Premise: Apple orchards in the United States are under constant threat from a large number of pathogens and insects. Appropriate and timely deployment of disease management depends on early disease detection. Incorrect and delayed diagnosis can result in either excessive or inadequate use of chemicals, with increased production costs and increased environmental and health impacts.Methods and Results: We have manually captured 3651 high‐quality, real‐life symptom images of multiple apple foliar diseases, with variable illumination, angles, surfaces, and noise. A subset of images, expert‐annotated to create a pilot data set for apple scab, cedar apple rust, and healthy leaves, was made available to the Kaggle community for the Plant Pathology Challenge as part of the Fine‐Grained Visual Categorization (FGVC) workshop at the 2020 Computer Vision and Pattern Recognition conference (CVPR 2020). Participants were asked to use the image data set to train a machine learning model to classify disease categories and develop an algorithm for disease severity quantification. The top three area under the ROC curve (AUC) values submitted to the private leaderboard were 0.98445, 0.98182, and 0.98089. We also trained an off‐the‐shelf convolutional neural network on this data for disease classification and achieved 97% accuracy on a held‐out test set.Discussion: This data set will contribute toward development and deployment of machine learning–based automated plant disease classification algorithms to ultimately realize fast and accurate disease detection. We will continue to add images to the pilot data set for a larger, more comprehensive expert‐annotated data set for future Kaggle competitions and to explore more advanced methods for disease classification and quantification.

The challenge to produce more food for a rising global population on diminishing agricultural land is complicated by the effects of climate change on agricultural productivity. Although great progress has been made in crop improvement, so far most efforts have targeted above-ground traits. Roots are essential for plant adaptation and productivity, but are less studied due to the difficulty of observing them during the plant life cycle. Root system architecture, made up of structural features like root length, spread, number, and length of lateral roots, among others, exhibits great plasticity in response to environmental changes, and could be critical to developing crops with more efficient roots. Much of the research on root traits has thus far focused on the most common cereal crops and model plants. As cereal yields have reached their yield potential in some regions, understanding their root system may help overcome these plateaus. However, root and tuber crops such as potato, sweetpotato, cassava, and yam may hold more potential for providing food security in the future, and knowledge of their root system additionally focuses directly on the edible portion. Root-trait modeling for multiple stress scenarios, together with high-throughput phenotyping and genotyping techniques, robust databases, and data analytical pipelines, may provide a valuable base for a truly inclusive ‘green revolution’. In the current review, we discuss root system architecture with special reference to root and tuber crops, and how knowledge on genetics of root system architecture can be manipulated to improve their tolerance to abiotic stresses.

Summary: We present the first worldwide study on the apple ( Malus × domestica) fruit microbiome that examines questions regarding the composition and the assembly of microbial communities on and in apple fruit. Results revealed that the composition and structure of the fungal and bacterial communities associated with apple fruit vary and are highly dependent on geographical location. The study also confirmed that the spatial variation in the fungal and bacterial composition of different fruit tissues exists at a global level. Fungal diversity varied significantly in fruit harvested in different geographical locations and suggests a potential link between location and the type and rate of postharvest diseases that develop in each country. The global core microbiome of apple fruit was represented by several beneficial microbial taxa and accounted for a large fraction of the fruit microbial community. The study provides foundational information about the apple fruit microbiome that can be utilized for the development of novel approaches for the management of fruit quality and safety, as well as for reducing losses due to the establishment and proliferation of postharvest pathogens. It also lays the groundwork for studying the complex microbial interactions that occur on apple fruit surfaces.

Pear (Pyrus spp.) is one of the most common fruit crops grown in temperate regions worldwide. Genetic enhancement of fruit quality is a fundamental goal of pear breeding programs. The genetic control of pear fruit quality traits is highly quantitative, and development of high-density genetic maps can facilitate fine-mapping of quantitative trait loci (QTLs) and gene identification. Bin-mapping is a powerful method of constructing high-resolution genetic maps from large-scale genotyping datasets. We performed whole-genome sequencing of pear cultivars ‘Niitaka’ and ‘Hongxiangsu’ and their 176 F₁ progeny to identify genome-wide single-nucleotide polymorphism (SNP) markers for constructing a high-density bin-map of pear. This analysis yielded a total of 1.93 million SNPs and a genetic bin-map of 3190 markers spanning 1358.5 cM, with an average adjacent interval of 0.43 cM. This bin-map, along with other high-density genetic maps in pear, improved the reference genome assembly from 75.5 to 83.7% by re-anchoring the scaffolds. A quantitative genetic analysis identified 148 QTLs for 18 fruit-related traits; among them, QTLs for stone cell content, several key monosaccharides, and fruit pulp acids were identified for the first time in pear. A gene expression analysis of six pear cultivars identified 399 candidates in the identified QTL regions, which showed expression specific to fruit developmental stages in pear. Finally, we confirmed the function of PbrtMT1, a tonoplast monosaccharide transporter-related gene responsible for the enhancement of fructose accumulation in pear fruit on linkage group 16, in a transient transformation experiment. This study provides genomic and genetic resources as well as potential candidate genes for fruit quality improvement in pear.

Apple scab, caused by Venturia inaequalis, is a destructive fungal disease of major apple cultivars worldwide, most of which are moderately to highly susceptible. Thus, development of scab resistant cultivars is one of the highest priorities of apple breeding programs. The principal source of resistance for breeding programs has been the scab resistance gene Rvi6 that originated from the Japanese crabapple Malus floribunda (Sieb.) sel. 821. Isolates of V. inaequalis able to overcome Rvi6 have been identified in Europe, but have not yet been reported on the American continents. We recently discovered scab infection on M. floribunda 821 trees in a research orchard at Geneva, NY, U.S.A., where approximately 10% of the leaves bore profusely sporulating apple scab lesions, many of which had coalesced to cover entire leaves. We observed both chlorosis, typical to Rvi6, and pinpoint pitting symptoms typical to failed infections by V. inaequalis on hosts bearing the Rvi7 gene. We assessed genetic diversity and population genetic structure of 11 V. inaequalis isolates in total, of North American and European origin, isolated from M. floribunda 821, ‘Nova Easygro’, ‘Golden Delicious’, TSR33T239, ‘Schone van Boskoop’, and ‘Prima’, using 16,321 genome-wide SNPs. Population genetic structure and PCA separated the isolates into distinct European and U.S. groups. The forgoing suggests that the new Rvi6 virulent isolates emerged within U.S. populations, rather than being transported from Europe. The complete resistance breakdown in M. floribunda 821 but not in descendant cultivars, which kept their field resistance, suggests that durable resistance to apple scab will require a more comprehensive understanding of Rvi6 mediated resistance in diverse genetic backgrounds.