Browsing by Author "Santantonio, Nicholas"

Now showing 1 - 8 of 8
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    Digital Phenotyping and Genomic Prediction Using Machine and Deep Learning in Animals and Plants
    Bi, Ye (Virginia Tech, 2024-10-03)
    This dissertation investigates the utility of deep learning and machine learning approaches for livestock management and quantitative genetic modeling of rice grain size under climate change. Monitoring the live body weight of animals is crucial to support farm management decisions due to its direct relationship with animal growth, nutritional status, and health. However, conventional manual weighing methods are time consuming and can cause potential stress to animals. While there is a growing trend towards the use of three-dimensional cameras coupled with computer vision techniques to predict animal body weight, their validation with deep learning models as well as large-scale data collected in commercial environments is still limited. Therefore, the first two research chapters show how deep learning-based computer vision systems can enable accurate live body weight prediction for dairy cattle and pigs. These studies also address the challenges of managing large, complex phenotypic data and highlight the potential of deep learning models to automate data processing and improve prediction accuracy in an industry-scale commercial setting. The dissertation then shifts the focus to crop resilience, particularly in rice, where the asymmetric increase in average nighttime temperatures relative to the increase in average daytime temperatures due to climate change is reducing grain yield and quality in rice. Through the use of deep learning and machine learning models, the last two chapters explore how metabolic data can be used in quantitative genetic modeling in rice under environmental stress conditions such as high night temperatures. These studies showed that the integration of metabolites and genomics provided an improvement in the prediction of rice grain size-related traits, and certain metabolites were identified as potential candidates for improving multi-trait genomic prediction. Further research showed that metabolic accumulation was low to moderately heritable, and genomic prediction accuracies were consistent with expected genomic heritability estimates. Genomic correlations between control and high night temperature conditions indicated genotype-by-environment interactions in metabolic accumulation and the effectiveness of genomic prediction models for metabolic accumulation varied across metabolites. Joint analysis of multiple metabolites improved the accuracy of genomic prediction by exploiting correlations between metabolite accumulation. Overall, this dissertation highlights the potential of integrating digital technologies and multi-omic data to advance data analytics in agriculture, with applications in livestock management and quantitative genetic modeling of rice.
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    Evaluation of Genomic Prediction and the Agronomic Performance of Facultative Barley
    Reith, Francis Arthur (Virginia Tech, 2024-10-28)
    Cultivated barley typically exhibits either a winter growth habit or a spring growth habit. Some cultivars display a facultative growth habit, allowing them to be cultivated as either winter or spring crops. This study evaluated 1,128 elite barley cultivars and breeding lines under fall and spring sowing to determine which lines had a facultative growth habit and the underlying genetics thereof. In the fall of 2021 and subsequent spring of 2022, The first trial focused on identifying genetic factors associated with facultative habit. Results indicated that facultative lines were rare, with the majority exhibiting a winter growth habit. GENOME WIDE SCANS revealed no novel QTL associated with facultative habit, but significant QTLs on chromosome 4H were identified, correlating with the vernalization gene "VRN-H2." Several haplotypes found on chromosome 4H within appear significant and may contribute to differences in facultative habit. Only 28% of facultative lines could be accurately predicted based on genetic data, suggesting that facultative habit is a more complex trait than previously understood. Significant epistatic interactions between chromosome 4H and 4 other chromosomes were discovered. These findings indicate facultative habit is a much more quantitative trait than previously reported. The second trial involved growing the best-performing lines from the first trial under both fall and spring sowing conditions. Winter-sown barley consistently outperformed spring-sown barley in grain yield across all facultative lines. Despite strong performance under spring conditions, yield rankings were inconsistent across both sowing seasons, implying that agronomic performance cannot be reliably predicted across seasons. Notably, the Virginia Tech malt barley line 'Avalon' demonstrated facultative growth but exhibited poor agronomic quality under spring sowing. In contrast, lines such as 'VA22M-20DH1349' and 'VA22M-20DH1182' showed superior performance in both sowing regimes, indicating their potential for future breeding programs and agronomic trials for facultative barley in the American East.
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    The Evaluation of Root System Architecture (RSA) As A New Breeding Target for Climate-Resilient Winter Wheat (Tritium aestivum L.)
