PRECISION OF FIELD EXPERIMENTS WITH VEGETABLE CROPS AS INFLUENCED BY PLOT SIZE AND SHAPE: III. POTATOES

1964 ◽  
Vol 44 (1) ◽  
pp. 57-65 ◽  
Author(s):  
I. L. Nonnecke ◽  
K. W. Smillie
Keyword(s):  
Digital Computer ◽  
Field Experiments ◽  
Computer Calculation ◽  
Trial Data ◽  
Logical Analysis ◽  
Flow Diagram ◽  
Basic Unit ◽  
Vegetable Crops ◽  
Size And Shape ◽  
Plot Size

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.

THE PRECISION OF FIELD EXPERIMENTS WITH VEGETABLE CROPS AS INFLUENCED BY PLOT AND BLOCK SIZE AND SHAPE.: II. CANNING PEAS

1960 ◽  
Vol 40 (2) ◽  
pp. 396-404
Author(s):  
I. L. Nonnecke
Keyword(s):  
Field Experiments ◽  
Block Size ◽  
Yield Variability ◽  
Vegetable Crops ◽  
Optimum Size ◽  
Size And Shape ◽  
Plot Size ◽  
Effect On Yield ◽  
Block Sizes ◽  
Uniform Reduction

In 1957, vine and shelled pea weights of canning peas from an irrigated uniformity trial were recorded to determine the effect on yield variability of varying plot and block sizes and shapes. The most uniform reduction in variation occurred in block shapes of one plot long and six plots wide with each increase in plot length. These results agree with those of other workers, that long, narrow blocks are more efficient than square blocks. The optimum plot size was found to be 5 feet long and 10 feet wide. Considerably more shelled peas were required for processing than could be obtained from the optimum size of plot for yield.

Optimizing plot size and shape for field experiments on terraces

1997 ◽  
Vol 33 (01) ◽  
pp. 51-64 ◽  
Author(s):  
R. Poultney ◽  
J. Riley ◽  
R. Webster
Keyword(s):  
Experimental Error ◽  
Field Experiments ◽  
Residual Variance ◽  
Size And Shape ◽  
Plot Size ◽  
Upper Limit ◽  
Plot Analysis ◽  
Residual Variances

Two methods, namely combined plot analysis and integration of variograms, have been applied to investigate and compare plot-to-plot yields of intercropped millet (mean yield of about 1.9 t ha−1) and maize (mean yield 4.25 t ha−1) on terraces in Nepal. Combining plots diminishing the residual variance of millet from 0.52 (t/ha)2 of the original 1 m×1 m units to 0.08 (t/ha)2 for 4 m×4 m plots, the largest for which reliable estimates could be derived. The residual variance of maize declined from 4.91 (t/ha)2 of the original units to 0.61 (t/ha)2 for 4 m×4 m plots. Orientation was immaterial. The variogram for millet was isotropic and bounded with a range of approximately 4 m. Within-plot variance calculated from the variogram increased, and experimental error decreased, as the size of plots increased to this value, beyond which there was little gain. The variogram for maize was unbounded, and so gave no ‘natural' upper limit for plot size, that is, over the range studied, up to 6 m×6 m. It was also anisotropic with larger gradient in the direction from front to back of the terrace than along the contour. The reduction in residual variance was greatest for narrow plots elongated in this direction. Formulae are provided from which to calculate from the variogram approximate residual variances for experiments of given area and size, shape, and orientation of plots. Its application gave similar results to those from the combined plot analysis. Overall, the results from the two methods were consistent.

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
Keyword(s):  
Coefficient Of Variation ◽  
Crop Improvement ◽  
Indian Mustard ◽  
Soil Heterogeneity ◽  
Basic Unit ◽  
Yield Data ◽  
Size And Shape ◽  
Plot Size ◽  
Yield Trial ◽  
Cent Decrease

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.  

scholarly journals Plot size and experimental unit relationship in exploratory experiments

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 ◽  
...  
Keyword(s):  
Field Experiments ◽  
Tuber Yield ◽  
Potato Crop ◽  
Variable Number ◽  
Basic Unit ◽  
Experimental Unit ◽  
Yield Data ◽  
Plot Size ◽  
Maximum Curvature

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.

THE PRECISION OF FIELD EXPERIMENTS WITH VEGETABLE CROPS AS INFLUENCED BY PLOT AND BLOCK SIZE AND SHAPE: I. SWEET CORN

1959 ◽  
Vol 39 (4) ◽  
pp. 443-457 ◽  
Author(s):  
I. L. Nonnecke
Keyword(s):  
Field Experiments ◽  
Sweet Corn ◽  
Block Size ◽  
Variation Method ◽  
Vegetable Crops ◽  
Optimum Size ◽  
Plot Size ◽  
Yield And Quality ◽  
Coefficients Of Variation ◽  
Block Sizes

In 1956 weights of marketable ears of hybrid sweet corn from three irrigated uniformity trials were recorded to determine the effect of varying plot and block sizes and shapes on yield variability. The coefficients of variation decreased with increased plot size. For block shapes of 1 × 6 plots (1 plot long and 6 plots wide) and block shapes of 3 × 2 plots (3 plots long and 2 plots wide) widening the plots was more effective in reducing variation than lengthening them. However, for block shapes of 6 × 1 plots and block shapes of 2 × 3 plots lengthening the plots was most effective. Estimates of cost were obtained showing the percentage of the total cost that was proportional to the number of plots used and the percentage that was proportional to the total area used per treatment. Optimum plot size for yield and quality studies was found to be one of two basic units (10 ft. by 6 ft., or 20 ft. by 3 ft.) depending upon cost assumed and the value of the regression coefficient. Smith's method for determining optimum size of plot agreed with the coefficients of variation method as to optimum size of plot.

