Weed management in sweet corn can be costly; genetic improvements in sweet corn competitiveness may reduce this expense. Competitive ability can exist as weed suppressive ability (WSA), or crop tolerance (CT). Previous studies in corn have found year of hybrid release, maturity, plant height, leaf angle and leafiness may affect WSA, while hybrid era, maturity, and plant height may affect CT. However, many of these studies were limited to very few genotypes. The objective of this study was to assess the effects of phenomorphological traits on sweet corn competitiveness and the inheritance of these traits. An incomplete half-diallel from seven historic sweet corn inbred lines of varying morphologies was evaluated in a split-block randomized complete block design in three environments. Forage sorghum was interplanted in half of the blocks to act as a model weed. Significant differences among hybrids were generally found for both phenomorphological traits and traits measuring WSA and CT, such as sorghum biomass and yield stability, respectively. Crop plant height was most predictive of WSA and CT. In this set of genotypes, competitive ability may be passed with reasonable fidelity from parent to offspring, suggesting that sweet corn could be bred for competitive ability.

The value of selection in conventional breeding trials of cultivars destined for organic systems depends on the correlation between systems and relative heritability of key traits. Genotype by environment interactions is a common phenomenon in plant breeding trials. Thus, multienvironment testing to identify stable genotypes is a high priority for organic systems. In addition, This article is protected by copyright. All rights reserved. because organic systems have limited inputs to buffer the environment, they may have greater spatial heterogeneity which may be better accounted for by additional spatial blocking terms beyond traditional randomized complete block design. Over two years, we evaluated 100 hybrid and 40 inbred sweet corn genotypes in 11 trials in organic systems across 6 locations and evaluated the addition of augmented incomplete block and row-column design to estimate the performance of sweet corn genotypes. Hybrids differed in their performance for all tested traits. Inbred parents differed in per se performance and general combining ability for all traits. For the hybrid entries, modelling spatial factors beyond the replicated complete blocks improved the model fit for days to anthesis, plant height, ear height, husk protection, ear width and ear length. For inbred entries, modelling spatial factors beyond the replicated complete blocks improved \ model fit for plant height, ear height, tenderness, and ear width. Wricke's ecovalence (W 2 i) was a useful measure of stability, correlating reasonably well with two of the three stability statistics considered in this analysis. Based on Wricke's ecovalence, some inbred parents were more stable than others across tested environments in their combining ability for all traits.

Local production of organic tomatoes marketed directly to consumers is growing rapidly in the U.S. Midwest. Growers serving this market need cultivars that are well adapted to local climatic conditions, are competitive under organic management, and have end-use quality characteristics desired by their customers. Participatory plant breeding is a powerful, cost-effective approach with potential to engage growers in development of new cultivars optimally adapted to organic farming systems. To initiate a participatory breeding program for organic tomatoes an online grower survey was conducted to identify key plant traits, and a diverse set of tomato germplasm was evaluated under organic management to better understand horticultural constraints and identify adapted germplasm for further development. Tomato growers rated flavor as their top breeding priority, followed by disease resistance with late blight (LB) (Phytophthora infestans), early blight (EB) (Alternaria solani), and septoria leaf spot (SLS) (Septoria lycopersici) identified as the most problematic diseases. In field trials, foliar diseases were problematic in both years, though many entries exhibited partial resistance. Differences among entries in resistance to insect pests such as hornworms (Manduca sexta) were also observed. Yield varied widely among entries with some of the F1 hybrids and heirloom cultivars performing well despite significant disease pressure. Overall, we identified existing cultivars and F1 hybrids with potential to meet the immediate needs of Midwest organic tomato growers, and segregating breeding populations for further selection to be conducted on working organic farms.

Plant breeding and seed issues are of growing importance in organic farming, but more regionally specific information is needed. In 2012, we surveyed Wisconsin organic vegetable growers regarding: a) general characteristics and farm practices; b) challenges in accessing organic seed; c) plant breeding priorities; and d) improving access to appropriate plant breeding and seed systems. Results suggest that growers had more difficulty accessing satisfactory genetics than seed quality, and that seed access was more problematic for growers with larger farming operations. Diverse plant breeding priorities, combined with prevalent variety trialing and seed saving, suggest a good fit with participatory plant breeding.

Plant breeders need efficient systems to identify which inbreds to combine to create new hybrid cultivars. The North Carolina Design II (NC DII) is a useful mating design to evaluate the potential of hybrid varieties and their inbred parents. Genomic best linear unbiased prediction (GBLUP) models, either with or without the inclusion of a dominance term in the model, have been found to be an efficient method for using rich marker sets for prediction. This study used marker data and phenotypic data collected in 11 organic trials across 6 locations on 40 inbred sweet corn (Zea mays This article is protected by copyright. All rights reserved.L.) genotypes and 100 hybrid progenies formed from 4 disconnected NC DII mating blocks to predict performance of untested sweet corn hybrids. In 2017, validation trials of 24 previously untested hybrids were grown in five organic environments to assess the correlation between actual performance and the performance predicted by GBLUP or NC DII general combining abilities (GCAs).Five-fold cross-validation accuracy ranged from 0.29 to 0.82 for the GBLUP predictions based on additive effects alone, and from 0.70 to 0.91 for GBLUP predictions based on combined additive and dominance effects. For all traits except flavor, addition of dominance effects to the model increased the cross-validation accuracy. Correlations between values measured in the 2017 validation trials and values predicted from the 2015 and 2016 training trials ranged from 0.36 to 0.