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- ItemOpen AccessAddressing the threat of frost damage on peach floral buds through large-scale cold hardiness phenotyping, dynamic weather modeling and non-targeted metabolomic and proteomic analysis(Colorado State University. Libraries, 2023) Sterle, David, author; Minas, Ioannis, advisor; Sharp, Julia, committee member; Prenni, Jessica, committee member; Caspari, Horst, committee memberCold damage to reproductive tissues is the greatest threat to the profitability of peach (Prunus persica) growers worldwide. Cold hardiness is the extent to which peach floral buds super-freeze without suffering lethal damage. Although no changes are visible externally to floral buds for much of the dormant season, cold hardiness fluctuates as they acclimate, deacclimate and respond to abiotic stressors such as temperature or drought. A greater understanding of the mechanisms involved in these fluctuations involves accurate and frequent measurement of the extent to which cold hardiness is changing, and the ambient weather factors influencing the changes, at different stages of the dormant season. Warmer or more erratic temperature changes during the dormant season threatens peach floral buds to more frequently receive frost damage if cold hardiness becomes misaligned with the timing of lethally cold weather events. Statistical analysis of the trends and forces impacting the cold hardiness of floral buds can help identify significant patterns. These patterns can be used to better understand the physiological mechanisms affecting cold hardiness changes, and they can be used to help predict the impact of weather conditions on cold hardiness. In addition to their use in a practical sense by growers to aid in frost management decisions, accurate cold hardiness prediction models can be used to estimate what effects foreseeable climate effects can have on the outlook of future peach production. Metabolic changes are known to occur in dormant plants, although the effects of the metabolome in peaches on cold hardiness are unknown. Changes associated with cold hardiness likely follow several trends. One such trend is the fluctuations of metabolic abundances across the season, which are more associated with the endodormancy, and ecodormancy phases and the prebloom phase. These trends likely take place every dormant season as buds undergo a steady process of acclimating and deacclimating. Another trend is the response floral buds exhibit in response to acute cold events, in order to rapidly increase cold hardiness. The study of this response necessitates the monitoring of cold hardiness as well as the metabolic shift to the weather event. The response can be further elucidated by comparing cold hardiness and metabolic changes between genotypes that have different cold hardiness phenotypes. By exploring changes a cold hardy genotype undergoes, geneticists may be able to target certain metabolic expressions that may increase the frost tolerance of future cultivars. Since frost damage can be so destructive to peach production, it is necessary to understand the risks to the peach industry moving forward surrounding climate change, and it is also necessary to understand the extent to which frost tolerance can be improved in future cultivars. This study uses a multifaceted approach to cold hardiness which involves improved and large-scale cold hardiness phenotyping using differential thermal analysis, dynamic weather prediction models and associated metabolic regulation understanding.
- ItemOpen AccessBridging the gap between biofortification and consumption: evaluating sorghum grain carotenoid degradation(Colorado State University. Libraries, 2023) Lepard, Ariel, author; Rhodes, Davina, advisor; Van Buiten, Charlene, committee member; Prenni, Jessica, committee member; Scanlin, Laurie, committee memberSorghum (Sorghum bicolor) is a major staple cereal crop consumed in sub-Saharan Africa and Southeast Asia, where some of the highest rates of vitamin A deficiency (VAD) are found. As with most cereals, sorghum has low concentrations of provitamin A carotenoids, which are converted to vitamin A in the body. Biofortification provides an opportunity to address VAD through the nutritional improvement of sorghum grain using a non-transgenic breeding approach to increase grain carotenoids. Though vitamin A biofortification in sorghum is possible, it is unknown if breeding for high carotenoids in the grain negatively affects carotenoid pathway functions in other tissues. Additionally, it is unknown if degradation during postharvest processing occurs to a significant degree in biofortified grain. To establish how breeding for high carotenoids in the grain affects the carotenoid pathway in other plant tissues, expression of ten genes in the carotenoid precursor, biosynthesis, or degradation pathways were evaluated in the grain, leaf, and root tissues. A correlation in the gene expression within the plant tissue, but not between the plant tissues, was found for most genes, which suggests that several of the carotenoid precursor, biosynthesis, and degradation genes are controlled by tissue-specific regulation. Correlation of carotenoid concentrations and gene expression was also found to be tissue specific, which further suggests tissue-specific regulation. The selection of genes with tissue-specific regulation for marker-assisted breeding reduces the chances of grain biofortification negatively affecting other tissues. Once carotenoids have been increased in the grain, it must be noted that vitamin A is not stable in most storage, processing, and cooking environments due to oxidative stress from light, heat, and oxygen. The degradation of the nutritional quality through post-harvest processing was evaluated by sampling carotenoid grain throughout harvest, drying, storage, processing, and cooking. Individual processing steps did not cause significant degradation but added up to significant degradation by the final cooking step, with ~39% of β-carotene loss. No significant difference between the loss in the different storage temperatures or cooking styles was seen. An increase in the target value from 4 μg β-carotene/g of sorghum to 5.6 μg/g will be needed to account for processing loss in order to provide 50% of the estimated average requirement (EAR) of vitamin A. Overall, both the information on tissue specific gene expression, and post-harvest degradation will further advance the development of carotenoid biofortified sorghum lines.
