A Mechanistic Model of Botrytis cinerea on Grapevines That Includes Weather, Vine Growth Stage, and the Main Infection Pathways

Integration of mathematical modeling and target-based application of biocontrol agents for the control of Botrytis cinerea in vineyards

BACKGROUND

Biocontrol agents (BCAs) are alternatives to synthetic fungicides with low risk to the environment and human health. Although several studies on the biocontrol of gray mold in vineyards have been performed, it is necessary to improve the usage of BCAs in fields conditions. Therefore, in the present study, BCAs were used both in calendar-based [based on four growth stages (GSs), i.e., flowering, pre-bunch closure, veraison, and before harvest] and predictive model-based strategies (only when Botrytis cinerea infection risk was predicted by the model). The BCAs applied during the seasons were selected considering the grapevine GSs. Treatments performed with BCAs were compared with synthetic fungicide treatments and an untreated control. The trials were conducted in three experimental vineyards with four epidemics. To evaluate the level of gray mold control of each treatment, disease severity was assessed at harvest and the presence of latent infection was evaluated.

RESULTS

The integrative use of the predictive model and BCAs provided satisfactory levels of gray mold control, with gray mold severity levels significantly lower (P < 0.001) than those of the untreated control, which had severity values (< 7%) similar to those observed with synthetic fungicides following both calendar and model-based strategies.

CONCLUSIONS

The integrative use of the predictive model and BCAs represents a valid alternative to conventional methods of gray mold control in vineyards, with more than 75% reduction in fungicide usage. © 2024 Society of Chemical Industry.

Biocontrol of Botrytis cinerea as Influenced by Grapevine Growth Stages and Environmental Conditions

The growth of four commercial biocontrol agents (BCAs: Bacillus amyloliquefaciens (BAD), Aureobasidium pullulans (APD), Metschnikowia fructicola (MFN), and Trichoderma atroviride (TAS)) was evaluated using turbidimetric assays on artificial substrates mimicking the chemical berry composition at four stages: pea-sized berries, veraison, softening, and ripe berries. The response of BCA growth differed among BCAs. Subsequently, the BCAs' population size was assessed after 1 to 13 days of incubation on the substrate mimicking ripe berries at 15 to 35 °C. The population size of BAD increased with temperatures, while that of MFN decreased; the population sizes of APD and TAS showed bell-shaped patterns with lower growth at 15 or 35 °C. Finally, the BCAs were applied to ripe berries and then incubated at 15 to 30 °C. After 1 to 13 days, the berries were inoculated with B. cinerea and incubated for 7 days, after which the BCA control efficacy was assessed. The highest control was observed at 25 °C for BAD and APD, at 15 to 20 °C for MFN, and at 25 to 30 °C for TAS. The results confirm that the plant substrates and temperature affect the population size of the BCA following application; temperature also affects the preventative efficacy of BCA against B. cinerea.

Efficacy of preharvest application of biocontrol agents against gray mold in grapevine

The use of biocontrol agents (BCAs) represents a promising alternative to conventional methods for the management of gray mold in vineyards during the berry ripening stage. The main advantages of BCAs are the short preharvest interval and lack of chemical fungicide residues in wine. In this study, eight commercial BCAs (based on different Bacillus or Trichoderma species and strains, Aureobasidium pullulans, Metschnikowia fructicola, and Pythium oligandrum) and a reference fungicide (boscalid) were applied to a vineyard during berry ripening over three seasons to evaluate the dynamics over time in terms of their relative efficacies in gray mold control. At 1-13 days after application of BCAs to the berry surfaces in field conditions, the berries were collected and artificially inoculated with conidia of Botrytis cinerea under controlled laboratory conditions, and gray mold severity was observed after 7 days of incubation. Significant differences were observed in gray mold severity among years, according to the number of days the BCAs grew on the berry surface before B. cinerea inoculation, and the season by day interaction (altogether accounting for >80% of the experimental variance). The variability in BCA efficacy was closely related to the environmental conditions at the time of application and in the following days. Overall, the BCA efficacy increased with the degree days accumulated between BCA application in the vineyard and B. cinerea inoculation in the dry (no rain) periods (r = 0.914, P = 0.001). Rainfall and the associated drop in temperature caused a relevant reduction of BCA efficacy. These results demonstrate that BCAs are an effective alternative to conventional chemicals for the preharvest control of gray mold in vineyards. However, environmental conditions can considerably affect the BCA efficacy.

