Improving Soil Moisture States in WRF-Hydro Using SWOT Observations

No abstract availabl

Snow Depth Estimation, Structure, Prediction, and Hydrologic Modeling at the Kilometer Scale in the Colorado Rocky Mountains

Research focuses on observing and predicting spatial distribution of snow depth at the kilometer scale. Observation of spatial snow depth distribution is considered by its estimation from random, sparse observations and important factors affecting this estimation. Predicting spatial distribution of both snow depth and melt rates begins from simple hypothesis wherein the spatial distribution of snow depth is structured by the spatial distribution of controlling variables. Predictions made by this structured view are evaluated in spatial modeling of peak-accumulation snow depth and applied to spatial distribution of a point-scale, temperature-index model of snowmelt runoff using minimal parameter complexity. High-resolution light detection and ranging (LiDAR) measurements provide a rich backdrop for understanding estimation from sparse observations and developing our structured view of snow distribution. The data are used to illuminate the effects of sample size on estimation skill, the uncertainty in estimation due to random sampling, the effect of model resolution on estimation skill, and the difference between cross-validated skill and skill based on the entire distribution. None of these topics have previously been explored in the literature. The effect of predictor quality is also investigated. LiDAR derived predictors are compared to readily available predictors downloaded from the internet. Hierarchical cluster analysis is used to decompose spatial non-stationarity of snow depth and results match qualitative understanding of the spatial distribution of physical controls. The same methodology is then used to decompose spatial non-stationarity of physical controls and infer patterns of snow depth distribution independent of observations. Even when using readily-available predictors, predicted patterns require at least 100-200 observations to be matched by standard estimation methods. Predicted patterns are then applied to formulate a parameterized spatial distribution of a 1-dimensional, temperature-index model to account for heterogeneity of both snow accumulation and melt. Our new method introduces fewer or comparable parameters as the current subgrid distribution, the areal depletion curve. Given highly uncertain parameter selection in practical application, we demonstrate that our more physically intuitive method virtually always results in significant improvement in simulated streamflow timing when compared to the depletion curve method

Assimilating SWOT Water Surface Elevations into the WRF-Hydro Modeling System in Alaska Using HydroDART

No abstract availabl

Bitter gourd, Momordica charantia L., breeding lines differ in secondary metabolite content according to market type

Bitter gourd, Momordica charantia L., is an important commercial cucurbitaceous vegetable of enormous medicinal value in Asia because of its secondary metabolite content. We report here the characterization and evaluation of open-pollinated (OP) edible South Asian and Southeast Asian types of bitter gourd breeding lines, developed at the World Vegetable Center, for horticultural traits (11 OP) and secondary metabolites (10 OP) and their comparisons with commercial OP and F1 hybrid cultivars. Marketable yields of South Asian and Southeast Asian type breeding lines were comparable to the OP ‘BARI Karella 1’ and the hybrid ‘Benteng’, respectively.The bitter gourd cultivars and breeding lines included in this study exhibited specific patterns for five secondary metabolites (saponins, carotenoids, chlorophyll a and b, and vitamin C): in general the two cultivars and South Asian type breeding lines contained higher levels of secondary metabolites, e.g. carotenoids, than the Southeast Asian bitter gourd breeding lines.Some of these bitter gourd lines will be released to Asian home and school gardeners after conducting multi-location trials across Asia to improve vegetable consumption as a main task of bitter gourd breeding