    Ragland, Demetrius Isaiah (Virginia Tech, 2024-10-22)
    Crop yields are expected to face more threatening circumstances due to ongoing climatic and environmental change. The continued sustainability of crop production will depend on genetic capacity of crops to adapt to increased biotic and abiotic barriers induced by climate change. Historically, shoot-based traits were breeding targets for overcoming yield gaps between developed and undeveloped nations. However, the rate of genetic gain has stabilized with conventional breeding targets for indirect yield improvement. As the availability of mineral fertilizers is steadily declining and the occurrence of low-fertility soils has increased, reoccurring yield disparities worldwide are propelling us to evaluate new breeding targets. There is potential for plant breeders to shift their focus to the root system architecture (RSA) as a new target for indirect selection, enabled by the phenotypic plasticity of winter wheat (Triticum sp.), one of the main staple agronomic crops. Our current limited understanding of the dynamic nature of the root system architecture is due to the difficulties associated with in situ phenotyping and characterization of anatomical traits. The objectives of this thesis were to 1) review advancements in root phenotyping methodologies and past, present, and future predictions; 2) evaluate differences in root biomass accumulation and remobilization among 22 Virginia Tech-developed elite germplasm; 3) evaluate potential genetic variability for root biomass accumulation across breeding lines. Minimal genetic variation was observed for root biomass accumulation through time. Soil coring proved not to be a very effective method for capturing genetic variability of root biomass accumulation from a soil depth of 10 cm. However, a low genetic signal was also observed for shoot biomass, even though the entire field plot for each genotype was sampled. Yet, a considerably higher genetic signal was observed for plant height. These results suggest that both root and shoot biomass are complex, polygenic traits that require significantly more attention to evaluate genetic differences.
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    The Genetic Architecture of Grain Quality and its Temporal Relationship with Growth and Development in Winter Malting Barley (Hordeum vulgare)
    Loeb, Amelia (Virginia Tech, 2023-06-26)
    This thesis explores the genetic architecture of malting quality within the Virginia Tech barley breeding program, and discusses implications for imposing selection on complex traits that are difficult to phenotype. Malting quality measures are destructive, and can not be performed before selection must be made for advancement of breeding lines in winter barley. A growing body of evidence suggests that malt quality is influenced by malting regime, growing environment, line genotype, and the interactions between them. We aim to better understand the genetic effect on malt quality in two manners: first, as it relates to the genetic architecture regulating malt quality parameters, and second the relationship between genetic growth patterns to end-use malting traits. This study included two years of breeding trial data of two and six-row winter malt barley across two locations. Results of a genome-wide association scan and genomic prediction of malt quality traits indicated that they are largely quantitative traits with complex inheritance. Previous studies have identified quantitative trait loci and genes regulating malt quality traits in markedly different germplasm. Heritability of traits ranged from 0.27 to 0.72, while mean predictive abilities ranged from 0.45 to 0.74. Thus, selection on genomic estimated breeding values (gEBVs) should perform similarly to selection on single phenotypic observations of quality, but can be done within the same season. This indicates that genomic selection may be a viable method to accelerate genetic improvement of malting quality traits. The use of gEBVs requires that lines be genotyped with genome-wide markers, somewhat limiting the number of candidate individuals. Selection on growth and development traits genetically correlated with quality measures could allow for selection among a much greater number of candidates if high-throughput phenotypes can be collected on many ungenotyped indivduals. Growth and development was quantified by the near-infrared vegetation index (NDVI) extracted from aerial images captured from multiple time points throughout the growing season. Estimates of genetic correlation identified time points throughout the season when quality traits are related to growth and development. We demonstrated that aerial imagery can discern growth patterns in barley and suggest ways it can be incorporated into the breeding pipeline.
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    Genetic Variability of Growth and Development in Response to Nitrogen in Two Soft Winter Wheat Populations
    Hoyt, Cameron Michael (Virginia Tech, 2022-07-11)
    The use of nitrogen (N) fertilizers is both costly to farmers and contributes to environmental degradation. N applied to wheat accounts for 18% of N applied to farmland globally, making it a prime target for reducing and optimizing N application. Chapter I is a review on nitrogen use efficiency (NUE) in wheat, with emphasis on breeding efforts and genetic resources available to increase NUE. The concept of effective use of nitrogen (EUN) as yield per unit N applied as a measure of N use, is also introduced. Chapter II is a study using two bi-parental double haploid families to evaluate genetic variability of both the genetic main effects (intercept) and linear response to N (slope) and determine the feasibility of selection for EUN in wheat. Using cross validation, a genomic prediction accuracy of 0.68 for intercept and 0.50 for slope was found, indicating that EUN is under genetic control and can be selected for. The prospect of breeding for EUN under limited resources, i.e., using fewer N rates and fewer experimental plots, is also explored. It was found that two different N treatments can be used to produce accurate predictions of intercept and slope as high as 0.98 and 0.95, respectively. Chapter III uses the same population described in chapter II to further investigate feasibility of selection for EUN using a normalized difference vegetation index (NDVI) obtained from multi-spectral aerial images gathered throughout the growing season. Cumulative photosynthesis across the growing season was estimated by integration across the NDVI curve, and compared to grain yield estimates to determine the efficacy of aerial imaging to identify high EUN lines. NDVI values and the area under the NDVI curve were able to predict yield and had the strongest ability to predict yield in moderate to low N treatments, with R2 values as high as 0.81 and 0.78 respectively.