Disease Forecasting for the Rational Management of Grapevine Mildews in the Chianti Bio-District (Tuscany)

Downy and powdery mildews are major grapevine diseases. In organic viticulture, a few fungicides with protectant activities (copper and sulphur in particular) can be used, and their preventative application frequently leads to unneeded spraying. The adoption of an epidemiological disease forecasting model could optimise the timing of treatments and achieve a good level of disease protection. In this study, the effectiveness of the EPI (Etat Potentiel d'Infection) model in predicting infection risk for downy and powdery mildews was evaluated in nine organic vineyards located in Panzano in Chianti (FI), over a 2-year period (2020-2021). The reliability of the EPI model was investigated by comparing the disease intensities, the number of fungicide sprayings, the quantities of the fungicides (kg/ha), and the costs of the treatment achieved, with or without the use of the model, in a vineyard. The results obtained over two seasons indicated that, in most cases, the use of the EPI model accurately signalled the infection risk and allowed for a reduction in the frequency and cost of spraying, particularly for powdery mildew control (-40% sprayings, -20% costs compared to the farmer's schedule), without compromising crop protection. The use of the EPI model can, therefore, contribute to more-sustainable disease management in organic viticulture.

Biochemical and genetic characterization of Botrytis cinerea laboratory mutants resistant to propamidine

BACKGROUND

Botrytis cinerea, the causal agent of gray mold, is one of the top 10 fungal pathogens in the world. Propamidine, an aromatic diamidine compound, exhibited both protective and therapeutic effects against B. cinerea. However, the resistance risk and mechanism of B. cinerea to propamidine are unclear.

RESULTS

Twelve high and stable resistant mutants were obtained from B. cinerea B05.10 by fungicide induction. Compared with the parental strain, the biological fitness of the mutants, including growth rate, spore germination, pathogenicity, and oxalic acid decreased significantly. There was no cross-resistance among propamidine and other commonly used fungicides, while the efficacy of propamidine against the resistance mutants declined. In addition, the cell membrane permeability, substance metabolism, and defense enzyme activities of the resistant mutants were significantly increased compared with the wild strain. Whole-genome sequencing of all resistant mutants found that there were 32 SNPs and nine InDels. Importantly, nine common single-point mutant genes in the exon region were found in all 12 resistant mutants, and these genes were related to multiple pathways in vivo, indicating that many factors contributed to the formation of propamidine resistance.

CONCLUSION

These data suggested the resistance risk of B. cinerea to propamidine was low to moderate and the mechanism of propamidine was different from that of the existing fungicides. These results will increase understanding of the resistance mechanism of propamidine and provide a critical basis for the rational design of pesticide molecules based on targets. © 2022 Society of Chemical Industry.

Information on disease resistance patterns of grape varieties may improve disease management

Resistance to downy mildew (DM) and powdery mildew (PM) contributes to sustainable vineyard management by reducing the diseases and the need for fungicide applications. Resistant varieties vary in their degree of resistance to DM and PM, and in their susceptibility to other diseases. As a consequence, fungicide use may differ among varieties depending on their "resistance patterns" (i.e., the resistance level of a variety toward all of the diseases in the vineyard). The resistance patterns of 16 grapevine varieties to DM, PM, black rot (BR), and gray mold (GM) were evaluated over a 4-year period under field conditions. Disease severity was assessed on leaves and bunches, and the AUDPC (Area Under Disease Progress Curve) was calculated to represent the epidemic progress. GM was found only on bunches and only at very low levels, irrespective of the year or variety, and was therefore excluded from further analyses. The varieties were then grouped into four resistance patterns: i) low resistance to DM and PM, intermediate resistance to BR; ii) high resistance to DM, intermediate resistance to PM, low resistance to BR; iii) intermediate resistance to DM and BR, low resistance to PM; and iv) high resistance to DM, PM, and BR. AUDPC values on leaves were positively correlated with AUDPC values on bunches for susceptible varieties but not for resistant ones, with the exception of PM. Therefore, bioassays with leaves can be used to predict the resistance of bunches to DM and BR for susceptible varieties but not for resistant ones. These results may facilitate both strategic and tactical decisions for the sustainable management of grapevine diseases.