Influence of Size and Shape of Plots on the Precision of Field Experiments with Potatoes

1932 ◽  
Vol 22 (2) ◽  
pp. 366-372 ◽  
Author(s):  
S. H. Justesen
Keyword(s):  
Field Experiments ◽  
Size And Shape ◽  
Plot Size ◽  
Soil Variation ◽  
The Mean

1. A uniformity trial with potatoes was used for investigating the effect of size and shape of plots on the precision of field experiments. Up to a certain limit the S.D. in per cent. of the mean decreases when the size of plots is increased; further increase of plot size increases the errors as a lesser part of the soil variation can be removed.2. Two-row plots show less variation than either 1 or 3-row plots. This may be explained by row competition.3. When the area to be used is fixed, smaller plots are more efficient than larger, owing to the greater number of replications in the former case. One exception occurs in the case where border rows are not harvested; here 4-row plots are more efficient than 3-row plots, owing to the fact that a larger part of the soil is included in the calculations when 4-row plots are used.4. Long and narrow plots are more efficient than shorter and wider of the same size. The only exception is again explained by row competition.5. In field experiments with potatoes fairly large plots should be used; at least 2 rows wide and preferably long and narrow strips.

Establishment theoretical of recommendation fertilization guide of vegetable crops in Algeria: concept and validation

2015 ◽  
Vol 5 (1) ◽  
pp. 606-620
Author(s):  
Mahtali Sbih ◽  
Zoubeir BENSID ◽  
Zohra BOUNOUARA ◽  
Fouad DJAIZ ◽  
Youcef FERRAG
Keyword(s):  
Soil Fertility ◽  
Field Experiments ◽  
Soil Analysis ◽  
Critical Value ◽  
Yield Response ◽  
Published Data ◽  
Vegetable Crops ◽  
Fertilizer Recommendation ◽  
Continuous Models ◽  
Poor Soil

The goal of fertilization is to meet the nutritional needs of plants by completing the supply of soil nutrients in an economically profitable and environmentally friendly. Achieving on-farm optimum economic crop yields of marketable quality with minimum adverse environmental impact requires close attention to fertilization guide. The recommendations seek to do this by ensuring that the available supply of plant nutrients in soil is judiciously supplemented by additions of nutrients in fertilizers. The objective is that crops must have an adequate supply of nutrients, and many crops show large and very profitable increases in yield from the correct use of fertilizers to supply nutrients. The main objective of this work is to establishing a reference guide of fertilization of vegetable crops and cereal in Algeria. To meet this objective, we have processes in two steps: 1) Establishment of theoretical fertilizer recommendation from international guide of crop fertilization; 2) Validation of these developed theoretical fertilizer recommendation by trials in the fields. Sixteen fertilization guides of vegetable crops from the Canadian provinces (5 guides), USA (10 guides) and countries of northern Europe England (1 guide). Generally, the rating of these recommendation is ranging from poor soil to soil exceedingly rich; however, the numbers of fertility classes are very different. Indeed, Quebec Ontario, Minnesota, Wisconsin New England, Maryland and Kentucky and Florida guides are subdivided into 5 fertility classes, ranging from poor soil to soil exceedingly rich. The recommendation of New Brunswick and Manitoba contain six classes. The recommendation of Michigan, Nova Scotia and England contain 10 and 7 fertility classes respectively. The recommendation fertilizer of New York and New Jersey have 3classes. Unlike the systems of fertilization recommendation mentioned above, the recommendation fertilizer of Pennsylvania is based on continuous models of P, K and contains 34 classes for P and 22 classes K. Then we standardized the P soil analysis with conversion equations (Olsen method) and units of measurement (kg/ha, mg/kg…).Following this procedure we transformed discontinued systems of fertility classes in to continuous models to facilitate comparison between the different fertilization recommendation models in one hand, in other hand to obtain critical value (CV).Finally, we used statistics of the conditional expectation in order to generate the theoretical recommendation fertilization guide of fertilization with 7 fertility classes (VL, L, M, MH, OP, H and VH). The next step was calibrating soil tests against yield responses to applied nutrient in field experiments. A database (not published data) from agriculture and agri-food Canada, were used. Production of pumpkin responded positively and significantly to P or K soil fertility levels, increases being observed with P more often than with K. According to the Cate-Nelson methods, the critical value of Olsen-P in the top 20 cm of soil was about 25 mg/kg: at values of greater than or equal to 25 mg/kg, crops achieved about 80% of their maximal yield in the absence of fertilizer application. The CV of K in soil for this crop was about 140 mg/kg. The CV found was very close to this generated by the theoretical method for recommendation of fertilization guide. Finally, we used the procedure of Cope and Rouse in both sides of the CV in order to make subdivisions of different groups of soil fertility. One calibrates the soil-test value against yield response to tile nutrient to predict fertilizer requirement.

Field Plot Technique Studies with Flue‐Cured Tobacco. I. Optimum Plot Size and Shape 1

1963 ◽  
Vol 55 (2) ◽  
pp. 197-199 ◽  
Author(s):  
Julian W. Crews ◽  
Guy L. Jones ◽  
D. D. Mason
Keyword(s):  
Field Plot ◽  
Size And Shape ◽  
Plot Size ◽  
Field Plot Technique
Sign in / Sign up

Export Citation Format

Share Document