Sclerotinia sclerotiorum is a predominant plant pathogen, with host crops of agricultural and economic importance internationally. South African host crops of importance include canola, soybean and sunflower, which contribute significantly to the South African economy. This significance emphasises the importance of effective disease management strategies, including rotation with non-host crops, planting cultivars with a degree of tolerance, and using relevant cultural and chemical practices. The sporadic nature of disease outbreaks caused by Sclerotinia spp. can complicate fungicide application timing as a result of the pathogen’s interaction with the host and environment. The use of prediction modelling for diseases caused by Sclerotinia spp. can contribute to increased fungicide application efficacy and a reduction in the number of unnecessary sprays. Predictive modelling is based upon the collection and statistical analysis of multi-locality and multi-seasonal, pathogen, disease and weather data. Incorporating the complexity of disease initiation and development into such models is dependent on selecting the correct statistical tools to interpret appropriate data, which can be used to develop a model that is accurate, precise and reliable. Internationally, forecasting models for diseases caused by Sclerotinia spp. exist and are applied commercially for multiple Sclerotinia spp. on important agricultural crops. The application of these models in a South African context has been limited but provides promise for effective disease intervention technologies. This review provides a platform to raise awareness of the potential applications of plant disease epidemiology and the use of statistics and mathematical modelling in agricultural systems. Plant disease forecasts are an important part of the future for sustainable and economically viable agronomic decisions.

Huanglongbing (HLB) is one of the most important diseases affecting citriculture in the world. Knowledge of climatic factors linked to HLB risk at large spatial scales is limited. We gathered HLB presence/absence data from official surveys conducted in the state of Minas Gerais, Brazil, over 13 years. The total count of orange and mandarin orchards, and mean orchard area, normalized to a spatial grid of 60 cells (55 × 55 km), were derived from the same database. Monthly climate normals (1984 to 2013) of rainfall, mean temperature, and wind speed split into rainy (September to April) and dry (May to August) seasons (annual summary was retained) were obtained for each grid cell. Two hierarchical Bayesian modeling approaches were evaluated both based on the integrated nested Laplace approximation methodology. The first, the climate covariates model (CC model), used orchard, climate, and the spatial effect as covariates. The second, principal components (PC model), used the first three components from a principal component analysis of all variables and the spatial effect as covariates. Both models showed an inverse relationship between posterior prevalence and grid cell mean temperature during the dry season. Annual wind speed, as well as annual and rainy season rainfall, contributed to HLB risk, in the CC and PC models, respectively. A partial influence of neighboring regions on HLB risk was observed. The results should assist policymakers in defining regions at HLB risk and guide monitoring strategies to mitigate further spread of HLB in the state of Minas Gerais.

Fig rust, caused by Cerotelium fici, was first recorded in South Africa in 1927. Recent observations have revealed high incidence of rust and untimely defoliation of fig trees (Ficus carica) in residential gardens and commercial orchards. Using phylogenetic analysis, the causal organism of a fig rust isolate (PREM63073) collected in 2020 was confirmed as Phakopsora nishidana. Inoculation and microscope studies showed that mulberry plants were immune to P. nishidana isolate PREM63073. Infection of fig leaves occurred through stomata on the abaxial leaf surfaces. Very long germ tubes were observed for P. nishidana, often with no clear contact with the leaf surfaces and an apparent lack of directional growth towards stomata. Inoculated plants from 15 fig cultivars varied in their severity of leaf infection, whereas fruit of the cultivar Kadota developed reddish-brown blemishes without sporulation. Currently, C. fici and P. nishidana are recognised as occurring on F. carica in South Africa. This suggests a need to resolve the worldwide distribution and identity of the rust species involved.

Depending on the pathogenicity of the stripe rust fungus Puccinia striiformis f. sp. tritici, the nature of resistance in the wheat host plant, and the environment, a broad range of disease phenotypes can be expressed. Therefore, the phenotyping of partial adult plant stripe rust resistance requires reliable and repeatable procedures, especially under controlled conditions. In this study, the development of a flag leaf point inoculation method, which resulted in a 100% initial infection rate, is reported. Flag leaf inoculations were achieved by placing 6-mm antibiotic test paper discs, dipped into a urediniospore and water suspension and covered with water-proof plastic tape, on the adaxial side of leaves. Results from independent trials allowed for the statistical comparison of stripe rust lesion expansion rate in wheat entries that differ in resistance. The technique is inexpensive, reliable, and applicable to routine screening for adult plant response type, quantitative comparison of stripe rust progress, environmental influences, and pathogenicity of different isolates.

The increasing growth of agroindustrial activity resulting in excessive amounts of agriwaste has led to the accumulation of a large quantity of lignocellulosic residues all over the world, in particular in deforestation initiatives for the removal of invasive trees in South Africa. These lignocellulosic residues are rich in energy resources and consist of a mixture of natural polymers based on lignin, cellulose, and hemicellulose. The use of lignolytic fungi such as mushrooms in solid‐state fermentation could sufficiently degrade the indigestible lignocellulosic components and add medicinal and nutritional value to otherwise unusable, high‐energy waste material, which in turn could yield a new method of producing energy‐rich fodder for ruminant animals. The digestive type of animal for which the potential feed is developed must be identified and considered before deciding on the bioconversion method and process, as the outcomes for obtaining potentially high‐quality feeds for nonruminant and ruminant animals are different. The current study presents data on the bioconversion of lignocellulosic substrate using solid‐state fermentation with edible and medicinal mushrooms, Ganoderma lucidumand Pleurotus ostreatus, and a possible new species, to increase digestibility and nutritional value to be applied as ruminant animal feed. The solid‐state fermentation process was optimized and the resulting product was analyzed for the degradation of the lignocellulosic components. Results indicated that the solid‐state fermentation duration and mushroom species were key components in achieving significant degradation. Data obtained after 18 weeks of degradation indicated a significant (p < 0.05) reduction in the acid detergent fiber, acid detergent lignin, and neutral detergent fiber fractions of the biomass, with up to a 20% reduction in indigestible components. This increase in digestibility could contribute to increased energy availability for ruminant animals.