Breeding for resistance to new and emerging lettuce diseases in California

Abstract: Preventing crop loss due to diseases has historically been the primary focus of public lettuce (Lactuca sativa) breeding efforts in the United States. Recent years have seen a shift in the industry, with increasing percentages of romaine and mixed lettuces being grown under intensive production systems. Possibly related to this change, several diseases have recently been reported for the first time or have increased in incidence. Two of these, lettuce dieback and crown rot, affect primarily romaine lettuce, whereas a third, Fusarium wilt, threatens all types. Lettuce dieback is caused by soilborne viruses of the family Tombusviridae. This disease may be identical to 'brown blight', which was widespread in the 1940s but vanished when resistant crisphead cultivars were developed. Fusarium wilt of lettuce was initially observed in California in 1990, and first caused significant crop losses in both California and Arizona in 2001. Crown rot of romaine, now known as Phoma basal rot, was first observed in the Salinas Valley of California in 2001. The cause of this disease was recently identified as Phoma exigua. Progress and results of breeding for genetic resistance to these diseases will be discussed

Genome-Wide Differentiation of Various Melon Horticultural Groups for Use in GWAS for Fruit Firmness and Construction of a High Resolution Genetic Map

Ajuts: Funding support is provided by Gus R. Douglass Institute (Evans Allen Project to Nimmakayala) and USDA-NIFA (2010-02247 and 2012-02511).Melon (Cucumis melo L.) is a phenotypically diverse eudicot diploid (2n = 2x = 24) has climacteric and non-climacteric morphotypes and show wide variation for fruit firmness, an important trait for transportation and shelf life. We generated 13,789 SNP markers using genotyping-by-sequencing (GBS) and anchored them to chromosomes to understand genome-wide fixation indices (Fst) between various melon morphotypes and genomewide linkage disequilibrium (LD) decay. The FST between accessions of cantalupensis and inodorus was 0.23. The FST between cantalupensis and various agrestis accessions was in a range of 0.19-0.53 and between inodorus and agrestis accessions was in a range of 0.21-0.59 indicating sporadic to wide ranging introgression. The EM (Expectation Maximization) algorithm was used for estimation of 1436 haplotypes. Average genome-wide LD decay for the melon genome was noted to be 9.27 Kb. In the current research, we focused on the genome-wide divergence underlying diverse melon horticultural groups. A high-resolution genetic map with 7153 loci was constructed. Genome-wide segregation distortion and recombination rate across various chromosomes were characterized. Melon has climacteric and non-climacteric morphotypes and wide variation for fruit firmness, a very important trait for transportation and shelf life. Various levels of QTLs were identified with high to moderate stringency and linked to fruit firmness using both genome-wide association study (GWAS) and biparental mapping. Gene annotation revealed some of the SNPs are located in β-D-xylosidase, glyoxysomal malate synthase, chloroplastic anthranilate phosphoribosyltransferase, and histidine kinase, the genes that were previously characterized for fruit ripening and softening in other crops

Cucurbits powdery mildew race identity and reaction of melon genotypes

Genetic resistance is one of the most suitable strategies to control cucurbit powdery mildew (CPM) on melon, incited by Podosphaera xanthii or Golovinomyces orontii. However, many races of these pathogens have been reported worldwide in recent years, what may compromise the effectiveness of this method. Thus, annual surveys of CPM races and the screening of germplasm for new sources of genetic resistance provide a vital support to melon breeding programs. This study aimed at identifying a natural population of CPM race under greenhouse conditions, as well as evaluating the reaction of local and exotic melon germplasm for CPM-resistance. CPM race identity was based on the reaction of eight race differentials: Védrantais, Nantais Oblong, PMR 45, PMR 5, WMR 29, Edisto 47, PI 414723 and PI 124111. Fifty-nine melon genotypes were evaluated, 53 of them being germplasm accessions, and six net melon elite-inbred lines, besides two net melon-type cultivars (Louis and Fantasy). Plants were evaluated using a visual scale for leaf lesions. The causal pathogen was confirmed to be P. xanthii, based on the presence of fibrosin bodies in conidia and the complete resistance response of winter melon (Benincasa hispida). Race 4 was identified for the first time in the São Paulo state, Brazil. Genotypes A19, A30, A32, C67, C384, JAB-3, JAB-7, JAB-9, JAB-11, JAB-18, JAB-20 and Solarking showed to be resistant to the race 4