A Review of Cultural Practices for Botrytis Bunch Rot Management in New Zealand Vineyards

Botrytis bunch rot of grapes (BBR) causes substantial crop and wine quality issues globally. Past and present foundations for BBR control are based upon synthetic fungicides and varying forms of canopy management. Many authors regard the continued dependence on fungicides as unsustainable and have urged greater deployment of cultural, biological and nutritional strategies. However, in contrast to organic wine production, the uptake of alternative strategies in conventional vineyards has been slow based on cost and perceived reliability issues. This review summarises research from many different wine growing regions in New Zealand with the aim of demonstrating how traditional and newly developed cultural control practices have cost-effectively reduced BBR. In addition to reviewing traditional cultural practices (e.g., leaf removal), mechanical tools are described that remove floral trash and mechanically shake the vines. Multi-omics has improved our knowledge of the underlying changes to grape berries after mechanical shaking. Exogenous applications of calcium may correct calcium deficiencies in the berry skin and reduce BBR but the outcome varies between cultivar and regions. Nitrogen aids in grapevine defence against BBR but remains a complex and difficult nutrient to manage. The sustainable growth of organics and The European Green Deal will stimulate researchers to evaluate new combinations of non-chemical BBR strategies in the next decade.

Virulence-related metabolism is activated in Botrytis cinerea mostly in the interaction with tolerant green grapes that remain largely unaffected in contrast with susceptible green grapes

Botrytis cinerea is responsible for the gray mold disease, severely affecting Vitis vinifera grapevine and hundreds of other economically important crops. However, many mechanisms of this fruit-pathogen interaction remain unknown. The combined analysis of the transcriptome and metabolome of green fruits infected with B. cinerea from susceptible and tolerant genotypes was never performed in any fleshy fruit, mostly because green fruits are widely accepted to be resistant to this fungus. In this work, peppercorn-sized fruits were infected in the field or mock-treated, and berries were collected at green (EL32) stage from a susceptible (Trincadeira) and a tolerant (Syrah) variety. RNAseq and GC-MS data suggested that Syrah exhibited a pre-activated/basal defense relying on specific signaling pathways, hormonal regulation, namely jasmonate and ethylene metabolisms, and linked to phenylpropanoid metabolism. In addition, putative defensive metabolites such as shikimic, ursolic/ oleanolic, and trans-4-hydroxy cinnamic acids, and epigallocatechin were more abundant in Syrah than Trincadeira before infection. On the other hand, Trincadeira underwent relevant metabolic reprogramming upon infection but was unable to contain disease progression. RNA-seq analysis of the fungus in planta revealed an opposite scenario with higher gene expression activity within B. cinerea during infection of the tolerant cultivar and less activity in infected Trincadeira berries. The results suggested an activated virulence state during interaction with the tolerant cultivar without visible disease symptoms. Together, this study brings novel insights related to early infection strategies of B. cinerea and the green berry defense against necrotrophic fungi.

Mechanisms of Action of Microbial Biocontrol Agents against Botrytis cinerea

Botrytis cinerea is a phytopathogenic fungus responsible for economic losses from USD 10 to 100 billion worldwide. It affects more than 1400 plant species, thus becoming one of the main threats to the agriculture systems. The application of fungicides has for years been an efficient way to control this disease. However, fungicides have negative environmental consequences that have changed popular opinion and clarified the need for more sustainable solutions. Biopesticides are products formulated based on microorganisms (bacteria or fungi) with antifungal activity through various mechanisms. This review gathers the most important mechanisms of antifungal activities and the microorganisms that possess them. Among the different modes of action, there are included the production of diffusible molecules, both antimicrobial molecules and siderophores; production of volatile organic compounds; production of hydrolytic enzymes; and other mechanisms, such as the competition and induction of systemic resistance, triggering an interaction at different levels and inhibition based on complex systems for the production of molecules and regulation of crop biology. Such a variety of mechanisms results in a powerful weapon against B. cinerea; some of them have been tested and are already used in the agricultural production with satisfactory results.

Modeling the Effects of the Environment and the Host Plant on the Ripe Rot of Grapes, Caused by the Colletotrichum Species

Ripe rot caused by Colletotrichum spp. is a serious threat in many vineyards, and its control relies mainly on the repeated use of fungicides. A mechanistic, dynamic model for the prediction of grape ripe rot epidemics was developed by using information and data from a systematic literature review. The model accounts for (i) the production and maturation of the primary inoculum; (ii) the infection caused by the primary inoculum; (iii) the production of a secondary inoculum; and (iv) the infection caused by the secondary inoculum. The model was validated in 19 epidemics (vineyard × year combinations) between 1980 and 2014 in China, Japan, and the USA. The observed disease incidence was correlated with the number of infection events predicted by the model and their severity (ρ = 0.878 and 0.533, respectively, n = 37, p ≤ 0.001). The model also accurately predicted the disease severity progress during the season, with a concordance correlation coefficient of 0.975 between the observed and predicted data. Overall, the model provided an accurate description of the grape ripe rot system, as well as reliable predictions of infection events and of disease progress during the season. The model increases our understanding of ripe rot epidemics in vineyards and will help guide disease control. By using the model, growers can schedule fungicides based on the risk of infection rather than on a seasonal spray calendar.

