Development of a Decision Support System for the Management of Mummy Berry Disease in Northwestern Washington.

Mummy berry, caused by Monilinia vaccinii-corymbosi, is the most important disease of the northern highbush blueberry (Vaccinium corymbosum L.) in North America and can cause up to 70% yield losses in affected fields. A key event in the mummy berry disease cycle is the primary infection phase where ascospores are released by apothecia that infect emerging floral and vegetative tissues. Current management of mummy berry disease in northwestern Washington is predominantly reliant on the prevention of primary infections through prophylactic, calendar-based fungicide spray applications early in the growing season. To improve the understanding of risk during these periods and to help tailor management strategies, we developed a decision support system (DSS) based on field records spanning over five seasons and four locations in northwestern Washington. Environmental conditions across the region were highly uniform but different dynamics of apothecial development were observed under high- and low-management regimes. Based on our analysis, we suggest basing the initial iteration of the DSS on two sub-models. The first sub-model predicts the onset of apothecia based on chill-unit accumulation under high- and low-management regimes, and the second predicts primary infection risk, which provides opportunities to improve the timing of fungicide applications. The synoptic DSS proposed here is based on the current biological knowledge of the pathosystem and available data for the northwestern Washington region. We provide the analysis and the DSS implementation and evaluation as an open-source repository, providing opportunities for further improvements. Finally, we provide suggestions for future research and the operational efforts needed for improving the utility and accuracy of the mummy berry DSS.

First report of preharvest fruit rot of 'Pink Lady' apples caused by Colletotrichum fructicola in Italy.

In late summer 2019, a severe outbreak of fruit rot was observed in commercial 'Pink Lady' apple orchards (>20 ha in total) in the region Emilia-Romagna (Northern Italy). The symptoms on the fruit appeared as small circular red to brown lesions. Disease incidences of over 50% of the fruits were observed. To isolate the causal agent, 15 affected apples were collected and small portions of fruit flesh were excised from the lesion margin and placed on potato dextrose agar (PDA). The plates were incubated at 20°C in the dark, and pure cultures were obtained by transferring hyphal tips on PDA. The cultures showed light to dark gray, cottony mycelium, with the underside of the culture being brownish and becoming black with age. Conidia (n=20) were cylindrical, aseptate, hyaline, rounded at both ends, and 12.5 to 20.0 × 5.0 to 7.5 µm. The morphological characteristics were consistent with descriptions of Colletotrichum species of the C. gloeosporioides species complex, including C. fructicola (Weir et al. 2012). The identity of two representative isolates (PinkL2 & PinkL3) from different apples was confirmed by means of multi-locus gene sequencing. Genomic DNA was extracted using the LGC Mag Plant Kit (Berlin, Germany) in combination with the Kingfisher method (Waltham, USA). Molecular identification was conducted by sequencing the ITS1/ITS4 region and partial sequences of four other gene regions: chitin synthase (CHS), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), actin (ACT), and beta-tubulin (TUB). The sequences have been deposited in GenBank under accession numbers MT421924 & MT424894 (ITS), MT424612 & MT424613 (CHS), MT424616 & MT424617 (GAPDH), MT424614 & MT424615 (ACT), and MT424620 & MT424621 (TUB). MegaBLAST analysis revealed that our ITS sequences matched with 100% identity to Colletotrichum fructicola (Genbank JX010177). The CHS, GAPDH, ACT and TUB sequences of both isolates were 100% identical with C. fructicola culture collection sequences in Genbank (JX009807, JX009923, JX009436 and JX010400, respectively), confirming the identity of these isolates as C. fructicola. Koch's postulates were performed with 10 mature 'Pink Lady' apples. Surface sterilized fruit were inoculated with 20 µl of a suspension of 105 conidia ml-1 after wounding with a needle. The fruits were incubated at 20˚C at high relative humidity. Typical symptoms appeared within 4 days on all fruit. Mock-inoculated controls with sterile water remained symptomless. The fungus was reisolated and confirmed as C. fructicola by morphology and sequencing of all previously used genes. Until recently the reported causal agents of bitter rot of apple in Europe belong to the Colletotrichum acutatum species complex (Grammen et al. 2019). C. fructicola, belonging to C. gloeosporioides species complex, is known to cause bitter rot of apple in the USA, Korea, Brazil, and Uruguay (Kim et al. 2018; Velho et al. 2015). There is only one report of bitter rot associated with C. fructicola on apple in Europe (France) (Nodet et al. 2019). However, C. fructicola is also the potential agent of Glomerella leaf spot (GLS) of apple (Velho et al. 2015; 2019). To the best of our knowledge this is the first report of C. fructicola on apples in Italy. It is important to stress that the C. gloeosporioides species complex is still being resolved and new species on apple continue to be identified, e.g. C. chrysophilum that is very closely related to C. fructicola (Khodadadi et al. 2020). Given the risks of this pathogen the presence of C. fructicola in European apple orchards should be assessed and management strategies developed.