- ItemOpen AccessImpact of various factors on partial least squares model robustness for nondestructive peach fruit quality assessment(Colorado State University. Libraries, 2023) Pott, Jakob, author; Minas, Ioannis, advisor; Eakes, Joe, committee member; Koslovsky, Matt, committee memberGiven declining fruit consumption due to poor fruit quality and large amounts of waste, peach growers have continuously suffered from financial loss and the industry has seen a sharp decline in recent decades. Due to the time consuming and destructive nature of conventional fruit quality assessment, many peach growers prioritize fruit characteristics conducive to shipping and storage over characteristics which correlate with consumer acceptance. This prioritization has resulted in the poor-quality fruit which consumers have grown to associate with fresh peaches and contributed to large annual waste. A potential solution is the use of near-infrared spectroscopy (Vis-NIRS) paired with partial least squares (PLS) modeling, as a field deployable method that can be used to measure preharvest internal fruit quality to produce information quickly and non-destructively. These qualities offer an answer to declining fruit quality and waste. Although promising, the technology is only as good as the data used to train the models. Quality data is hard to collect as it requires the consideration of many factors including the temperature of the sample and the inclusion of biological variability impacted by seasonal changes, cultivar differences, fruit maturity, and many management factors such as crop load, rootstocks, irrigation regimes, and training systems to capture the relationships needed for good model performance. In tree fruit research, handheld Vis-NIRS devices have been used to predict internal quality parameters such as sweetness (dry matter content, DMC; soluble solids concentration, SSC) and fruit physiological maturity related to chlorophyll content (index of absorbance difference, IAD). Although accurate, the statistical models used to make such predictions often struggle with robustness across cultivars and growing seasons and regions due to a lack of biological variability, or a lack of representative data from factors like temperature. These challenges have led to slow industry adoption. To address this issue, models for 13 distinct peach cultivars were constructed by combining data from two seasons (2016 and 2021) followed by external validation with data from a third season (2022). The data from 2016 was collected over a range of preharvest factors, fruit development stages and temperatures, and the inclusion of 2021 data added additional biological variability. External validation produced error rates of 0.36 - 0.42%, 0.59 - 0.63%, and 0.05 - 0.04 for DMC, SSC and IAD, respectively, across the 13 peach cultivars indicating the models trained in 2021 were robust and performing at an acceptable level to impact grower decision making. It was observed that the additional inclusion of data from different cultivars and growing environments, as well as a third growing season (2017) did not significantly impact model performance. The lack of improvement suggests that the data from each year contain enough covariate variability to cover a broad range of measurements (i.e. input values) that growers and researchers are likely to observe when collecting data to predict peach quality in different orchards or seasons. This insensitivity to various environmental and growing conditions, generally referred to as external factors, due to the variability captured in the data used to build model is characteristic of a robust model.