Development and Evaluation of a Model that Predicts Grapevine Anthracnose Caused by Elsinoë ampelina

Grapevine anthracnose caused by Elsinoë ampelina is a serious threat in many vineyards, and its control requires repeated application of fungicides, usually on a calendar basis. A better understanding of the pathogen life cycle would help growers manage anthracnose more safely and effectively. After conducting a systematic literature search of grape anthracnose, we used the retrieved information and data to develop a mechanistic model based on systems analysis. The model simulates production and maturation of primary inoculum, infection caused by both primary and secondary conidia, and lesion formation and production of secondary inoculum. The model was validated for its ability to predict first seasonal onset of anthracnose lesions by using 8 years of data collected at Auckland, New Zealand, and disease progress during the season by using 3 years of data collected at Frelighsburg, Canada. Overall, the model provided accurate predictions of infection occurrence, with 0.96 accuracy, 0.91 sensitivity, and 0.97 specificity. The model also showed good accuracy for predicting disease progress, with a concordance correlation coefficient between observed and predicted disease severities of 0.92, a root mean square error of 0.14, and a coefficient of residual mass of 0.06. Although the model failed to predict 10 of 110 real infection periods, these missed infections led to only mild disease symptoms. We therefore conclude that the model is reliable and can be used to reduce the costs of anthracnose management by improving the timing of fungicide applications.

Biosensor Technologies for Early Detection and Quantification of Plant Pathogens

Plant pathogens are a major reason of reduced crop productivity and may lead to a shortage of food for both human and animal consumption. Although chemical control remains the main method to reduce foliar fungal disease incidence, frequent use can lead to loss of susceptibility in the fungal population. Furthermore, over-spraying can cause environmental contamination and poses a heavy financial burden on growers. To prevent or control disease epidemics, it is important for growers to be able to detect causal pathogen accurately, sensitively, and rapidly, so that the best practice disease management strategies can be chosen and enacted. To reach this goal, many culture-dependent, biochemical, and molecular methods have been developed for plant pathogen detection. However, these methods lack accuracy, specificity, reliability, and rapidity, and they are generally not suitable for in-situ analysis. Accordingly, there is strong interest in developing biosensing systems for early and accurate pathogen detection. There is also great scope to translate innovative nanoparticle-based biosensor approaches developed initially for human disease diagnostics for early detection of plant disease-causing pathogens. In this review, we compare conventional methods used in plant disease diagnostics with new sensing technologies in particular with deeper focus on electrochemical and optical biosensors that may be applied for plant pathogen detection and management. In addition, we discuss challenges facing biosensors and new capability the technology provides to informing disease management strategies.

Towards Sensor-Based Phenotyping of Physical Barriers of Grapes to Improve Resilience to Botrytis Bunch Rot

Botrytis bunch rot is one of the economically most important fungal diseases in viticulture (aside from powdery mildew and downy mildew). So far, no active defense mechanisms and resistance loci against the necrotrophic pathogen are known. Since long, breeders are mostly selecting phenotypically for loose grape bunches, which is recently the most evident trait to decrease the infection risk of Botrytis bunch rot. This study focused on plant phenomics of multiple traits by applying fast sensor technologies to measure berry impedance (Z _REL ), berry texture, and 3D bunch architecture. As references, microscopic determined cuticle thickness (MS _CT ) and infestation of grapes with Botrytis bunch rot were used. Z _REL hereby is correlated to grape bunch density OIV204 (r = -0.6), cuticle thickness of berries (r = 0.61), mean berry diameter (r = -0.63), and Botrytis bunch rot (r = -0.7). However, no correlation between Z _REL and berry maturity or berry texture was observed. In comparison to the category of traditional varieties (mostly susceptible), elite breeding lines show an impressive increased Z _REL value (+317) and a 1-μm thicker berry cuticle. Quantitative trait loci (QTLs) on LGs 2, 6, 11, 15, and 16 were identified for Z _REL and berry texture explaining a phenotypic variance of between 3 and 10.9%. These QTLs providing a starting point for the development of molecular markers. Modeling of Z _REL and berry texture to predict Botrytis bunch rot resilience revealed McFadden R ² = 0.99. Taken together, this study shows that in addition to loose grape bunch architecture, berry diameter, Z _REL , and berry texture values are probably additional parameters that could be used to identify and select Botrytis-resilient wine grape varieties. Furthermore, grapevine breeding will benefit from these reliable methodologies permitting high-throughput screening for additional resilience traits of mechanical and physical barriers to Botrytis bunch rot. The findings might also be applicable to table grapes and other fruit crops like tomato or blueberry.

