Sensor-Based Quantification of Peanut Disease Defoliation Using an Unmanned Aircraft System and Multispectral Imagery.

Early leaf spot (Passalora arachidicola) and late leaf spot (Nothopassalora personata) are two of the most economically important foliar fungal diseases of peanut, often requiring seven to eight fungicide applications to protect against defoliation and yield loss. Rust (Puccinia arachidis) may also cause significant defoliation depending on season and location. Sensor technologies are increasingly being utilized to objectively monitor plant disease epidemics for research and supporting integrated management decisions. This study aimed to develop an algorithm to quantify peanut disease defoliation using multispectral imagery captured by an unmanned aircraft system. The algorithm combined the Green Normalized Difference Vegetation Index and the Modified Soil-Adjusted Vegetation Index and included calibration to site-specific peak canopy growth. Beta regression was used to train a model for percent net defoliation with observed visual estimations of the variety 'GA-06G' (0 to 95%) as the target and imagery as the predictor (train: pseudo-R2 = 0.71, test k-fold cross-validation: R2 = 0.84 and RMSE = 4.0%). The model performed well on new data from two field trials not included in model training that compared 25 (R2 = 0.79, RMSE = 3.7%) and seven (R2 = 0.87, RMSE = 9.4%) fungicide programs. This objective method of assessing mid-to-late season disease severity can be used to assist growers with harvest decisions and researchers with reproducible assessment of field experiments. This model will be integrated into future work with proximal ground sensors for pathogen identification and early season disease detection.[Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Comparative Transcriptome Analysis Identified Candidate Genes for Late Leaf Spot Resistance and Cause of Defoliation in Groundnut.

Late leaf spot (LLS) caused by fungus Nothopassalora personata in groundnut is responsible for up to 50% yield loss. To dissect the complex nature of LLS resistance, comparative transcriptome analysis was performed using resistant (GPBD 4), susceptible (TAG 24) and a resistant introgression line (ICGV 13208) and identified a total of 12,164 and 9954 DEGs (differentially expressed genes) respectively in A- and B-subgenomes of tetraploid groundnut. There were 135 and 136 unique pathways triggered in A- and B-subgenomes, respectively, upon N. personata infection. Highly upregulated putative disease resistance genes, an RPP-13 like (Aradu.P20JR) and a NBS-LRR (Aradu.Z87JB) were identified on chromosome A02 and A03, respectively, for LLS resistance. Mildew resistance Locus (MLOs)-like proteins, heavy metal transport proteins, and ubiquitin protein ligase showed trend of upregulation in susceptible genotypes, while tetratricopeptide repeats (TPR), pentatricopeptide repeat (PPR), chitinases, glutathione S-transferases, purple acid phosphatases showed upregulation in resistant genotypes. However, the highly expressed ethylene responsive factor (ERF) and ethylene responsive nuclear protein (ERF2), and early responsive dehydration gene (ERD) might be related to the possible causes of defoliation in susceptible genotypes. The identified disease resistance genes can be deployed in genomics-assisted breeding for development of LLS resistant cultivars to reduce the yield loss in groundnut.

Sixty-One Years Following Registration, Phorate Applied In-Furrow at Planting Suppresses Development of Late Leaf Spot on Peanut.

Late and early leaf spot are caused by Nothopassalora personata and Passalora arachidicola, respectively, and are damaging diseases of peanut (Arachis hypogaea L.) capable of defoliation and yield loss. Management of these diseases is most effective through the integration of tactics that reduce starting inoculum and prevent infection. The insecticide phorate was first registered in 1959 and has been used in peanut production for decades in-furrow at planting to suppress thrips. Phorate further provides significant suppression of Tomato spotted wilt virus infection beyond suppression of its thrips vector alone by activating defense-related responses in the peanut plant. From six experiments conducted from 2017 to 2019 in Blackville, SC, Reddick, FL, and Quincy, FL, significantly less leaf spot defoliation was exhibited on peanuts treated with phorate in-furrow at planting (26%) compared with nontreated checks (48%). In-season fungicides were excluded from five of the experiments, whereas the 2018 Quincy, FL, experiment included eight applications on a 15-day interval. Across individual experiments, significant suppression of defoliation caused by late leaf spot was observed from 64 to 147 days after planting. Although more variable within location-years, pod yield following phorate treatment was overall significantly greater than for nontreated peanut (2,330 compared with 2,030 kg/ha; P = 0.0794). The consistent defoliation suppression potential was estimated to confer an average potential net economic yield savings of $90 to $120 per hectare under analogous leaf spot defoliation. To our knowledge, these are the first data in the 61 years since its registration demonstrating significant suppression of leaf spot on peanut following application of phorate in-furrow at planting. Results support phorate use in peanut as an effective and economical tactic to incorporate to manage late and early leaf spot infections and development of fungicide resistance.

