Evidence map›Paper›PMID 39397987›Full record

ArticleHeliyon2024

Evaluation of unmanned aerial vehicle for effective spraying application in coconut plantations.

R Pandiselvam, Daliyamol, Syed Imran S, Vinayaka Hegde, M Sujithra, P S Prathibha, V H Prathibha, K B Hebbar

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

R PandiselvamPhysiology, Biochemistry and Post-Harvest Technology Division, ICAR -Central Plantation Crops Research Institute, Kasaragod, 671 124, Kerala, India.
DaliyamolCrop Protection Division, ICAR -Central Plantation Crops Research Institute, Kasaragod, 671 124, Kerala, India.
Syed Imran SICAR - Central Institute of Agricultural Engineering, Regional Station, Coimbatore, 641 008, Tamil Nadu, India.
Vinayaka HegdeCrop Protection Division, ICAR -Central Plantation Crops Research Institute, Kasaragod, 671 124, Kerala, India.
M SujithraCrop Protection Division, ICAR -Central Plantation Crops Research Institute, Kasaragod, 671 124, Kerala, India.
P S PrathibhaCrop Protection Division, ICAR -Central Plantation Crops Research Institute, Kasaragod, 671 124, Kerala, India.
V H PrathibhaCrop Protection Division, ICAR -Central Plantation Crops Research Institute, Kasaragod, 671 124, Kerala, India.
K B HebbarPhysiology, Biochemistry and Post-Harvest Technology Division, ICAR -Central Plantation Crops Research Institute, Kasaragod, 671 124, Kerala, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unmanned aerial vehicle (UAV) pesticide application in recent years owing to its importance such as time saving, reduction in human drudgery and also reduction in pesticides application rate. UAV has a great potential to address the problem involved in manual chemicals spraying in tall crops like coconut plantation where at present operation performed by manual climbing involves lots of drudgery and life risk. The current study aimed to understand the most influencing spraying parameters, such as spray height and spray time of the UAV sprayer on droplet characteristics such as spray droplet size, spray coverage and spray deposition at different layers (spindle, middle and bottom) of coconut tree canopy. The selected spray height (1, 2 and 3 m) and spray time (5, 8 and 11 s) significantly affects (

Indexed as

Aerial sprayCoconut treePesticide applicatorSpray characteristicsTall cropsUAV

Identifiers

PMID39397987
PMCPMC11470614

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.