Use of LAMP for Assessing Botrytis cinerea Colonization of Bunch Trash and Latent Infection of Berries in Grapevines

A real-time loop-mediated isothermal amplification (LAMP) assay was evaluated for the detection of Botrytis cinerea in grapevine bunch trash, immature berries, and ripening berries. A simple method for the preparation of crude extracts of grape tissue was also developed for on-site LAMP analysis. When tested with 14 other fungal species frequently found in grapevines, the LAMP assay was specific and sensitive to a B. cinerea DNA quantity of 0.1 ng/µL. The sensitivity was further tested using bunch trash samples with B. cinerea colonization levels between 6 and 100% and with bulk-berry samples composed of 4 pathogen-free berries or 4 berries among which 25 to 100% had been inoculated with B. cinerea. The LAMP assay detected the lowest B. cinerea colonization level tested in bunch trash and in immature and mature berries in less than 20 min. In single-berry experiments, LAMP amplified B. cinerea DNA from all artificially inoculated individual immature and mature berries. No amplification occurred in B. cinerea-free material. The real-time LAMP assay has the potential to be used as a rapid on-site diagnostic tool for assessing B. cinerea colonization in bunch trash and B. cinerea latent infections in berries, which represent critical stages for decision-making about disease management.

Metagenomics analysis of fungal communities associated with postharvest diseases in pear fruits under the effect of management practices

An amplicon metagenomic approach based on the ITS1 region of fungal rDNA was employed to identify the composition of fungal communities associated with diseases of pear fruits during postharvest storage. The sampled fruits were harvested at an orchard using routine management practices involving treatments with various chemical fungicides and were transferred to a storage packinghouse. Effective tags of reading sequences clustered into 53 OTUs whereas Ascomycota was the dominant phylum (83.4%) followed by Basidiomycota (15.8%). Our results revealed that four genera, Penicillium, Rhodotorula, Alternaria and Cladosporium were the most abundant representing 59-95% of the relative abundance per sample. The interruption of chemical treatments during the last month before harvest altered the structure of the fungal community of fruits among untreated and treated samples, mainly in cases of relative abundance of Penicillium and Rhodotorula genera. We hypothesize that various antagonistic interactions might occur on fruit surfaces among the detected fungal genera whose relative abundances were affected by fungicide treatments. Interestingly, some common pre- and postharvest pear fungal pathogens were either less present (such as Moniliana), or undetected (such as Aspergillus, Venturia and Septoria) in untreated and treated samples.

Consideration of Latent Infections Improves the Prediction of Botrytis Bunch Rot Severity in Vineyards

The current study validated a mechanistic model for Botrytis cinerea on grapevine with data from 23 independent Botrytis bunch rot (BBR) epidemics (combinations of vineyards × year) that occurred between 1997 and 2018 in Italy, France, and Spain. The model was operated for each vineyard by using weather data and vine growth stages to anticipate, at any day of the vine-growing season, the disease severity (DS) at harvest (severe, DS ≥ 15%; intermediate, 5 < DS < 15%; and mild, DS ≤ 5%). To determine the ability of the model to account for latent infections, postharvest incubation assays were also conducted using mature berries without symptoms or signs of BBR. The model correctly classified the severity of 15 of 23 epidemics (65% of epidemics) when the classification was based on field assessments of BBR severity; when the model was operated to include BBR severity after incubation assays, its ability to correctly predict BBR severity increased from 65% to >87%. This result showed that the model correctly accounts for latent infections, which is important because latent infections can substantially increase DS. The model was sensitive and specific, with the false-positive and false-negative proportion of model predictions equal to 0.24 and 0, respectively. Therefore, the model may be considered a reliable tool for decision-making for BBR control in vineyards.