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    Multi-Species Genomics-Enabled Selection for Improving Agroecosystems Across Space and Time
    Wolfe, Marnin D.; Jannink, Jean-Luc; Kantar, Michael B.; Santantonio, Nicholas (2021-06-23)
    Plant breeding has been central to global increases in crop yields. Breeding deserves praise for helping to establish better food security, but also shares the responsibility of unintended consequences. Much work has been done describing alternative agricultural systems that seek to alleviate these externalities, however, breeding methods and breeding programs have largely not focused on these systems. Here we explore breeding and selection strategies that better align with these more diverse spatial and temporal agricultural systems.
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    Validation of DNA marker-assisted selection for forage biomass productivity under deficit irrigation in alfalfa
    Singh, Lovepreet; Pierce, Chris; Santantonio, Nicholas; Steiner, Robert; Miller, Don; Reich, Jon; Ray, Ian (Wiley, 2022-03)
    Drought and limited irrigation resources threaten agricultural sustainability in many regions of the world. Application of genomic-based breeding strategies may benefit crop variety development for these environments. Here, we provide a first report on the effect of deploying DNA marker-assisted selection (MAS) for the drought resilience quantitative trait in alfalfa (Medicago sativa L.). The goals of this study were to validate the effect of several quantitative trait loci (QTL) associated with alfalfa forage and crown-root (CR) biomass during drought and to determine their potential to improve forage yield of elite germplasm under water-limited conditions. Marker assisted selection was employed to introgress favorable or unfavorable DNA marker alleles affiliated with 10 biomass QTL into three elite backgrounds. Thirty-two populations were developed and evaluated for forage productivity over 3 yr under continuous deficit irrigation management in New Mexico, USA. Significant yield differences (ranging from -13 to 26%) were detected among some MAS-derived populations in all three elite backgrounds. Application of QTL MAS generally resulted in expected phenotypic responses within an elite genetic background that was similar to that in which the QTL were originally identified. However, relative performance of the populations varied substantially across the three genetic backgrounds. These outcomes indicate that QTL MAS can significantly affect forage productivity of elite alfalfa germplasm in drought-stressed environments. However, if biomass QTL are detected in donor germplasm that is genetically dissimilar to targeted elite populations, characterization of donor alleles may be warranted within elite backgrounds of interest to confirm their phenotypic effects prior to implementing MAS-based breeding.
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    Virginia-grown Barley for Craft Brewing: Evaluation of Free Amino Nitrogen Content and Malt Sensory Characteristics
    Carmody, Kyle Garrett (Virginia Tech, 2023-06-14)
    Regionally-Grown barley is in demand for craft malting and brewing in Virginia. Barley lines suited to both Virginia's climate and craft brewing applications are currently under development. Free amino nitrogen (FAN) is a malt quality parameter that influences beer flavor directly and via yeast metabolism during fermentation. FAN and the individual amino acids making up FAN influence yeast health, beer color development, flavor, and flavor stability. Despite potential impacts on beer quality, individual amino acid concentrations in barley and malt are not generally measured or monitored. The objective of this project is to evaluate and assess the conversion of FAN and individual amino acid concentrations during the malting and mashing process of genetically distinct varieties. An additional objective is to evaluate their malt sensory characteristics, to understand genetic variability therein. Raw barley and malt samples were subject to low temperature aqueous extraction, and wort was produced using an isothermal hot water extract technique. FAN and amino acid composition were determined for each line for raw barley, malt and wort extracts, prepared as described. Statistical analysis revealed that these lines had significantly different changes in FAN and amino acid composition. Sensory characteristics of malt hot steep teas were evaluated by forty (N=40) panelists with brewing experience using a sorting task to group malts with similar sensory characteristics, and to assign descriptors to those groups. From the sixteen (N=16) breeding lines, five (5) distinct sensory groups were identified. Taken together, our findings will inform the selection process for barley lines for craft brewing, and add to the knowledge of the extent to which free amino acid composition varies among eastern barley lines and along the malting and mashing processes.