- ItemOpen AccessPlant growth under photovoltaic arrays of varying transparencies – a study of plant response to light and shadow in agrivoltaic systems(Colorado State University. Libraries, 2023) Hickey, Thomas, author; Bousselot, Jennifer, advisor; Uchanski, Mark, advisor; Harrow, Del, committee memberAmidst the rising global pressures put on the interdependent systems in the food, energy, and water nexus, this document highlights the potential for systems-based solutions at the intersection of food cultivation, ecosystem services, and energy production in urban and rural environments. Agrivoltaics (APV) is a land-use model that enables simultaneous cultivation of food crops and electricity generation on the same plot of land. Agrivoltaic systems integrate solar photovoltaic (PV) energy generation with agricultural operations, maximizing the utilization of solar energy. This approach has gained significant research interest in the United States with scalable implementation is on the horizon. Research efforts at Colorado State University (CSU) aim to advance the understanding of plant responses to various shade conditions under PV arrays, benefiting stakeholders in agriculture, solar energy industries, policymakers, and governmental agencies. In particular, agrivoltaic research conducted at CSU's Horticulture and Landscape Architecture (HLA) department has focused on open field specialty crops and native pollinator plant species while documenting the overarching light and temperature growing environment. A replicated 2-year crop trial was conducted at the open field test site, comparing crop yield and growing conditions under three different PV module types with varying transparencies to traditional full sun production. Statistical analysis revealed a reduction in squash yield directly under the PV panels while no significant differences in yield for bell peppers, jalapeno peppers, lettuce and tomatoes growing north and south of the arrays. In a separate study, a simulated green roof structure was constructed around an existing PV array at CSU's Foothills Campus to explore the feasibility of rooftop agrivoltaics. A one-year study of six native pollinator plant species was conducted to assess differences in establishment, survivability, growth index, and growing conditions between full sun and PV shade environments. Overall, there were no statistically significant differences in mean Plant Growth Index (PGI) throughout the establishment season, however, notable variations in overwinter survivability were observed. In both studies the PV modules moderated the environment, resulting in lower maximum daytime ambient temperatures and even greater reduction in soil temperature throughout the growing season. Light levels are reduced under all PV module types with the least reduction under semi-transparent modules. Variations in growing conditions in these APV systems indicate the need for further research to optimize PV systems in order to maximize energy production and plant vitality.
- ItemOpen AccessQuantitative analysis of runoff in green roof structures in the Colorado Front Range(Colorado State University. Libraries, 2023) Salerno, Amanda, author; Bousselot, Jennifer, advisor; Choi, Jane, committee member; Sharvelle, Sybil, committee memberThe green roof capacity of retaining rainwater extends the runoff duration further than the actual rain event, releasing part of it slowly into the drainage system and positively impacting it. However, the volumes will depend on the size of the rainfall event and the green roof design. Therefore, specific attention should be paid when designing a new green roof project, like geographic locations, materials peculiarities, and the project's needs, including biotic and abiotic design components. The need for more local data regarding this analysis in Western North America is still significant. Therefore, this study aims to analyze the impact of three different green roof systems on Colorado's climate by reduction of runoff, retention volume, and runoff coefficient. Moreover, we aim to analyze plant health and substrate moisture retention and components for better water capture. To achieve the goals outlined, three different green roofs technologies, with different retention and detention layers technologies, and a control roof, a conventional low slope roof for comparison, are placed at Colorado State University in Fort Collins, Colorado, United States; the systems include a Sempergreen Purple Roof, a Sempergreen Sponge Roof, and a Green Roof Technology with an Extenduct Drainage System; all were vegetated with Sedum mats, base slopes of 1% toward the rooftop drain, and measuring 1m x 2m. The drainage systems in each green roof were designed to test performance under steady, low-intensity, high-intensity, short-duration, and long-duration rainfall conditions and simulated rain events. All the systems have the same drain system connected to a v-notch weir. Volume, speed, and time were measured to quantify the runoff from all roof systems. Our data suggests that green roof volume capture varies with preexisting substrate moisture conditions, frequency and size of storms, and drainage layer components. Green Roof Technology with an Extenduct Drainage System and Sponge Roof had the best volume retention in less intense, more frequent, and back-to-back rainfall events. On the other hand, Purple Roof performed better for larger rain events that might lead to flooding and urban drainage concerns in cities. Ultimately, the Colorado-specific data from this study will enable the intentional design of green roofs to optimize plant health and water management.