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Almond anthracnose is a serious and emerging disease in several countries. All isolates causing almond anthracnose have been assigned to the Colletotrichum acutatum species complex, of which only C. fioriniae and C. godetiae have been associated with the disease to date. Here, we characterized Colletotrichum isolates from almond fruit affected by anthracnose in the Andalusia region. Two Colletotrichum isolates causing olive anthracnose were included for comparison. Morphological characteristics were useful for separating the isolates into groups based on colony morphology. Pathogenicity tests in almond, olive, and apple fruit showed differences in virulence and some degree of pathogenic specialization among isolates. Molecular characterization allowed clear identification of the Colletotrichum isolates tested. The olive isolates were identified as C. godetiae and C. nymphaeae, both previously identified in Andalusian olive orchards. Two phylogenetic species were identified among the almond isolates: C. godetiae, with gray colonies, which is well known in other countries, and C. acutatum, with pink-orange colonies. This species identification differs from those of pink-colony subpopulations described in other countries, which are C. fioriniae. Therefore, this study is also the first report of a new species of Colletotrichum causing almond anthracnose within the C. acutatum species complex.

English walnut (Juglans regia L.) is considered an economically important fruit crop worldwide. In Spain, little attention has been given to walnut diseases owing to the minor economic importance of the walnut crop in the country until recently. In 2017, typical symptoms of branch dieback and shoot blight of English walnut were observed in southern Spain. From 2017 to 2018, 10 commercial walnut orchards showing disease symptoms were surveyed. Botryosphaeriaceae and Diaporthe fungi were consistently isolated from affected shoots. Cytospora isolates were also recovered with minor relevance. Representative isolates of each fungal group were characterized based on colony and conidial morphology, optimum growth temperature, and comparison of DNA sequence data from the internal transcribed spacer, elongation factor 1-α, and β-tubulin genomic areas. Pathogenicity tests were performed on detached and attached shoots and on detached fruit by inoculating them with mycelial plugs. Botryosphaeriaceae and Diaporthe isolates had higher optimum growth temperatures (≈25 to 27°C) than Cytospora sp. (19.5°C). The following species were identified: Botryosphaeriaceae: Botryosphaeria dothidea, Diplodia seriata, Dothiorella sarmentorum, Dothiorella sp., Neofusicoccum mediterraneum, and N. parvum; Diaporthe: Diaporthe neotheicola, Dia. rhusicola, Diaporthe sp., and Phomopsis amygdali; and Cytospora sp. Botryosphaeriaceae isolates were the most aggressive fungi to walnut in all tissues evaluated, followed by Diaporthe isolates and Cytospora sp. N. parvum was the most virulent among the remaining species tested in any of the tissues evaluated, followed by B. dothidea or N. mediterraneum. This work is the first report to identify the fungal species causing this complex disease of English walnut in Spain and Europe.

BackgroundAlmond is an emerging crop due to the health benefits of almond consumption including nutritional, anti-inflammatory, and hypocholesterolaemia properties. Traditional almond producers were concentrated in California, Australia, and Mediterranean countries. However, almond is currently present in more than 50 countries due to breeding programs have modernized almond orchards by developing new varieties with improved traits related to late flowering (to reduce the risk of damage caused by late frosts) and tree architecture. Almond tree architecture and flowering are acquired and evaluated through intensive field labour for breeders. Flowering detection has traditionally been a very challenging objective. To our knowledge, there is no published information about monitoring of the tree flowering dynamics of a crop at the field scale by using color information from photogrammetric 3D point clouds and OBIA. As an alternative, a procedure based on the generation of colored photogrammetric point clouds using a low cost (RGB) camera on-board an unmanned aerial vehicle (UAV), and an semi-automatic object based image analysis (OBIA) algorithm was created for monitoring the flower density and flowering period of every almond tree in the framework of two almond phenotypic trials with different planting dates.ResultsOur method was useful for detecting the phenotypic variability of every almond variety by mapping and quantifying every tree height and volume as well as the flowering dynamics and flower density. There was a high level of agreement among the tree height, flower density, and blooming calendar derived from our procedure on both fields with the ones created from on-ground measured data. Some of the almond varieties showed a significant linear fit between its crown volume and their yield.ConclusionsOur findings could help breeders and researchers to reduce the gap between phenomics and genomics by generating accurate almond tree information in an efficient, non-destructive, and inexpensive way. The method described is also useful for data mining to select the most promising accessions, making it possible to assess specific multi-criteria ranking varieties, which are one of the main tools for breeders.

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