Reduction of Botrytis cinerea Colonization of and Sporulation on Bunch Trash

Botrytis bunch rot (BBR) of grapevine, caused by Botrytis cinerea, is commonly managed by fungicide (FUN) sprays at flowering (A), at prebunch closure (B), at veraison (C), and before harvest. Applications at A, B, and C are recommended to reduce B. cinerea colonization of bunch trash and the production of conidia during berry ripening. The effects of these applications were previously evaluated as reductions in BBR severity at harvest rather than as reductions in bunch trash colonization and sporulation by B. cinerea. This study investigated the effects of FUNs (a commercial mixture of fludioxonil and cyprodonil), biological control agents (BCAs; Aureobasium pullulans and Trichoderma atroviride), and botanicals (BOTs; a commercial mixture of eugenol, geraniol, and thymol) applied at different timings (A, B, C, or ABC) compared with a nontreated control (NT) on B. cinerea bunch trash colonization and sporulation in vineyards. The ability of B. cinerea to colonize the bunch trash (as indicated by B. cinerea DNA content) and sporulate (as indicated by the number of conidia produced under optimal laboratory conditions) was highly variable, and this variability was higher between years (2015 to 2018) than among the three vineyards and three sampling times (i.e., 1 week after applications at A, B, and C). B. cinerea sporulation on bunch trash was significantly lower in plots treated with FUN than in NT in only 3 of 18 cases (3 vineyards × 2 years × 3 sampling times). FUN applications, however, significantly reduced B. cinerea colonization of bunch trash compared with NT; for colonization, BCA efficacy was similar to that of FUN, but BOT efficacy was variable. For all products, colonization reduction was the same with application at A versus ABC, meaning that the effect of an early season application lasted from flowering to 1 week after veraison. These results indicate that the early season control of B. cinerea is important to reduce the saprophytic colonization of bunch trash, especially when the risk of BBR is high.

Biocontrol of Botrytis cinerea on Grape Berries as Influenced by Temperature and Humidity

Six commercial biocontrol agents (BCAs, containing Aureobasidium pullulans, Bacillus amyloliquefaciens, Bacillus amyloliquefaciens plantarum, Bacillus subtilis, Pythium oligandrum, or Trichoderma atroviride) were applied to ripening berries that were then incubated at one of four temperatures (T, 15, 20, 25, and 30°C) and one of four relative humidity levels (RH, 60, 80, 90, and 100%). After 1 to 13 days of incubation (BCA colonization period), the berries were inoculated with conidia of Botrytis cinerea and kept at 25°C and 100% RH for 7 days, at which time Botrytis bunch rot (BBR) was assessed. The response of BBR control to T/RH conditions and BCA colonization period differed among BCAs; the coefficients of variation among the BCAs ranged from 44.7 to 72.4%. An equation was developed that accounted for the combined effects of T, RH, and BCA colonization period on BBR control. The equation, which had an R²>0.94, could help farmers select the BCA to be used for a specific application based on weather conditions at the time of treatment and in the following days.

Critical Success Factors for the Adoption of Decision Tools in IPM

The rational control of harmful organisms for plants (pests) forms the basis of the integrated pest management (IPM), and is fundamental for ensuring agricultural productivity while maintaining economic and environmental sustainability. The high level of complexity of the decision processes linked to IPM requires careful evaluations, both economic and environmental, considering benefits and costs associated with a management action. Plant protection models and other decision tools (DTs) have assumed a key role in supporting decision-making process in pest management. The advantages of using DTs in IPM are linked to their capacity to process and analyze complex information and to provide outputs supporting the decision-making process. Nowadays, several DTs have been developed, tackling different issues, and have been applied in different climatic conditions and agricultural contexts. However, their use in crop management is restricted to only certain areas and/or to a limited group of users. In this paper, we review the current state-of-the-art related to DTs for IPM, investigate the main modelling approaches used, and the different fields of application. We also identify key drivers influencing their adoption and provide a set of critical success factors to guide the development and facilitate the adoption of DTs in crop protection.

Advanced Diagnostic Approaches for Necrotrophic Fungal Pathogens of Temperate Legumes With a Focus on Botrytis spp

Plant pathogens reduce global crop productivity by up to 40% per annum, causing enormous economic loss and potential environmental effects from chemical management practices. Thus, early diagnosis and quantitation of the causal pathogen species for accurate and timely disease control is crucial. Botrytis Gray Mold (BGM), caused by Botrytis cinerea and B. fabae, can seriously impact production of temperate grain legumes separately or within a complex. Accordingly, several immunogenic and molecular probe-type protocols have been developed for their diagnosis, but these have varying levels of species-specificity, sensitivity and consequent usefulness within the paddock. To substantially improve speed, accuracy and sensitivity, advanced nanoparticle-based biosensor approaches have been developed. These novel methods have made enormous impact toward disease diagnosis in the medical sciences and offer potential for transformational change within the field of plant pathology and disease management, with early and accurate diagnosis at the point-of-care in the field. Here we review several recently developed diagnostic tools that build on traditional approaches and are available for pathogen diagnosis, specifically for Botrytis spp. diagnostic applications. We then identify the specific gaps in knowledge and current limitations to these existing tools.

