End‐Border Effects in Irrigated Barley Yield Trials<sup>1</sup>

Bhalli, M. A.; Day, A. D.; Tucker, Henry; Thompson, R. K.; Massey, G. D.

doi:10.2134/agronj1964.00021962005600030028x

Cited by 11 publications

(9 citation statements)

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“…1000-grain weight was the least affected. Similar results were found by Bhalli et al (1964) and Brown & Weibel (1957).…”

Section: Discussionsupporting

confidence: 90%

“…As expected, yields were higher when whole plots were harvested than when the border rows, adjacent to the pathway, were removed before harvesting (Bhalli et al 1964;Fischer, 1979Fischer, , 1981Austin & Blackwell, 1980). Several other studies examined the effects of border rows in continuous sowing of varieties (no uncropped pathways between them), using different crops (cited by Jensen & Federer, 1964, 1965Rich, 1973).…”

Section: Introductionmentioning

confidence: 69%

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Edge effects on yield, yield components and other traits in mechanized durum wheat and barley trials

Hadjichristodoulou

1983

J. Agric. Sci.

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A series of trials were conducted during 1979-82 under semi-arid conditions in a Mediterranean-type environment to study the edge effects in mechanized durum wheat and barley variety trials when uncropped pathways are left between plots. Varietal differences in edge effects on grain yield were in most trials not significant. Thus, edge effects do not distort significantly the relative ranking of varieties.Edge effects were significant for all traits studied and higher in grain and straw yields. These effects were also higher in drier seasons. The overestimation of grain yield from whole plots was 13-18% in relatively high rainfall seasons and 29% in a dry season. In two seasons the scores on the two outer rows were higher than on the two central rows by 89 and 117 % for grain yield, by 72 and 73 % for straw yield, by 44 and 48 % for numbers of tillers, by 6% for 1000-grain weight and by 14 and 40% fornumber of grains per tiller. The edge effect was not confined to the outer rows, but it extended to the inner rows of the plot; the magnitude of this effect varied with season and trait.Rows adjacent to the pathway and unprotected from wind had a lower value for all traits than the opposite rows of the pathway, which were protected by the inner rows.

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“…1000-grain weight was the least affected. Similar results were found by Bhalli et al (1964) and Brown & Weibel (1957).…”

Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 69%

Edge effects on yield, yield components and other traits in mechanized durum wheat and barley trials

Hadjichristodoulou

1983

J. Agric. Sci.

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“…Considering the optimal design for v � 5, p � 5 obtained from the set of shifts [1, 2, 3]t; the following are the matrix L, matrix M, and N matrix of the CBRMD (Table 2). [19,16,21,14,23,12,25,10,27,8,29,6,31,4,33,2,35,18,1,34,3,32,5,30,7,28,9,26,11,24,13,22,15,20,17]t…”

Section: □ Theoremmentioning

confidence: 99%

“…Repeated measurements designs (RMDs) have wide applications to ensure the validity and reproducibility of research in plant breeding and genetics research. Such designs have been extensively applied in areas where the treatment could be a plant variety, fertilizer, irrigation, or pesticide [1][2][3]. In crop experiments, the neighbor e ects have been recognized by Haines and Benzian [4] as well as Jenkyn and Dyke [5] due to competition for light, poaching of nutrients by plant roots, and the spread of disease pathogens.…”

Section: Introductionmentioning

confidence: 99%

Optimal Circular Balanced Repeated Measurements Designs for $v = p$ through the Method of Cyclic Shift (MCS) Rule II

Shehzad

Rajab

Daniyal

et al. 2022

Mathematical Problems in Engineering

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Background. One of the common characteristics of preclinical genetic experimentation is the result of repeated measurements, and for this purpose, repeated measurements designs (RMDs) have gained much more significance. In the class of RMDs, balanced repeated measurements designs (BRMDs) are preferred as they balance out the residual effects since the experimentation is repeated over time on different subjects. This study provides the theoretical framework of universal optimal criteria proposed by Kiefer (1975) for the newly proposed circular balanced repeated measurements designs (CBRMDs) by Rajab et al. (2018). These universal optimality criteria were proved for the special class of designs where the number of treatments is equal to the number of periods. Universal optimality has been discussed considering all the possible effects in the models, i.e., units, subjects, treatments, and periods. Methodology. This study characterized CBRMDs, where several treatments and periods are equal in the contest of three separate models with their matrices of information in simplified form. We used these simplified matrices of information to ascertain the criteria for universally optimal CBRMDs under different conditions. These new CBRMDs have been constructed using the well-known method of cyclic shifts (MCS) rule II. Results. Universal optimality of the new proposed classes of designs has been discussed theoretically. Universally optimal CBRMDs were constructed for v = p odd using the MCS rule II along with the confirmation of the universal optimality criteria proposed in the existing theory. Conclusions. The proposed class of new CBRMDs has been proven to have theoretically universally optimal designs, which have been constructed by the method of cyclic shifts rule II when the number of treatments is equal to the number of periods.

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“…Vernon [14] found substantial neighbour effects when plots receiving different manurial treatments were adjacent. Irrigation experiments are also liable to produce large neighbour effects; Bhalli et al [2] describe an example of this in the arable crop situation. They found that the neighbour effect varied between different varieties of barley, leading to substantial errors in the ranking of the varieties when the plot edges were included.…”

Section: Neighbour Effectsmentioning

confidence: 99%

Avoiding edge effects in agroforestry experiments; the use of neighbour-balanced designs and guard areas

Langton

1990

Agroforest Syst

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A number of different types of edge effects on experimental plots are defined, and it is shown that they are frequently important in agroforestry experiments. Methods of eliminating edge effects, either at the design or the analysis stage, are described. Computer simulations, based on uniformity data, are used to investigate the efficacy of neighbourbalanced designs, with and without neighbour terms, for reducing the problem of neighbour effects between different treatments. It is concluded that, while neighbour-balanced designs may be useful in certain situations or in combination with other methods, it is preferable to eliminate edge effects by using adequate guard rows. Recommendations are therefore made concerning the correct use of guard areas in agroforestry experimentation.

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End‐Border Effects in Irrigated Barley Yield Trials¹

Cited by 11 publications

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Edge effects on yield, yield components and other traits in mechanized durum wheat and barley trials

Edge effects on yield, yield components and other traits in mechanized durum wheat and barley trials

Optimal Circular Balanced Repeated Measurements Designs for $v = p$ through the Method of Cyclic Shift (MCS) Rule II

Avoiding edge effects in agroforestry experiments; the use of neighbour-balanced designs and guard areas

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End‐Border Effects in Irrigated Barley Yield Trials1

Cited by 11 publications

References 0 publications

Edge effects on yield, yield components and other traits in mechanized durum wheat and barley trials

Edge effects on yield, yield components and other traits in mechanized durum wheat and barley trials

Optimal Circular Balanced Repeated Measurements Designs for v = p through the Method of Cyclic Shift (MCS) Rule II

Avoiding edge effects in agroforestry experiments; the use of neighbour-balanced designs and guard areas

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End‐Border Effects in Irrigated Barley Yield Trials¹

Optimal Circular Balanced Repeated Measurements Designs for $v = p$ through the Method of Cyclic Shift (MCS) Rule II