Grain Legume Genetics and Physiology Research Unit

Pullman, WA, United States

Grain Legume Genetics and Physiology Research Unit

Pullman, WA, United States
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Le May C.,Agrocampus Ouest | Le May C.,CNRS Institute of Genetics, Environment and Plant Protection | Le May C.,French National Institute for Agricultural Research | Onfroy C.,CNRS Institute of Genetics, Environment and Plant Protection | And 9 more authors.
European Journal of Plant Pathology | Year: 2017

Aphanomyces euteiches Drechsler is an oomycete pathogen of leguminous crops that causes root rot, a severe disease of pea (Pisum sativum L.) worldwide. An improved understanding of the genetic structure of A. euteiches populations would increase knowledge of pathogen evolution and assist in the design of strategies to develop pea cultivars and germplasm with stable disease resistance. Twenty six primers pairs were used to amplify Sequence Related Amplified Polymorphisms (SRAP) among 49 A. euteiches isolates sampled from pea. A total of 190 polymorphic SRAP bands were generated, of which 82 were polymorphic between all the A. euteiches isolates. The percentage of polymorphic bands per primer pair ranged from 22 to 75%. According to the PIC value estimated for each marker, 60% of the SRAP markers were highly to reasonably informative (PIC > 0.25). Genetic structure of A. euteiches populations sampled in different American and French locations showed low to high genetic diversity within populations. The largest variation occurred within countries, with a total estimated genetic diversity of 0.477 and 0.172 for American and French populations, respectively. This was particularly evident from a principal component analysis (PCA) and a Minimum Spanning Networks (MSN) based on genetic profiles of isolates, which generated two different clusters, one corresponding to the French isolates and four American isolates (MV1, MV5, MV7, Ath3), and the other to American isolates. A. euteiches populations from cultivated pea in France appeared as a single unstructured population, whereas American isolates of A. euteiches diverged into three different populations. © 2017 Koninklijke Nederlandse Planteziektenkundige Vereniging

Sankaran S.,Washington State University | Khot L.R.,Washington State University | Espinoza C.Z.,Washington State University | Jarolmasjed S.,Washington State University | And 7 more authors.
European Journal of Agronomy | Year: 2015

Global plant genetics research efforts have focused on developing high yielding, stress tolerant, and disease resistant row and field crop varieties that are more efficient in their use of agronomic inputs (water, nutrients, pesticides, etc.). Until recently, a key bottleneck in such research was the lack of high-throughput sensing technologies for effective and rapid evaluation of expressed phenotypes under field conditions for holistic data-driven decision making and variety selection. This review focuses on technological aspects of integrating unmanned aerial vehicles with imaging systems to enhance field phenotyping capabilities. The state-of-the-art of unmanned aerial vehicle technology for various applications including crop emergence, vigor, and characterization of yield potential of row and field crops has been reviewed. The potential of using aerial imaging to evaluate resistance/susceptibility to biotic and abiotic stress for crop breeding and precision production management has been discussed along with future perspectives and developments. © 2015 Elsevier B.V.

Bodah E.T.,Washington State University | Porter L.D.,Grain Legume Genetics and Physiology Research Unit | Chaves B.,Grain Legume Genetics and Physiology Research Unit | Dhingra A.,Washington State University
Euphytica | Year: 2016

Fusarium root rot caused by Fusarium solani f. sp. pisi (Fsp) can result in major yield losses in pea (Pisum sativum L.). Currently no fungicides effectively manage this disease. Previous studies evaluated the Pisum germplasm collection for resistance to Fsp, however, evaluations of commercial market classes of pea cultivars grown in the US, and elsewhere, have not been reported. This study evaluated pea accessions and commercial cultivars for Fsp resistance under greenhouse conditions. Accessions evaluated included pigmented lines with high levels of partial resistance to Fsp. Based on root disease severity (RDS) values, the most Fsp-resistant Austrian winter, green fresh, green dry, yellow dry, green winter and yellow winter pea were: PI 125673, 5003, ‘Banner’, ‘Carneval’, PS 05300234, and ‘Whistler’, respectively. Genotypes with a RDS value of 3.05, on a 0–6 scale with 6 being severe, or less had no significant (P ≤ 0.05) reductions in plant height, shoot dry weight, and root dry weight, compared to non-inoculated controls, establishing an important disease threshold value for pea breeders. Plant height, more than shoot dry weight or root dry weight, was the most highly negatively correlated growth parameter related to RDS in repeated tests based on Pearson’s Correlation coefficients. However, root dry weight was also a highly sensitive growth parameter affected by Fsp since 14 of 33 genotypes had significant (P ≤ 0.05) reductions in root dry weight compared to non-inoculated controls, while only 5 of 33 genotypes had significant reductions in plant height and/or shoot dry weight in combined tests. © 2016 Springer Science+Business Media Dordrecht (outside the USA)

Sankaran S.,Washington State University | Wang M.,Washington State University | Vandemark G.J.,Grain Legume Genetics and Physiology Research Unit
Engineering in Agriculture, Environment and Food | Year: 2015

In chickpeas, the seed size is a critical phenotype that needs to be evaluated carefully during variety development. The sieve analysis used for determining seed size distribution in legumes is labor intensive and time consuming method. An image-based method for sizing chickpeas seeds was developed in this study. Samples from a total of 72 plots from two different locations were harvested and seed size was analyzed. The results show that seed size calculated from image-based method was highly correlated to the ground-truth data, with a correlation coefficient of 0.90. The image processing technique provides rapid evaluation of seed size for phenotyping chickpeas and the method also can be adapted for similar seed types. © 2015 Asian Agricultural and Biological Engineering Association.

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