The Measurement and Interpretation of Genotype X Environment Interactions in Semidwarf Winter Wheats in Kansas PDF Download

Author: Badri Nath Kayastha
Publisher:
ISBN:
Category : Crop yields
Languages : en
Pages : 186

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Author: Amanda De Oliveira Silva
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Category :
Languages : en
Pages :

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Understanding factors underpinning the variation in nitrogen (N) utilization efficiency (NUtE) [i.e., grain yield per unit of N uptake at maturity] is critical to direct future breeding and agronomic management strategies in wheat. However, no study has summarized changes in wheat NUtE across a wide range of environments. Further, the conservative behavior of producers to intensify management practices may have been contributing to the yield stagnation in the US southern Great Plains. Our goals were to: (i) perform a synthesis-analysis using published data to study NUtE in wheat, and (ii) conduct field studies to investigate the influence of genotype, environment, and management on grain yield and nutrient uptake. Results from our synthesis-analysis (n=529) showed a positive and curvilinear relationship between grain yield and NupMAT, indicating that opportunities to enhance yield through improving NUtE would only be possible at greater-than-average yield and N uptake levels. By measuring the effects of other reported variables on the residuals of the relationship between NUtE and N uptake, we observed that the variability in NUtE at particular levels of N uptake was greater for fall- than for winter-sown wheat, but it was similar for all wheat classes. The negative correlation between grain protein concentration and the residuals indicated a challenge to increase yield through improving NUtE with no penalties in grain protein. We conducted two field research experiments at difference sites during the 2015-16 and 2016-17 growing seasons in Kansas. In our experiment 1, we conducted on-farm experiments across three locations and two growing seasons in Kansas using 21 modern winter wheat genotypes grown under either standard (SM) or intensified management (IM) systems. Results showed that across all sites-years and genotypes, the IM increased yield by 0.9 Mg ha−1 relative to the SM. Even in the lowest yielding background condition, the IM outyielded SM, and expectedly, the yield response to IM increased with the achievable yield of the environment. The yield response of genotypes to IM was related to the responses of biomass between the two management systems rather than harvest index, strongly driven by improvements in grain number while independent of changes in grain weight, and related to improvements in N uptake. In our experiment 2, we evaluated the partial contribution of 14 management practices on grain yield and the accumulation of N, P, K and S during the growing season using a single bread-wheat genotype grown under four site-years. Fungicide was the main treatment affecting yield and nutrient uptake. Overall, all nutrients were accumulated at a similar proportion at each growth stage relative to their respective accumulation at the end of the season. Shoot concentration for IM seemed to maintain higher concentration of nutrients as compared to the SM control during the growing season. This was emphasized by the significant increase in nutrition indices for N and S from SM to IM control, indicating possible luxury uptake under IM. Hence, crop intensification strategies may alter nutrient uptake at the end of season, but will not affect timing and rate of uptake during the growing season.

Author: John Luscombe Purchase
Publisher:
ISBN:
Category : Analysis of variance
Languages : en
Pages : 166

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Author:
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ISBN:
Category : Dissertation abstracts
Languages : en
Pages : 574

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Author: Samuel Lee Shafer
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ISBN:
Category :
Languages : en
Pages : 118

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Author: Paul Norman Fox
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ISBN:
Category : Genotype-environment interaction
Languages : en
Pages : 154

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Author: Mark J. Larson
Publisher:
ISBN:
Category : Genotype-environment interaction
Languages : en
Pages : 312