Relating Peanut Rx Risk Factors to Epidemics of Early and Late Leaf Spot of Peanut.

Previous research has demonstrated the efficacy of prescription fungicide programs, based upon Peanut Rx, to reduce combined effects of early leaf spot (ELS), caused by Passalora arachidicola (Cercospora arachidicola), and late leaf spot (LLS), caused by Nothopassalora personata (syn. Cercosporidium personatum), but the potential of Peanut Rx to predict each disease has never been formally evaluated. From 2010 to 2016, non-fungicide-treated peanut plots in Georgia and Florida were sampled to monitor the development of ELS and LLS. This resulted in 168 cases (unique combinations of Peanut Rx risk factors) with associated total leaf spot risk points ranging from 40 to 100. Defoliation ranged from 13.9 to 100%, and increased significantly with increasing total risk points (conditional R2 = 0.56; P < 0.001). Leaf spot onset (time in days after planting [DAP] when either leaf spot reached 1% lesion incidence), ELS onset, and LLS onset ranged from 29 to 140, 29 to 142, and 50 to 143 DAP, respectively, and decreased significantly with increasing risk points. Standardized AUDPC of ELS was significantly affected by risk points (conditional R2 = 0.53, P < 0.001), but not for LLS. After removing redundant Peanut Rx factors, planting date, rotation, historical leaf spot prevalence, cultivar, and field history were used as fixed effects in mixed effect regression models to evaluate their contribution to leaf spot, ELS or LLS prediction. Results from mixed effects regression confirmed that the selected Peanut Rx risk factors contributed to the variability of at least one measurement of development of combined or separate epidemics of ELS and LLS, but not all factors affected ELS and LLS equally. Historical leaf spot prevalence, a new potential preplant risk factor, was a consistent predictor of the dominant disease(s) observed in the field. Results presented here demonstrate that Peanut Rx is a very effective tool for predicting leaf spot onset regardless of which leaf spot is predominant, but also suggest that associated risk does not reflect the same development for each disease. These data will be useful for refining thresholds for differentiating high, moderate, and low risk fields, and reevaluating the timing of fungicide applications in reduced input programs with respect to disease onset.

Mycosphaerellaceae - Chaos or clarity?

The Mycosphaerellaceae represent thousands of fungal species that are associated with diseases on a wide range of plant hosts. Understanding and stabilising the taxonomy of genera and species of Mycosphaerellaceae is therefore of the utmost importance given their impact on agriculture, horticulture and forestry. Based on previous molecular studies, several phylogenetic and morphologically distinct genera within the Mycosphaerellaceae have been delimited. In this study a multigene phylogenetic analysis (LSU, ITS and rpb2) was performed based on 415 isolates representing 297 taxa and incorporating ex-type strains where available. The main aim of this study was to resolve the phylogenetic relationships among the genera currently recognised within the family, and to clarify the position of the cercosporoid fungi among them. Based on these results many well-known genera are shown to be paraphyletic, with several synapomorphic characters that have evolved more than once within the family. As a consequence, several old generic names including Cercosporidium, Fulvia, Mycovellosiella, Phaeoramularia and Raghnildiana are resurrected, and 32 additional genera are described as new. Based on phylogenetic data 120 genera are now accepted within the family, but many currently accepted cercosporoid genera still remain unresolved pending fresh collections and DNA data. The present study provides a phylogenetic framework for future taxonomic work within the Mycosphaerellaceae.