Impact of grain morphology and the genotype by environment interactions on test weight of spring and winter wheat (Triticum aestivum L.)

Yabwalo, Dalitso N.; Berzonsky, William A.; Brabec, Daniel; Pearson, Thomas C.; Glover, Karl D.; Kleinjan, Jonathan

doi:10.1007/s10681-018-2202-7

Cited by 22 publications

(19 citation statements)

References 32 publications

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“…However, the relationship between TW and wheat milling potential is not always warranted and generally affected by wheat classes, varieties within the class and specific growing condition [1][2][3]. Studies have shown that TW was affected by wheat moisture, kernel density, kernel shape and packing factors, which were not related to milling yield [4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Inter-Relationships between Test Weight, Thousand Kernel Weight, Kernel Size Distribution and Their Effects on Durum Wheat Milling, Semolina Composition and Pasta Processing Quality

Wang¹,

Fu²

2020

Foods

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Although most of the durum wheat produced in the Canadian prairies in 2017 and 2018 met the test weight (TW) requirements for the top grades of Canada Western Amber Durum (CWAD), some samples of top grades were inferior in milling quality. To understand the abnormality, this study was conducted to investigate TW, thousand kernel weight (TKW) and kernel size distribution (KSD) in relation to durum milling potential, semolina composition and pasta quality. With reduction of kernel size, semolina and total milling yields decreased progressively, and kernels passing through no.6 slotted sieve had detrimental impact on milling. The overall relationship between TW and milling yields appeared to be genotype dependent. At similar TW, variety showed lower milling yields had greater proportion of smaller kernels. By account for the difference in KSD, greater relationships (R2 > 0.91, p < 0.001) were found for TKW and proportion of kernels passing No.6 slotted sieve with milling yields than TW (R2 = 0.75, p < 0.001). This infers potential use of small kernels (passing No.6 slotted sieve) as a new objective grading factor for rapid prediction of milling quality of CWAD. Although small kernels exhibited much higher yellow pigment than the larger ones, pasta made from small kernels was duller, redder and less yellow, likely due to the higher semolina ash and protein contents, which adversely affected pasta color.

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Section: Introductionmentioning

confidence: 99%

Inter-Relationships between Test Weight, Thousand Kernel Weight, Kernel Size Distribution and Their Effects on Durum Wheat Milling, Semolina Composition and Pasta Processing Quality

Wang¹,

Fu²

2020

Foods

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“…Bulk density was a stable trait across years, with low CV and satisfactory genotype differentiation. Yabwalo et al (2018) mentioned stability in test weight as a criterion for selecting genotypes: test weight is another calculation of bulk weight. In addition, this trait (bulk weight) showed the largest number of lines that outyielded the original population (landrace).…”

Section: Discussionmentioning

confidence: 99%

“…The fifth line was selected as having the best yield in each plot (for bulk density). Karimizadeh et al (2012) refer to bulk density as a suitable selection criterion for yield improvement, positively correlated (among other traits), and up to 0.90 grain yield (Hanchinal et al, 1993;Mason et al, 2007); it is used in a recent study in terms of test weight (Yabwalo et al, 2018).…”

Section: Methodsmentioning

confidence: 99%

Preliminary comparisons of early generation individual selection efficiency of a local wheat landrace under different experimental field designs

Greveniotis

Sioki

2019

Chil. j. agric. res.

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Wheat (Triticum aestivum L.) landraces are traditional adapted varieties developed and used by farmers but not usually improved by breeders. The objective of our study was to compare the efficiency of three different methods (arrangements) of homogeneity blocks to produce high-yield progenies during the breeding procedure of a local bread wheat landrace. This original genetic material underwent a mass selection scheme in F2 individual plants in three different experimental designs to reduce soil heterogeneity (honeycomb, gridding, double rows); selection was based on individual plant grain weight. In F3 lines, bulk density was the selection criterion in a specific arrangement that divided the experimental field into three plots for 12 subplots to reduce soil heterogeneity. The F4 lines were evaluated in randomized complete block trials for 2 yr based on grain yield, 1000-kernel weight, and bulk density. Progenies from the three different experimental designs were compared. The gridding method seemed more efficient for evaluating sister lines because it maximized yields, provided a greater number of promising lines, and F3/F4 correlations were high and significant. Wheat plants did not perform well under the double row system (mean bulk density 756 g L-1). Heritability was high for all studied traits (0.93) and bulk density was a reliable criterion for selecting promising genetic materials (90.1% genotype contribution in variability) and revealed differences between methods. The local landrace was unstable and exhibited specific adaptability to the cultivated environment. Selected lines (from the most efficient method) improved yield performance by 11% on the average compared with the original population.

