English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Yield stability (simply ‘‘stability’’) is a crop genotype’s performance over a range of environmental conditions, such that a specific genotype may be less sensitive to environmental change (i.e., above-average stability) or more sensitive to environmental change (i.e., below-average stability) relative to other genotypes. The ideal genotype for most crops is believed to have both above-average yield and above-average stability. The objective of the study was to determine the pattern of genotype adoption and use of processing sweet corn in relation to yield and stability. I hypothesized that if yield and stability influence decision-making on genotype choice, then differences among commercial genotypes in such traits would relate to the pattern of adoption and use of those genotypes. Stability analyses of ear mass and case production were conducted on processing sweet corn genotypes grown in varied environments of the United States’ UpperMidwest and Pacific Northwest. Yield and stability of the 12 most tested genotypes were then related to the extent of their adoption and use by a sweet corn processing company over a 20-year period. Although some genotypes exhibited above-average yield or above-average stability, data revealed there was no evidence of both traits in individual genotypes currently used in processing sweet corn. Adoption of genotypes with below-average yield or stability was less than other genotypes. Genotype adoption pattern of case production showed the greatest proportion of adoption of above-average stability genotypes. Stable case production across all environments is a more important trait in a genotype to the sweet corn processor than a genotype with record yields under favorable conditions. This conclusion is consistent with the industry’s need to have a predictable level of performance in the processing facility, through which all raw product must flow, on a daily basis for the about three-month window of harvest in the northern United States. Yield stability refers to a crop genotype’s performance over a range of environmental conditions. The predominant agronomic concept of yield stability, hereafter called simply ‘‘stability,’’ is that a genotype’s yield changes in a predictable manner across an environmental gradient (Becker and Leon, 1988). A genotype’s stability is measured in relation to other genotypes, such that the genotype of interest may be less sensitive to environmental change (i.e., above-average stability) or more sensitive to environmental change (i.e., below-average stability) relative to other genotypes. The ideal genotype for most crops is purported to have high yield and high stability over a wide range of environments (Dia et al., 2016; Lu’quez et al., 2002; Mohammed et al., 2016). Some authors have questioned whether yield and stability are linked. Genetic gains in yield potential of wheat (Triticum aestivum L.) corresponded with a general decrease in stability (Calderini and Slafer, 1999). Yield and stability of genotypes were negatively correlated in cowpea [Vigna unguiculata (L.) Walp.] field trials (Padi, 2007). In field corn (Zea mays L.), Jensen and Cavalieri (1983) reported a weak negative relationship between yield and stability. In other field corn research, high-yielding genotypes generally displayed average stability (Tollenaar and Lee, 2002). However, Lobell et al. (2014) showed that U.S. Midwest field corn yield increases in recent years were accompanied by greater sensitivity to drought stress and high vapor pressure deficit. Although the relationship between yield and stability remains in question, to the best of our knowledge, the extent to which genotype yield and stability relates to genotype adoption (i.e., extent to which cultivars are actually used) has not been examined in any crop. Processing sweet corn is grown under contract whereby the processing company determines the genotype for each field contracted. Therefore, genotype adoption in processing sweet corn is driven by the processor, not the grower. Furthermore, there are distinctly different ways to quantify ‘‘yield’’ of processing sweet corn. Contract growers are compensated for mass of unhusked ears per unit area, hereafter called ear mass. Case production is the number of cases of canned sweet corn produced per hectare. Therefore, although ear mass determines gross profit margin to the grower, case production accounts for gross profit margin to the sweet corn processor (Williams, 2014). Yield stability of sweet corn is unknown. Commercial sweet corn genotypes vary in tolerance to several stresses, including diseases (Pataky et al., 2011), herbicides (Nordby et al., 2008), and weed interference (So et al., 2009). More recently, differential tolerance to plant population density has been reported among sweet corn genotypes grown for processing (Williams, 2012). Based on surveys of growers’ fields, Williams (2012) found that density-tolerant genotypes were being under-planted. Multiple lines of