{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T02:08:57Z","timestamp":1769998137943,"version":"3.49.0"},"reference-count":30,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2019,1,17]],"date-time":"2019-01-17T00:00:00Z","timestamp":1547683200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100013276","name":"Interreg","doi-asserted-by":"publisher","award":["143081"],"award-info":[{"award-number":["143081"]}],"id":[{"id":"10.13039\/100013276","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The right moment to harvest apples in fruit orchards is still decided after persistent monitoring of the fruit orchards via local inspection and using manual instrumentation. However, this task is tedious, time consuming, and requires costly human effort because of the manual work that is necessary to sample large orchard parcels. The sensor miniaturization and the advances in gas detection technology have increased the usage of gas sensors and detectors in many industrial applications. This work explores the combination of small-sized sensors under Unmanned Aerial Vehicles (UAV) to understand its suitability for ethylene sensing in an apple orchard. To accomplish this goal, a simulated environment built from field data was used to understand the spatial distribution of ethylene when subject to the orchard environment and the wind of the UAV rotors. The simulation results indicate the main driving variables of the ethylene emission. Additionally, preliminary field tests are also reported. It was demonstrated that the minimum sensing wind speed cut-off is 2 ms\u22121 and that a small commercial UAV (like Phantom 3 Professional) can sense volatile ethylene at less than six meters from the ground with a detection probability of a maximum of     10 %    . This work is a step forward in the usage of aerial remote sensing technology to detect the optimal harvest time.<\/jats:p>","DOI":"10.3390\/s19020372","type":"journal-article","created":{"date-parts":[[2019,1,17]],"date-time":"2019-01-17T11:30:27Z","timestamp":1547724627000},"page":"372","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":41,"title":["A Comprehensive Study of the Potential Application of Flying Ethylene-Sensitive Sensors for Ripeness Detection in Apple Orchards"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6241-4124","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Valente","sequence":"first","affiliation":[{"name":"Laboratory of Geo-information Science and Remote Sensing, Wageningen University &amp; Research, 6708 PB Wageningen, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rodrigo","family":"Almeida","sequence":"additional","affiliation":[{"name":"Laboratory of Geo-information Science and Remote Sensing, Wageningen University &amp; Research, 6708 PB Wageningen, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5549-5993","authenticated-orcid":false,"given":"Lammert","family":"Kooistra","sequence":"additional","affiliation":[{"name":"Laboratory of Geo-information Science and Remote Sensing, Wageningen University &amp; Research, 6708 PB Wageningen, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,1,17]]},"reference":[{"key":"ref_1","unstructured":"Alexandratos, N., and Bruinsma, J. 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