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“…The reason why test weight is not always a good index of quality is that it is a complex character influenced by single grain density and packing characteristics of the grain (Doehlert & McMullen, 2008; Pushman, 1975; Yamazaki & Briggle, 1969; Yabwalo et al, 2018). Single grain density accounts for 78 to over 90% of the test weight variation (Doehlert & McMullen, 2008; Yabwalo et al, 2018) and can be affected by moisture content in a nonlinear manner, with drying increasing the test weight to a lesser extent than dampening altering it (Hook, 1984; Pushman, 1975; Tkachuk & Kuzina, 1979). Factors that affected packing characteristics are of a genetic nature (kernel shape, surface texture) (Doehlert & McMullen, 2008; Yabwalo et al, 2018) but also include the presence of broken, shrunken, or damaged grain (Yamazaki & Briggle, 1969).…”

Section: Introductionmentioning

confidence: 99%

“…Single grain density accounts for 78 to over 90% of the test weight variation (Doehlert & McMullen, 2008; Yabwalo et al, 2018) and can be affected by moisture content in a nonlinear manner, with drying increasing the test weight to a lesser extent than dampening altering it (Hook, 1984; Pushman, 1975; Tkachuk & Kuzina, 1979). Factors that affected packing characteristics are of a genetic nature (kernel shape, surface texture) (Doehlert & McMullen, 2008; Yabwalo et al, 2018) but also include the presence of broken, shrunken, or damaged grain (Yamazaki & Briggle, 1969). Therefore, grain cleaning can improve test weight by removing impurities in wheat (Kiser, 1992; Seitz et al., 1985; Yamazaki & Briggle, 1969) or by separating whole kernels of different densities (Bettge et al., 1989).…”

Section: Introductionmentioning

confidence: 99%

Efficiency of grain cleaner to increase test weight in wheat (Triticum aestivum)

Crépon

Duyme

2020

Cereal Chem

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Background and objectives Weather conditions can deteriorate the test weight to the extent that some wheat lots see their access to the market compromised. Test weight degradation may be due to low grain density or to an alteration in packing characteristics, in particular because of a high level of impurities in the batch. Therefore, grain cleaning can improve test weight by removing impurities. The objective of this work was to determine the settings of the cleaner that significantly influence both the improvement of test weight and the amount of materials removed by cleaning, in order to advise silo managers on the cleaning strategy to adopt in case of low‐test weight harvest. Findings We implemented a complete factorial design of experiments using a laboratory cleaner‐separator. The factors tested were the initial test weight, the screens used, the aspiration, and the grain flow rate. Conclusions Cleaning significantly improve test weight by an average of 2.1 kg/hl. The average amount of material removed is 8.1%. The only setting that significantly impacts the test weight gain is the grain flow rate. Using a more open screen does not affect test weight gain but greatly increases screenings, so this strategy should be avoided. Significance and novelty As a result of this work, two decision trees guide the choice of the operators as regards the adjustment of the devices according to the expected specific weight gain and the amount of lost material caused.

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Impact of grain morphology and the genotype by environment interactions on test weight of spring and winter wheat (Triticum aestivum L.)

Cited by 22 publications

References 32 publications

Inter-Relationships between Test Weight, Thousand Kernel Weight, Kernel Size Distribution and Their Effects on Durum Wheat Milling, Semolina Composition and Pasta Processing Quality

Inter-Relationships between Test Weight, Thousand Kernel Weight, Kernel Size Distribution and Their Effects on Durum Wheat Milling, Semolina Composition and Pasta Processing Quality

Preliminary comparisons of early generation individual selection efficiency of a local wheat landrace under different experimental field designs

Efficiency of grain cleaner to increase test weight in wheat (Triticum aestivum)

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