(1): 35-43


1983 ◽  
Vol 100 (1) ◽  
pp. 211-220 ◽  
Author(s):  
G. E. L. Morris ◽  
I. E. Currah

SUMMARYFor many horticultural crops the distribution of weight over size grades is of more importance than the total weight. This paper shows how simply determined features of interrelationships of the weight, size and shape of an individual in the crop can be combined to provide estimates of various aspects of the distribution of crop weight over size grades. The two relationships required are (i) the probability density function of the grading variable for the crop; (ii) a function relating the weight of an individual to the corresponding value of the grading variable.The paper shows how each of these can be determined either from published data or by simple experiment. Examples using data on onions and carrots are given to illustrate this and also to show some of the more important practical applications of the methods. For example, they allow the results of grading with one set of size grades to be extrapolated to a different set of grades without recourse to further measurement or experimentation and this is illustrated using published data on carrots. Other possible uses are also discussed and outlined.


1988 ◽  
Vol 39 (3) ◽  
pp. 351 ◽  
Author(s):  
ACF Trevitt ◽  
JR Freney ◽  
JR Simpson ◽  
WA Muirhead

The effects of differences in size of microplot and type of enclosure on the floodwater parameters determining ammonia volatilization were studied. The results show that the use of enclosures can retard urea hydrolysis, suppress the maximum daytime pH values (an effect which is cumulative over a number of days), and significantly reduce the potential for ammonia volatilization. These effects are the consequence of lowered light (and heat) penetration in the enclosed area due to shading of the floodwater by the enclosure walls. The magnitude of these effects varies with plot size and shape, and the material used for construction of the plot wall. A preliminary analysis suggests that, if errors due to shading are acceptable when 90% or more of the incident solar radiation always penetrates to the enclosed floodwater, then square plots with opaque walls must be at least 1.2 m along a side and cylindrical plots must be at least 1.2 m in diameter when wall height is 0.1 m above the floodwater.


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