evidence indicate sweet corn yield could be increased by growing density-tolerant genotypes at higher plant densities than currently done (Williams, 2012, 2015). Undoubtedly, various factors affect adoption of a specific genotype, including ease of growing, harvesting, and processing. Conceivably, if yield and stability influence processors’ decisionmaking on genotype choice, then differences among commercial genotypes in such traits would relate to the pattern of adoption and use of those genotypes. The objective of the study was to determine the pattern of genotype adoption and use of processing sweet corn in relation to yield and stability. The following hypotheses were tested: 1) adoption and use of genotypes with below-average yield or stability will be less than other genotypes, 2) the most widely used genotypes will show above-average yield or stability, and 3) above-average stability is a more important trait in a genotype than above-average yield. Materials and Methods To protect the confidentiality of parties who provided data for this research, details regarding locations and genotypes will be limited to only those aspects essential to addressing the aforementioned hypotheses. Genotype trials. Genotype trials were placed in locations representative of the major processing sweet corn production regions of the United States, namely the Pacific Northwest and Upper Midwest. Production environments in the Pacific Northwest are characterized by a cold semiarid climate and center pivot irrigation. Production environments in the Upper Midwest are characterized by a warm-summer or hot-summer humid continental climate. Generally in the Received for publication 10 Oct. 2017. Accepted for publication 2 Nov. 2017. I express sincere gratitude to the anonymous processing company for providing the datasets used in this research. Mention of a trademark, proprietary product, or vendor does not constitute a guarantee or warranty of the product by the U.S. Department of Agriculture and does not imply its approval to the exclusion of other products or vendors that also may be suitable. Corresponding author. E-mail: martin.williams@ ars.usda.gov. 1748 HORTSCIENCE VOL. 52(12) DECEMBER 2017 Midwest, fine-textured soils are rainfed and coarse-textured soils are irrigated. Genotype trials were conducted from 2004 to 2015. Each year, trials were planted over the wide range of planting dates common to processing sweet corn production (Table 1). In the Upper Midwest, planting dates ranged from 5 May to 1 July. In the Pacific Northwest, planting dates ranged from 31 Mar. to 19 June. Production practices, including seeding rate, fertilizer application, and pest management, were standard to commercial production at each locale. The experimental protocol was designed as a randomized complete block with three replications. Experimental units (i.e., plots) measured 3.0 m wide (four rows on 76-cm row spacing) by 9.2 m long. Treatments consisted of genotypes of shrunken2 (sh2) processing sweet corn. On average, 23 genotypes were included per trial; however, not all genotypes were present in every trial. Only the 12 most commonly tested genotypes in the present study are reported. Consistent with previous stability research, genotypes were tested in 15 or more environments (Hildebrand and Russell, 1996; Mohammed et al., 2016). All genotypes were developed for main-season production and ranged in maturity from 78.1 to 87.7 d. Genotypes were harvested at 76% kernel moisture. Plots were hand harvested from the center two rows of each plot, 6 m in length. Ears were then husked using a husking bed, and fresh kernels were cut from the cob with an industry-grade hand-fed corn cutter. Both critical measurements of crop yield were recorded; namely, ear mass and case production. Ear mass was total mass of unhusked ears, reported in Mt·ha. Case production was number of cases of canned sweet corn produced per hectare, where each case represents 6.13 kg of fresh kernel mass. Stability analysis. Several statistical methods for evaluating stability have been developed, including univariate and multivariate models (Gauch, 2006; Kang, 1993). Several univariate models have been found to measure the same aspect of stability (Dia et al., 2016), whereas multivariate models are particularly useful in determining genotypes most suitable for specific environments (Mohammed et al., 2016). Regardless of the specific method, analyses of both yield (means) and stability (variances) are more informative than individual statistics (Dia et al., 2016). Because the focus of this research was on the pattern of genotype adoption and use, we chose a standard analytical approach that directly quantified genotype stability. Regression analysis was used to calculate stability of the 12 genotypes. The procedure calculates an environmental yield index as the mean yield of all genotypes (i.e., population mean) in each environment (Finlay and Wilkinson, 1963). Th

Genotype Adoption in Processing Sweet Corn Relates to Stability in Case Production