The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Efficient Management of Fruit Pests by Pheromone Nanogels
Open accessAbstract
Environment-friendly management of fruit flies involving pheromones is useful in reducing the undesirable pest populations responsible for decreasing the yield and the crop quality. A nanogel has been prepared from a pheromone, methyl eugenol (ME) using a low-molecular mass gelator. This was very stable at open ambient conditions and slowed down the evaporation of pheromone significantly. This enabled its easy handling and transportation without refrigeration, and reduction in the frequency of pheromone recharging in the orchard. Notably the involvement of the nano-gelled pheromone brought about an effective management of Bactrocera dorsalis, a prevalent harmful pest for a number of fruits including guava. Thus a simple, practical and low cost green chemical approach is developed that has a significant potential for crop protection, long lasting residual activity, excellent efficacy and favorable safety profiles. This makes the present invention well-suited for pest management in a variety of crops.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Agricultural sustainability and intensive production practices
Tilman, D., Cassman, K. G., Matson, P. A., Naylor, R., & Polasky, S. (2002) · Nature · doi:10.1038/nature01014 · Cited by 7,957
Cited by
Functional π-Gelators and Their Applications
Babu, S. S., Praveen, V. K., & Ajayaghosh, A. (2014) · Chemical Reviews · doi:10.1021/cr400195e · Cited by 1,725
Nanotechnology in agri-food production: an overview
Sekhon, B. (2014) · Nanotechnology, Science and Applications · doi:10.2147/nsa.s39406 · Cited by 1,073
Nanotechnology in agriculture: Opportunities, toxicological implications, and occupational risks
Iavicoli, I., Leso, V., Beezhold, D. H., & Shvedova, A. A. (2017) · Toxicology and Applied Pharmacology · doi:10.1016/j.taap.2017.05.025 · Cited by 656
Nanoparticles for pest control: current status and future perspectives
Athanassiou, C. G., Kavallieratos, N. G., Benelli, G., Losic, D., Usha Rani, P., & Desneux, N. (2018) · Journal of Pest Science · doi:10.1007/s10340-017-0898-0 · Cited by 454
Datta, S., & Bhattacharya, S. (2015) · Chemical Society Reviews · doi:10.1039/c5cs00093a · Cited by 293
Self-citation
Metadata
- Authors
- Bhagat, D., Samanta, S. K., & Bhattacharya, S.
- Venue
- Scientific Reports
- Published
- 2013-02-18
- Volume
- 3
- Issue
- 1
- Pages
- 1294-1294
- ISSN
- 2045-2322 (ISSN-L)
- OpenAlex
- W2090894779
- Cited by
- 177
- References
- 1
- FWCI
- 9.06
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.