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.

Development and Validation of a Mechanistic, Weather-Based Model for Predicting Puccinia graminis f. sp. tritici Infections and Stem Rust Progress in Wheat.

Stem rust (or black rust) of wheat, caused by Puccinia graminis f. sp. tritici (Pgt), is a re-emerging, major threat to wheat production worldwide. Here, we retrieved, analyzed, and synthetized the available information about Pgt to develop a mechanistic, weather-driven model for predicting stem rust epidemics caused by uredospores. The ability of the model to predict the first infections in a season was evaluated using field data collected in three wheat-growing areas of Italy (Emilia-Romagna, Apulia, and Sardinia) from 2016 to 2021. The model showed good accuracy, with a posterior probability to correctly predict infections of 0.78 and a probability that there was no infection when not predicted of 0.96. The model's ability to predict disease progress during the growing season was also evaluated by using published data obtained from trials in Minnesota, United States, in 1968, 1978, and 1979, and in Pennsylvania, United States, in 1986. Comparison of observed versus predicted data generated a concordance correlation coefficient of 0.96 and an average distance between real data and the fitted line of 0.09. The model could therefore be considered accurate and reliable for predicting epidemics of wheat stem rust and could be tested for its ability to support risk-based control of the disease.

A Weather-Driven Model for Predicting Infections of Grapevines by Sporangia of Plasmopara viticola.

A mechanistic model was developed to predict secondary infections of Plasmopara viticola and their severity as influenced by environmental conditions; the model incorporates the processes of sporangia production and survival on downy mildew (DM) lesions, dispersal and deposition, and infection. The model was evaluated against observed data (collected in a 3-year vineyard) for its accuracy to predict periods with no sporangia (i.e., for negative prognosis) or with peaks of sporangia, so that growers can identify periods with no/low risk or high risk. The model increased the probability to correctly predict no sporangia [P(P-O-) = 0.67] by two times compared to the prior probability, with fewer than 3% of the total sporangia found in the vineyard being sampled when not predicted by the model. The model also correctly predicted peaks of sporangia, with only 1 of 40 peaks unpredicted. When evaluated for the negative prognosis of infection periods, the model showed a posterior probability for infection not to occur when not predicted P(P-O-) = 0.87 with only 9 of 108 real infections not predicted; these unpredicted infections were mild, accounting for only 4.4% of the total DM lesions observed in the vineyard. In conclusion, the model was able to identify periods in which the DM risk was nil or very low. It may, therefore, help growers avoid fungicide sprays when not needed and lengthen the interval between two sprays, i.e., it will help growers move from calendar-based to risk-based fungicide schedules for the control of P. viticola in vineyards.

Millennials as organizational citizens: Conceptualization and measurement development.

Despite existing scholarly progress in organizational citizenship behavior (OCB), prior research has predominantly investigated OCB using Baby Boomers and Generation Xers. As Millennials who possess different sets of workplace values and beliefs are entering the workforce, there is a need for conceptualizing OCB and developing an OCB scale suitable for Millennials. In this study, we conceptualize OCB in Millennials as voluntary behaviors that promote the prosperity of oneself, coworkers, the organization, and the community. Additionally, we employ exploratory factor analysis and identify a four-factor model of OCB, including empathetic responsiveness, role modeling, professional development, and social responsibility. We then conduct confirmatory factor analysis and construct a 13-item measurement scale for Millennial OCB. Finally, we assess and find evidence for the construct validity of the 13-item measurement scale. We conclude this study with an overview of theoretical and managerial implications.

Components of partial resistance to Plasmopara viticola enable complete phenotypic characterization of grapevine varieties.

Six components of partial resistance (RCs) were studied in 15 grapevine varieties with partial resistance to Plasmopara viticola: (i) infection frequency (IFR, proportion of inoculation sites showing sporulation), (ii) latent period (LP50, degree-days between inoculation and appearance of 50% of the final number of sporulating lesions), (iii) lesion size (LS, area of single lesions in mm2), (iv) production of sporangia (SPOR, number of sporangia produced per lesion, and SPOR', number of sporangia produced per mm2 of lesion), (v) infectious period (IP, number of sporulation events on a lesion), and (vi) infectivity of sporangia (INF, infection efficiency of sporangia produced on resistant varieties). Artificial inoculation monocycle experiments were conducted for a 3-year period on leaves collected at leaf development, flowering, and fruit development. Compared to the susceptible variety 'Merlot', the partially resistant varieties showed reduced IFR, longer LP, smaller LS, fewer SPOR and SPOR', shorter IP, and lower INF. At leaf development, IFR, SPOR, and INF were higher and LP was shorter than at flowering and fruit development. RCs analysis through monocyclic experiments provides reliable assessments of the resistance response of grapevine accessions. The workload required for routine assessment in breeding programs could be reduced by measuring IFR and SPOR, while producing robust results.

Can Spore Sampler Data Be Used to Predict Plasmopara viticola Infection in Vineyards?

