A process-based model to simulate sugarcane orange rust severity from weather data in Southern Brazil

Valeriano, Taynara Tuany Borges; Rolim, Glauco de Souza; Manici, L.; Giustarini, Laura; Bregaglio, Simone

doi:10.1007/s00484-021-02162-5

Cited by 5 publications

(4 citation statements)

References 35 publications

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“…The occurrence of orange rust depends on environmental conditions, with greater severity being observed in conditions of high humidity and warm temperatures (Minchio et al, 2017) in adult plants (Garcia et al, 2007;Braithwaite et al, 2009). In susceptible parents, an increase in the disease progress curve was observed at the end of November and greater disease severity from January onwards, corroborating the research by Araújo et al (2013), Chapola et al (2016) and Valeriano et al (2021).…”

Section: Discussionsupporting

confidence: 72%

Research Article Resistance to orange rust associated with the G1 molecular marker in parents of Brazilian RB sugarcane varieties

Borella¹,

Brasileiro²,

Azeredo³

et al. 2022

Genet. Mol. Res.

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RB867515 (resistant to orange rust). Of the 63 sugarcane parents, 43 were classified as resistant, of which 27 were positive for the G1 marker; 10 as intermediate, including seven positives for G1; 10 were susceptible, among which four were positive for this marker. The molecular marker G1 showed an accuracy of 71% in predicting the resistant phenotype and could be used as a tool for the characterization of resistant germplasm.

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Section: Discussionsupporting

confidence: 72%

Research Article Resistance to orange rust associated with the G1 molecular marker in parents of Brazilian RB sugarcane varieties

Borella¹,

Brasileiro²,

Azeredo³

et al. 2022

Genet. Mol. Res.

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“…The rotten model was developed as a BioMA component in Microsoft C#, following the guidelines of the Diseases components ( Bregaglio and Donatelli, 2015 ; Valeriano et al, 2021 ; Wang et al, 2021 ).…”

Section: Methodsmentioning

confidence: 99%

“…Process-based simulation models are needed to extrapolate the experimental results from one site to another, thus enabling the development of early warning systems, to either optimize the chemical control of plant diseases or perform scenario analyses on pathogen suitability over large areas ( Gillespie and Sentelhas, 2008 ). In addition, plant disease models are increasingly requested by private and public stakeholders to timely identify critical situations and quantify the expected impacts on yield and quality ( Bregaglio et al, 2016 ; Valeriano et al, 2021 ). With these premises, we developed a new simulation model to predict the incidence of the rotten defect on hazelnuts.…”

Section: Introductionmentioning

confidence: 99%

Rotten Hazelnuts Prediction via Simulation Modeling—A Case Study on the Turkish Hazelnut Sector

Valeriano¹,

Fischer²,

Ginaldi³

et al. 2022

Front. Plant Sci.

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The quality defects of hazelnut fruits comprise changes in morphology and taste, and their intensity mainly depends on seasonal environmental conditions. The strongest off-flavor of hazelnuts is known as rotten defect, whose candidate causal agents are a complex of fungal pathogens, with Diaporthe as the dominant genus. Timely indications on the expected incidence of rotten defect would be essential for buyers to identify areas where hazelnut quality will be superior, other than being useful for farmers to have the timely indications of the risk of pathogens infection. Here, we propose a rotten defect forecasting model, and we apply it in the seven main hazelnut producing municipalities in Turkey. We modulate plant susceptibility to fungal infection according to simulated hazelnut phenology, and we reproduce the key components of the Diaporthe spp. epidemiological cycle via a process-based simulation model. A model sensitivity analysis has been performed under contrasting weather conditions to select most relevant parameters for calibration, which relied on weekly phenological observations and the post-harvest analyses of rotten incidence in the period 2016–2019, conducted in 22 orchards. The rotten simulation model reproduced rotten incidence data in calibration and validation datasets with a mean absolute error below 1.8%. The dataset used for model validation (321 additional sampling locations) has been characterized by large variability of rotten incidence, in turn contributing to decrease the correlation between reference and simulated data (R2 = 0.4 and 0.21 in West and East Black Sea region, respectively). This denotes the key effect of other environmental and agronomic factors on rotten incidence, which are not yet taken into account by the predictive workflow and will be considered in further improvements. When applied in spatially distributed simulations, the model differentiated the rotten incidence across municipalities, and reproduced the interannual variability of rotten incidence. Our results confirmed that the rotten defect is strictly dependent on precipitation amount and timing, and that plant susceptibility is crucial to trigger fungal infections. Future steps will envisage the application of the rotten simulation model to other hazelnut producing regions, before being operationally used for in-season forecasting activities.

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“…It also highlights the generic value of many weather-based models designed to predict progress of plant diseases solely with a key thermal predictor and a moisture duration requirement, regardless of the complexity of the relationship between the pathogen, the host, and the environment (Magarey et al 2005;Bregaglio et al 2013;Launay et al 2014;El Jarroudhi et al 2017). In Brazil, agro-climatic favorability zones for sugarcane orange rust at large production scales were mapped using predictive models based on long-term weather records (Sentelhas et al 2016;Valeriano et al 2021). These models could also be investigated to map disease risk zones for the local sugarcane industry which is characterized by extremely diverse climatic production areas (Dumont et al 2022).…”

Section: Differences In Mean Severity Levels Between Locationsmentioning

confidence: 99%

Effects of orange rust on sugarcane yield traits in a multi-environment breeding program

Dijoux

Dumont²,

Paysan³

et al. 2023

Euphytica

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Orange rust caused by Puccinia kuehnii is a major emerging disease in many sugarcane-producing countries. Breeding for resistant varieties is the main strategy for controlling orange rust. The rapid spread of this disease in recently contaminated sugarcane industries offers the opportunity to use on-going breeding trials to investigate the effect of orange rust on yield traits and gauge levels of resistance required to minimize losses. Orange rust was first observed in 2018 in Reunion. This study reports the effects of the disease on cane yield (CY), recoverable sugar (RS), fiber content (FIB) and economic index (EI) in five environments of Reunion’s sugarcane breeding program located in diverse agro-climatic zones. Disease resistance assessed under natural infection had high broad-sense heritability (0.76–0.91) in multi-environment analyses. Mean infection levels differed between locations congruently with location differences for two influential climatic parameters (humidity and temperature). Maximum potential yield losses ($${YL}_{max}$$ YL max ) associated with orange rust were estimated using regression analyses of yield traits versus disease susceptibility. $${YL}_{max}$$ YL max for CY and EI varied between environments and reached up to 26.0% and 24.2% respectively, in one of the most humid environments. RS was either unaffected or only slightly increased by the disease. In contrast, FIB was always reduced by the disease ($${YL}_{max}$$ YL max ≤6.5%). Multi-environment analyses of yield traits of varieties common to all five environments gave insights into the impact of orange rust on the yielding ability of these varieties across all environments. All these data provide food for thoughts to efficient breeding strategies for varietal resistance to orange rust.

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A process-based model to simulate sugarcane orange rust severity from weather data in Southern Brazil

Cited by 5 publications

References 35 publications

Research Article Resistance to orange rust associated with the G1 molecular marker in parents of Brazilian RB sugarcane varieties

Research Article Resistance to orange rust associated with the G1 molecular marker in parents of Brazilian RB sugarcane varieties

Rotten Hazelnuts Prediction via Simulation Modeling—A Case Study on the Turkish Hazelnut Sector

Effects of orange rust on sugarcane yield traits in a multi-environment breeding program

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