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Extensive research has been devoted to evaluating potential genotype-environment interactions. However, plant breeders are still in need of a simple way to describe how genotypes respond to different locations and years. In an environmentally diverse state like Oregon, significant genotype-environment interactions do occur The resulting lack of association between actual and genotypic potential yield performance makes it difficult to select genotypically superior lines. This study was prompted to evaluate the extent of such an interaction and compare various yield stability models. A significant genotype-environment interaction encompassing lines, environments, and years was discovered for each individual year analyzed and for the combined analysis of 1992, 1994 and 1995, and 1989 through 1994. Most lines evaluated during 1992, 1994 and 1995 were adapted to low yielding environments. However, two genotypes (OR880172 and OR880525) exhibited broad adaptation. Stephens and Mac Vicar were less adapted to the relatively high yielding Chambers site than the other genotypes tested during 1992, 1994 and 1995 due to Septoria tritici infections. The most stable genotypes during the combined 1992, 1994 and 1995 and 1989-1994 seasons were OR870831, Madsen and OR8500933H. Gene was the most desirable genotype based on stability and yield for both the combined 1992, 1994 and 1995 and 1989-1994 seasons. Due to an inability to adapt to higher yielding environments, the cultivar Rohde was the least stable genotype during the same combined periods. High and low temperatures and precipitation had minor yet significant effects on yield responses at all three sites during various periods identified. Advanced winter wheat selections and cultivars were grown in three diverse environments and compared over different time periods. Due to trial design and the objective of identifying superior genotypes from a set tested in target environments a combination of two methods, stability variance and a selection index, emerged as the most appropriate techniques. These approaches are considered the most appropriate because they use the mean of the trial as a gauge for measuring stability.

Author: Byron J Evers
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Globally wheat is one of the three most important cereal crops globally providing 20% of protein and total calories consumed. In the world as well as the state of Kansas, wheat is planted on more acres than any other crop. Additionally, wheat sales generated $1.27 billion in revenue in 2021 making wheat an economic driver for the entire state. However, the annual genetic gain in wheat is 0.8-1.2% and is not sufficient to support the increasing global population. Therefore, the adoption of new technology and computational methods are critical to increase genetic gain and increase wheat adaptability both globally and in the Central Plains. Proper temporal resolution is critical for quality HTP sensor data collection, as collection at key physiological growing points can increase yield prediction and assist with phenotypic selection. However, growth stages are dependent on weather and fluctuate both across locations and years. This makes day of year or day after sowing a poor phenology metric, particularly with winter wheat where the vernalization requirement compounds phenology prediction challenges and significantly shifts developmental stages relative to calendar days. This study was designed to assess the performance of various phenology models to predict heading time of both historically adapted and experimental genotypes of wheat genotypes in Kansas. The results suggest that full season models with multi-phase coefficients can increase phenology prediction over traditional thermal indices. However, using cumulative thermal times after the vernalization requirements also provided phenology predictions that were statistically similar to the full season phase change models. Genotype by environment interactions is a prominent issue for breeding programs, particularly when performance testing elite lines across multiple locations and years. In addition to macroenvironments, variations in soil properties have shown to develop microenvironments within location years. These soil microenvironments can potentially be quantified through both traditional and precision agriculture tools. Whereas, traditional soil sampling density is limited by cost and time, precision agriculture on-the-go soil sensors have the potential to gather large quantities of data. However, these measurements are often giving only relative measurements. Through this experiment two sensor platforms were evaluated as potential tools to quantify spatial variability within breeding programs. This study showed that soil spatial variability does impact genotype yield performance and that indirect measurements from both sensor platforms can quantify this impact. The continued development of high quality, cost effective multi-spectral imaging devices has led to numerous studies to evaluate this technologies ability to predict traits and grain yield. Despite these advancements the widespread implementation of these tools for selection has been slow and most breeders still rely on harvested grain yield and visual selection for cultivar advancement. The intention of this experiment was to evaluate high spatial resolution data from, multi-spectral sensors at multi-temporal collection points to make yield group rank order selections. Additionally, a random forest algorithm was used to evaluate the potential of incorporating machine learning with HTP data as a selection tool. Although the rank order correlations were higher than the correlation to grain yield, the selection accuracies of random forest were not statistically better than the no-information rate. However, this study does lay the groundwork for future similar studies using alternative sensor aided metrics and machine learning algorithms. Overall, the combined results of these studies show that these precision agriculture tools have to potential to increase genetic gain in plant breeding. However, these studies also show that both sensor and computational limitations still exist. Moving forward it is pivotal that future studies focus on technology combinations that have the potential to easily be implemented within a breeding program.

Author: Li Pei
Publisher:
ISBN:
Category :
Languages : en
Pages : 104

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Author: Kraig Lyle Roozeboom
Publisher:
ISBN:
Category :
Languages : en
Pages : 388

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