Potential of the Dithiocarbimate Fungicides on the Control of Coffee Leaf Rust and Asian Soybean Rust
Bibliographic record
Abstract
Coffee leaf rust (Hemileia vastatrix) and Asian soybean rust (Phakopsora pachyrhizi) are diseases that cause great losses in the productivity of these crops, not only in Brazil but on a global scale. Coffee and soybean varieties grown are susceptible to these diseases. Thus, it is necessary to search for efficient compounds for their chemical control, mainly from the group of protectors or residuals so that they can be formulated with systemic fungicides to control the diseases. This allows not only the efficient management of diseases but also the prevention of the emergence of resistant mutants in the populations of these pathogens. In this context, the present study aimed to evaluate the sensitivity and effect of bis(N-R-sulfonyldithiocarbimato)zincate(II) salts fungicides on the epidemiological components of pathosystems coffee × H. vastatrix and soybean × P. pachyrhizi. Initially, four zinc(II) complexes salts (1A, 2A, 1B, and 2B) with N-R-sulfonyldithiocarbimates were synthesized. In the first experiment, the in vitro sensitivity of H. vastatrix and P. pachyrhizi was studied for the four compounds synthesized and mancozeb at 0.5, 5.0, 50.0, 100.0 and 200.0 µmol L-1. All the compounds synthetized in this study had inhibitory effects on H. vastatrix and P. pachyrhizi. In the greenhouse it was studied the effect of bis(N-R-sulfonyldithiocarbimato)zincate(II) salts on the epidemiological components of coffee leaf rust and Asian soybean rust. For the pathosystem coffee × H. vastatrix, there were no differences in the values obtained for the bis(N-R-sulfonyldithiocarbimato)zincate(II) salts and mancozeb for the latent period. For the sporulated lesion variable, the control treatment had a mean value of 149.0 lesions/leaf, differing significantly from the other treatments. The mean value of compound 2B was estimated as 25.0 lesions/leaf, differing significantly from treatments 1A, 1B, 2B, and mancozeb. Treatments 1A, 1B, 2B, and mancozeb did not differ significantly from each other. For the Asian soybean rust, the area under the disease progress curve had a mean value of 75.8 for the control, while for the 2A treatment the value was 4.1, differing from the other compounds. The treatments 1A, 1B, 2A, and mancozeb did not differ significantly from each other. In conclusion, compounds 1A, 2A, and 1B were more efficient in the control of the coffee leaf rust, while compound 2A was efficient in the control of the Asian soybean rust.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".