Grapevine downy mildew (DM) is caused by the dimorphic oomycete Plasmopara viticola, which incites epidemics through primary and secondary infection cycles that occur throughout the season. The secondary infection cycles are caused by the sporangia produced on DM lesions. The current research examined the relationship between numbers of airborne sporangia and DM development on grape leaves to determine whether spore sampler data can be useful to predict the potential for secondary infections of P. viticola. Three years (2015-2017) of spore sampler data confirmed that sporangia are a common component of the airborne microflora in a DM-infested vineyard and that their numbers depend on weather conditions. For a total of 108 days, leaf samples were collected from the vineyard at 2- to 3-day intervals and incubated under optimal conditions for P. viticola infection. The numbers of airborne sporangia sampled on 1 to 7 days before leaf sampling were significantly correlated with the numbers of DM lesions on the leaves. The best correlation (r=0.59), however, was found for the numbers of viable airborne sporangia (SPV), which were assessed by using equations driven by the vapour pressure deficit. In Bayesian and ROC curve analyses, SPV was found to be a good predictor of P. viticola infection of grape leaves, with AUROC=0.821 and false positive predictions mainly occurring at low SPV. A binary logistic regression showed that a threshold of 2.52 viable sporangia m-3 air day-1 enables a prediction of no infection with a posterior probability of 0.870, which was higher than the prior probability of 0.574. Numbers of viable sporangia in the vineyard air is therefore a useful predictor of infection and especially of no infection. The predictor missed some observed infections, but these infections were not severe (they accounted for only 31 of 374 DM lesions).

A Real-Time PCR Assay for the Quantification of Plasmopara viticola Oospores in Grapevine Leaves.

Grapevine downy mildew caused by Plasmopara viticola is one of the most important diseases in vineyards. Oospores that overwinter in the leaf litter above the soil are the sole source of inoculum for primary infections of P. viticola; in addition to triggering the first infections in the season, the oospores in leaf litter also contribute to disease development during the season. In the current study, a quantitative polymerase chain reaction (qPCR) method that was previously developed to detect P. viticola DNA in fresh grapevine leaves was assessed for its ability to quantify P. viticola oospores in diseased, senescent grapevine leaves. The qPCR assay was specific to P. viticola and sensitive to decreasing amounts of both genomic DNA and numbers of P. viticola oospores used to generate qPCR standard curves. When the qPCR assay was compared to microscope counts of oospores in leaves with different levels of P. viticola infestation, a strong linear relationship (R2 = 0.70) was obtained between the numbers of P. viticola oospores per gram of leaves as determined by qPCR vs. microscopic observation. Unlike microscopic observation, the qPCR assay was able to detect significant differences between leaf samples with a low level of oospore infestation (25% infested leaves and 75% non-infested leaves) vs. samples without infestation, and this ability was not influenced by the weight of the leaf sample. The results indicate that the qPCR method is sensitive and provides reliable estimates of the number of P. viticola oospores in grapevine leaves. Additional research is needed to determine whether the qPCR method is useful for quantifying P. viticola oospores in grapevine leaf litter.

Assessment of Resistance Components for Improved Phenotyping of Grapevine Varieties Resistant to Downy Mildew.

Grapevine varieties showing partial resistance to downy mildew, caused by Plasmopara viticola, are a promising alternative to fungicides for disease control. Resistant varieties are obtained through breeding programs aimed at incorporating Rpv loci controlling the quantitative resistance into genotypes characterized by valuable agronomic and wine quality traits by mean of crossing. Traditional phenotyping methods used in these breeding programs are mostly based on the assessment of the resistance level after artificial inoculation of leaf discs in bioassays, by using the visual score proposed in the 2nd Edition of the International Organization of Vine and Wine (OIV) Descriptor List for Grape Varieties and Vitis species (2009). In this work, the OIV score was compared with an alternative approach, not used for the grapevine-downy mildew pathosystem so far, based on the measurement of components of resistance (RCs); 15 grapevine resistant varieties were used in comparison with the susceptible variety 'Merlot'. OIV scores were significantly correlated with P. viticola infection frequency (IFR), the latent period for the downy mildew (DM) lesions to appear (LP50), and the number of sporangia produced per lesion (SPOR), so that when the OIV score increased (i.e., the resistance level increases), IFR and SPOR decreased, while LP50 increased. The relationship was linear for LP50, monomolecular for IFR and hyperbolic for SPOR. No significant correlation was found between OIV score and DM lesion size, sporangia produced per unit area of lesion, length of infectious period, and infection efficiency of the sporangia produced on DM lesions. The correlation between OIV score and area under the disease progress curve (AUDPC) calculated by using the RCs and a simulation model was significant and fit an inverse exponential function. Based on the results of this study, the measurement of the RCs to P. viticola in grapevine varieties by means of monocyclic, leaf disc bioassays, as well as their incorporation into a model able to simulate their effect on the polycyclic development of DM epidemics in vineyards, represents an improved method for phenotyping resistance level.