To support growers, Vineland has conducted a series of agronomic trials in 2017 and 2018 to better understand how to grow this crop efficiently. Results on spacing, days to maturity, harvesting, postharvesting and pest management have been compiled into an easy-to-read research update report.
Journal of Sensory Studies, May 30, 2019, e12524.
The article is available here at a cost
Abstract: Bowen, A.J., Blake, A. and J. Turecek. This study reports on the development of a process to objectively evaluate color using descriptive analysis. Panelists established a color lexicon (hue, lightness, evenness) and a two‐dimensional reference tool. The lexicon was applied to 23 baked sweet potato cultivars, along with a flavor lexicon. Color attributes all differentiated the products; most of the variation was due to color evenness. A consumer acceptance test (n = 204) was conducted on a subset of the products and showed a strong bias for specific color attributes. Consumers liked even, light‐orange hue; however, small changes in color dimensions impacted visual appeal. Overall characterization of products is described by a three‐factor principal component analysis solution. F1 (44% variance) correlated to moist texture and a redder‐orange hue and inversely correlated to stickiness. F2 (30% variance) correlated with high evenness and inverse correlation with acidic, bitter taste, and earthy aroma. F3 (15% variance) correlated to high sweet taste and caramel aroma.
Nature, May 17, 2019
Scientific Reports volume 9, Article number: 7522 (2019)
The article can be viewed here
Abstract: H. Elsadr, S. Sherif, T. Banks, D. Somers & S. Jayasankar. Maturity date (MD), defined as the duration between the first calendar day of the year and maturity, and fruit development period (FDP), defined as the duration between full bloom and maturity, are highly variable in peach [Prunus persica (L.) Batsch]. There is a need to discover molecular markers associated with these traits in order to enhance the efficiency and reliability of breeding for extending the harvest season in peach. An association mapping population consisting of 132 peach accessions was phenotypically evaluated for MD and FDP, and genotypically characterized using the genotyping-by-sequencing (GBS) approach. The phenotypic and genotypic data collected were used to conduct a genome-wide association study (GWAS). The GWAS identified three SNPs on chromosome 4 that are significantly associated with both FDP and MD. These three SNPs covered a region of 43,067 bp; we referred to this region as the MD/FDP locus. Seven genes were identified in the MD/FDP locus. One or more of these genes is believed to regulate some aspect of maturity in peach. The data reported here is expected to aid in marker-assisted seedling selection (MASS) targeted towards widening peach germplasm for maturity, particularly early maturity.
Journal of Risk Research, April 7, 2019
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Abstract: Whittingham, N., Boecker, A. and A. Grygorczyk. The present study investigates how the most foundational factors to individual differences – personality traits and personal values – affect the perceived safety of genetic modification and their relative importance. Publicly available communication data from 522 Twitter accounts discussing genetically modified foods and their safety was processed in two steps. First, accounts were categorized by the researchers as viewing GM foods as either safe or not safe. Second, using the IBM Watson platform, the Twitter communication data were subjected to lexical analysis to assign scores according to the Five Factor Model for personality traits and Schwartz’s basic individual values to the individual accounts. Logistic regression analyses were performed to determine how perceived GM food safety is linked to personality traits and individual values. Although both traits and values significantly contribute to explaining GM attitudes, personality traits strongly moderate the effect of individual values on risk perception.
In: Arai K., Kapoor S., Bhatia R. (eds) Intelligent Systems and Applications. IntelliSys 2018. Advances in Intelligent Systems and Computing, vol 869. Springer, Cham. pp. 1178-1184
The article is available here at a cost.
Abstract: Kashkoush, M. and G. Avigad. Mushrooms intended for the fresh market are solely harvested by hand. Accordingly, the mushroom industry depends heavily on human labor. It is estimated that 50% of a mushroom farm’s operational cost are associated with labor cost and that is mainly around harvesting. Harvesting mushrooms is arduous work, resulting in an exceptionally high employee turnover rate (up to 50% employee turnover rate is estimated for Canada). Recent increases in hourly wages, combined with tighter control on working hours and conditions, have further intensified the labor problem. One way to overcome the cost of labor, availability and quality/consistency of harvesting decisions is automation. The decision making component is, in fact, the bottle neck towards having an automated mushroom harvesting system. A Decision Support System (DSS) for mushroom harvesting has been recently developed and tested at Vineland Research and Innovation Centre, and is currently undergoing further tuning and enhancements.