Search

Cultivar resistance is a major asset for the management of crop diseases and can play an important role in agroecological transition. However, the wide deployment of a reduced number of resistance genes can lead to a rapid adaptation of pathogen populations and to a loss of resistance efficiency. The objective of this study was to characterize and discuss different trajectories of adult plant ratings for resistance to yellow rust in French wheat cultivars between 1963 and 2018. Among 719 cultivars assessed for at least 2 years, 590 cultivars showed no variation in their resistance scores, despite a mean of 4.3 years and up to 33 years of assessment. A set of descriptive variables was computed in order to compare the evolution of resistance score of 129 cultivars that experienced resistance variation. We applied a principal component analysis and a hierarchical clustering on principal components to this subdataset to constitute clusters corresponding to different cultivar profiles. Clusters C1 and C2 had small resistance variations (1–2 points on a 1–9 scale); Cluster C3 had long assessment durations and several small drops in resistance score and could be associated with quantitative resistance erosion; Cluster C4 included major drops in resistance score (4–5 points), often associated with known breakdowns of major resistance genes. Cases of limited drops in resistance score as a known resistance gene was broken down suggest the presence of efficient adult plant resistance. We discuss the use of information extracted from this dataset and methods to further explore sources of resistance to yellow rust present in French cultivars. [ABSTRACT FROM AUTHOR]

Crop diseases can cause major yield losses, so the ability to detect and identify them in their early stages is important for disease control. Deep learning methods have shown promise in classifying multiple diseases; however, many studies do not use datasets that represent real field conditions, necessitating either further image processing or reducing their applicability. In this paper, we present a dataset of wheat images taken in real growth situations, including both field and glasshouse conditions, with five categories: healthy plants and four foliar diseases, yellow rust, brown rust, powdery mildew and Septoria leaf blotch. This dataset was used to train a deep learning model. The resulting model, named CerealConv, reached a 97.05% classification accuracy. When tested against trained pathologists on a subset of images from the larger dataset, the model delivered an accuracy score 2% higher than the best‐performing pathologist. Image masks were used to show that the model was using the correct information to drive its classifications. These results show that deep learning networks are a viable tool for disease detection and classification in the field, and disease quantification is a logical next step. [ABSTRACT FROM AUTHOR]

Canada is one of the largest wheat producers in the world, and wheat is grown over an area spanning most of the southern latitudes, with the prairie region (provinces of Saskatchewan, Alberta, and Manitoba) being the main producer. Several pathogens and pests attack wheat, but at present fusarium head blight (FHB), stripe rust, and leaf spots are the most damaging diseases to wheat production in Canada. Historically, smuts, stem rust, and leaf rust caused major crop losses in Canada and can still pose serious threat if management practices are relaxed. Cropping practices used by Canadian farmers to grow and harvest wheat over the last century have influenced disease development and pathogen biology, affecting the severity, incidence, and prevalence of crop diseases over time. Changes such as reduced tillage coincide with emergence of residue‐borne diseases, such as FHB and leaf spots, while the deployment of resistant cultivars and increased fungicide use has resulted in the reduction of common bunt, stem, and leaf rust. This review will discuss the influence of long‐term cropping practices, alone or in combination, on the biology, emergence, and prevalence of wheat diseases in Canada over the last century. [ABSTRACT FROM AUTHOR]

Known and unknown genes conferring seedling and adult plant resistance (APR) to leaf rust, stem rust and stripe rust were detected either singly or in combination in a set of 136 African wheat genotypes using multi‐pathotype tests with characterized Australian Puccinia triticina (Pt), P. graminis f. sp. tritici (Pgt) and P. striiformis f. sp. tritici (Pst) pathotypes. Lines Beladi 132, IYN 68/9.44, Kenya Kifaru and Kenya Mbweha were postulated to carry resistance against multiple pathotypes of Pt, Pgt and Pst, whereas IAR/W/163‐3, Grano Di Moggio Tipo 44 and Trigo 48 had resistance against all pathotypes tested in the current study. Field evaluation with the three rust pathogens detected low to high APR in more than 50% of lines, and while most tested positive with markers linked to known APR genes (csLV34, csLV46G22, TM10KASPAR, csGS, Cfb5006 and csSr2), many carried unidentified and useful resistance to all three rusts. Genetic analysis of F3 mapping populations based on seven genotypes showed either monogenic or digenic inheritance of APR to leaf rust, stem rust and stripe rust. The lines postulated to carry effective uncharacterized seedling genes and APR genes are of great potential value in diversifying resistance to help achieve durable control of all three rust diseases of wheat. [ABSTRACT FROM AUTHOR]

Aneuploid and intervarietal chromosome substitution lines of wheat cv. Chinese Spring were used to study the effects of homoeologous chromosomes 7A, 7B and 7D upon adult plant resistance to yellow rust (Puccinia striiformis), Chromosomes 7B and 7D carry factors upon their short arms which interact to influence resistance. The results can be explained if there is a single locus determining resistance upon the short arms of chromosomes 7B and 7D. These loci may be homoeo-allelic; however, no evidence was found for a corresponding locus upon the short arm of chromosome 7A. Three homologous variants of the factor 7Ds were found but no variation was found for the factor on 7Bs. [ABSTRACT FROM AUTHOR]