Quantification of Botrytis cinerea in Grapevine Bunch Trash by Real-Time PCR

Quantification of colonization of grape bunch trash by Botrytis cinerea is crucial for Botrytis bunch rot (BBR) control. A previously developed quantitative polymerase chain reaction (qPCR) method was adapted to quantify B. cinerea DNA in grape bunch trash, and a colonization coefficient (CC) was calculated as the ratio between the DNA concentrations of B. cinerea and of Vitis vinifera. CC values increased linearly with the number of conidia of B. cinerea or the quantity of mycelium of B. cinerea added to the bunch trash increased. CC values also increased linearly in bunch trash samples containing increasing percentages of B. cinerea-colonized bunch trash; in the latter samples, CC values were correlated with subsequent assessments of B. cinerea colonization of trash (as determined by plating on agar) and sporulation on the trash (as determined by spore counts after incubation in humid chambers). The qPCR assay was also validated using trash collected from bunches treated or not treated with fungicides in three vineyards in two seasons. CC values reflected the reduction in sporulation and in latent infections of mature berries caused by fungicide application. The qPCR assay enables rapid, specific, sensitive, and reliable quantification of the degree of colonization of bunch trash by B. cinerea, which makes it a useful tool for studies of the epidemiology and management of BBR.

A network meta-analysis provides new insight into fungicide scheduling for the control of Botrytis cinerea in vineyards

BACKGROUND

Control of Botrytis bunch rot (BBR) is currently based on the application of fungicides at four timings corresponding to specific growth stages of vines: end of flowering (A), pre-bunch closure (B), veraison (C) and before harvest (D). The current research provides a network meta-analysis of 116 studies conducted between 1963 and 2016 in nine countries, in which 14 strategies (based on combinations of 1, 2, 3, or 4 sprays applied in A, B, C, and/or D) were compared.

RESULTS

When a one-spray strategy was applied, BBR control was more effective with sprays applied in A, C, or D than B. With a two-spray strategy, strategy AC provided similar control as strategy BC; strategy CD also provided good control. For a 3-spray strategy, the best disease control was consistently obtained with strategy ACD. Four-spray strategy ABCD provided the best control but often involved needless sprays so that the routine application of four sprays is not justified.

CONCLUSIONS

Spraying at timing A seems to be very important for achieving efficient and flexible disease control. Flexibility is reduced by spraying at timing B rather than A. © 2018 Society of Chemical Industry.

Automated Analysis of Aggregated Datasets to Identify Climatic Predictors of Botrytis Bunch Rot in Wine Grapes

Botrytis bunch rot (BBR), caused by Botrytis cinerea, results in serious losses to wine-grape production in some seasons during the preharvest period. In order to predict seasons that are at risk from BBR, datasets consisting of 25 disease, weather and vine phenology variables were aggregated from 101 SiteYears across seven regions and nine growing seasons. Automated analyses were used to compare a range of statistical methods for their ability to predict BBR epidemics, including the Kruskal-Wallis test, logistic regression, receiver operating characteristic analysis, and skill-scores. Variables based on relative humidity and surface-wetness duration were significant and consistent predictors of BBR epidemics across the range of analyses applied. Variables integrating temperature and wetness duration, including the Bacchus and Broome models, also demonstrated high predictive ability; however, they did not outperform their constituent components in all analyses. Automation of data analyses was an effective way to compare a wide range of statistical methods and a large number of variables with minimal user input, following initial code development. Significant time was needed to check input data and software code, but a greater return on investment would occur should the analytical process be applied to new datasets, including those from other pathosystems.

Microbial Antagonism Toward Botrytis Bunch Rot of Grapes in Multiple Field Tests Using One Bacillus ginsengihumi Strain and Formulated Biological Control Products

Botrytis bunch rot (BBR), caused by the necrotrophic fungus Botrytis cinerea, is a major disease of wine and table grapes worldwide. Due to negative effects of pesticides on the environment and human health, alternative control strategies against BBR, such as biological control agents (BCAs), are required to produce high-quality grapes and wines with high standards of food safety. However, few biological control products against BBR are available, and their efficacy is sometimes variable. This study aimed to evaluate and compare (1) the efficacy of new bacterial BCA strains developed at INRA Bordeaux and (2) the BBR reductions achieved by commercial biocontrol products that are already registered or close to being registered. During three consecutive seasons, 10 field experiments were established in six different experimental vineyards in southwestern France. Spray applications were performed at key phenological stages (five or six during the season), or at high BBR-risk periods late in the season according to a Disease Risk Index model. At harvest, BBR incidence and severity (% of symptomatic berries per bunch) were visually determined. The experiments included four bacterial strains at an early experimental stage, particularly Bacillus ginsengihumi (S38). Nine commercial BCA products were also tested, including Bacillus subtilis, Bacillus amyloliquefaciens, Aureobasidium pullulans, Ulocladium oudemansii, and Candida sake. Among the four experimental bacterial strains, only B. ginsengihumi S38 significantly controlled the BBR, presenting reductions in the average severity ranging from 35 to 60%, compared to untreated control, throughout the three seasons. Several commercial BCAs achieved significant reductions in BBR severity ranging from 21 to 58%, although not in every trial. The treatments that achieved higher reductions in severity rates were based on C. sake (45%), B. subtilis (54%), and B. amyloliquefaciens (58%). The efficacy of those BCAs was consistent throughout the studied seasons. The results confirmed the suitability of several biological control products under the conditions in vineyards in southwestern France, while also highlighting the good performance of the novel experimental BCA B. ginsengihumi S38 strain, which achieved similar control rates to the products registered for commercial use. The major factors involved in the variability in the results are also discussed.