First report of Phytophthora chlamydospora causing postharvest fruit rot on apples and pears in the Netherlands.

Apple (Malus domestica) and pear (Pyrus communis) are important fruit crops in the Netherlands, with total production of 269,000 tons and 402,000 tons in 2018, respectively. In 2018 and 2019 postharvest fruit rots were observed on the apple variety Elstar (one observation) and pear varieties Conference and Doyenné du Comice (multiple observations). The symptoms were found after storage in controlled atmosphere storage facilities on fruits from different orchards across the Netherlands. Disease incidences up to 50% of the stored fruit were observed. The diseased fruits showed circular brown to black spots with irregular and diffuse margins that enlarged rapidly to form distinctive rings, typical of Phytophthora infection. Several Phytophthora species are currently known to cause fruit rot of pome fruit (Sanchez et al. 2019). To isolate the causal agent, small portions of fruit flesh from decayed fruit were excised from the lesion margin and placed on potato dextrose agar (PDA). The plates were incubated at 20°C in the dark, and pure cultures were obtained by transferring hyphal tips on PDA. The colonies were white with petaloid and rosette-shaped patterns. The isolates grown on PDA formed irregularly branched hyphae, produced persistent non-papillate sporangia, usually on unbranched sporangiophores and chlamydospores were produced. The characteristics were similar to those described for Phytophthora chlamydospora Brasier and Hansen sp. nov. (Hansen et al. 2015). The identity of three representative isolates (KP00219, WURR121 and WURR119) from two different pear cultivars (Conference and Doyenné) and one apple cultivar (Elstar), respectively, was confirmed by means of multilocus gene sequencing. Genomic DNA was extracted using the LGC Mag Plant Kit (Berlin, Germany) in combination with the Kingfisher method (Waltham, USA). Sequences of ITS region, COX and EF were amplified and sequenced. The sequences have been deposited in GenBank (Accession Nos. MT125889, MT125891, and MT125890 [ITS], MT153610, MT153612, and MT153611 [COX], MT153613, MT153615, and MT153614 [EF]. MegaBLAST analysis revealed that our ITS, COX and EF sequences matched with 100% identity to Phytophthora chlamydospora isolates in GenBank AF541901 and AF541902 (ITS), JF771548 and JF771549 (COX), JN936005 and JN936006 (EF). In order to perform Koch's postulates a pathogenicity assay was performed using mycelial plugs of the cultures KP00219, on pear cv. Conference, and WURR119 and WURR121, on apple cv. Elstar and pear cv. Doyenné du Comice. Ten apples and pears per cultivar were disinfected, and wounded using a sterile cork borer in the middle of the fruit surface area. A mycelial plug of a two weeks old fungal culture was then placed onto the fruit. Placement of a PDA plug without fungal growth was used as a control. The fruits were incubated at 18˚C at high relative humidity for 7 days. Symptoms appeared within 3 days on all fruits. Mock-inoculated controls remained symptomless. The fungus was reisolated and confirmed as P. chlamydospora by morphology and sequencing. P. chlamydospora is found in streams and wet soil worldwide, and has only rarely been recovered as a pathogen from ornamental and woody species (Blomquist et al. 2012; Ginetti et al. 2014; Türkölmez et al. 2016). To our knowledge, this is the first report confirming P. chlamydospora as a causal agent of fruit rot of commercially produced apple and pear cultivars in the Netherlands.

Predicting Ascospore Release of Monilinia vaccinii-corymbosi of Blueberry with Machine Learning.

Mummy berry, caused by Monilinia vaccinii-corymbosi, causes economic losses of highbush blueberry in the U.S. Pacific Northwest (PNW). Apothecia develop from mummified berries overwintering on soil surfaces and produce ascospores that infect tissue emerging from floral and vegetative buds. Disease control currently relies on fungicides applied on a calendar basis rather than inoculum availability. To establish a prediction model for ascospore release, apothecial development was tracked in three fields, one in western Oregon and two in northwestern Washington in 2015 and 2016. Air and soil temperature, precipitation, soil moisture, leaf wetness, relative humidity and solar radiation were monitored using in-field weather stations and Washington State University's AgWeatherNet stations. Four modeling approaches were compared: logistic regression, multivariate adaptive regression splines, artificial neural networks, and random forest. A supervised learning approach was used to train the models on two data sets: training (70%) and testing (30%). The importance of environmental factors was calculated for each model separately. Soil temperature, soil moisture, and solar radiation were identified as the most important factors influencing ascospore release. Random forest models, with 78% accuracy, showed the best performance compared with the other models. Results of this research helps PNW blueberry growers to optimize fungicide use and reduce production costs.