Comparison of Three Modelling Approaches for Predicting Deoxynivalenol Contamination in Winter Wheat

Forecasting models for mycotoxins in cereal grains during cultivation are useful for pre-harvest and post-harvest mycotoxin management. Some of such models for deoxynivalenol (DON) in wheat, using two different modelling techniques, have been published. This study aimed to compare and cross-validate three different modelling approaches for predicting DON in winter wheat using data from the Netherlands as a case study. To this end, a published empirical model was updated with a new mixed effect logistic regression method. A mechanistic model for wheat in Italy was adapted to the Dutch situation. A new Bayesian network model was developed to predict DON in wheat. In developing the three models, the same dataset was used, including agronomic and weather data, as well as DON concentrations of individual samples in the Netherlands over the years 2001–2013 (625 records). Similar data from 2015 and 2016 (86 records) were used for external independent validation. The results showed that all three modelling approaches provided good accuracy in predicting DON in wheat in the Netherlands. The empirical model showed the highest accuracy (88%). However, this model is highly location and data-dependent, and can only be run if all of the input data are available. The mechanistic model provided 80% accuracy. This model is easier to implement in new areas given similar mycotoxin-producing fungal populations. The Bayesian network model provided 86% accuracy. Compared with the other two models, this model is easier to implement when input data are incomplete. In future research, the three modelling approaches could be integrated to even better support decision-making in mycotoxin management.

Association Between Weather Variables, Airborne Inoculum Concentration, and Raspberry Fruit Rot Caused by Botrytis cinerea

Botrytis fruit rot (BFR), one of the most important diseases of raspberry (Rubus spp.), is controlled primarily with fungicides. Despite the use of fungicides, crop losses due to BFR are high in most years. The aim of this study was to investigate the association between airborne inoculum, weather variables, and BFR in order to improve the management of the disease as well as harvest and storage decisions. Crop losses, measured as the percentage of diseased berries during the harvest period, were monitored in unsprayed field plots at four sites in three successive years, together with meteorological data and the number of conidia in the air. Based on windowpane analysis, there was no evidence of correlation between crop losses and temperature, vapor pressure deficit, wind, solar radiation, or probability of infection. There were significant correlations between crop losses and airborne inoculum and between crop losses and humidity-related variables, and the best window length was identified as 7 days. Using 7-day average airborne inoculum concentration combined with 7-day average relative humidity for periods ending 6 to 8 days before bloom, it was possible to accurately predict crop losses (R² of 0.86 to 0.89). These models could be used to assist with managing BFR, timing harvests, and optimizing storage duration in raspberry crops.

Accurate prediction of black rot epidemics in vineyards using a weather-driven disease model

BACKGROUND

Grapevine black rot caused by Guignardia bidwellii is a serious threat in vineyards, especially in areas with cool and humid springs. A mechanistic, weather-driven model was recently developed for the detailed prediction of black rot epidemics. The aim of this work was to evaluate the model by comparison with observed disease development in leaves and clusters in a vineyard in north Italy from 2013 to 2015.

RESULTS

The model accurately predicted disease onset. The probability of predicting new infections that did not occur (i.e. unjustified alarms) was ≤0.180, while the probability of missing actual infections was 0.175 for leaves and 0.263 for clusters. In 78% of these false negative predictions, the difference between expected and actual disease onset was ±2 days; therefore, only one infection period was actually missed by the model. The model slightly overestimated disease severity (mainly on leaves) when the observed disease severity was >0.6.

CONCLUSION

The model was highly accurate and robust in predicting the infection periods and dynamics of black rot epidemics. The model can be used for scheduling fungicide sprays in vineyards. © 2016 Society of Chemical Industry.