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Precision Sprayer Technologies for E...

Rayamajhi, Aleena,

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Precision Sprayer Technologies for Enhanced Ornamental Crop Management /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Precision Sprayer Technologies for Enhanced Ornamental Crop Management // Aleena Rayamajhi.
Author:	Rayamajhi, Aleena,
Description:	1 electronic resource (180 pages)
Notes:	Source: Masters Abstracts International, Volume: 86-07.
Contained By:	Masters Abstracts International86-07.
Subject:	Agricultural engineering. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31633772
ISBN:	9798302135506

Precision Sprayer Technologies for Enhanced Ornamental Crop Management /
Rayamajhi, Aleena,

Precision Sprayer Technologies for Enhanced Ornamental Crop Management /Aleena Rayamajhi. - 1 electronic resource (180 pages)

Source: Masters Abstracts International, Volume: 86-07.

Woody ornamentals are essential to landscapes, yet technological advancements in their cultivation often lag behind other agricultural sectors. Traditional spraying methods for ornamental crops can lead to over or under-application of agrochemicals, posing health, environmental, and economic risks. This research aimed to improve precision spraying through advanced technologies, for reducing agrochemical usage while optimizing management practices. This study utilized a high-resolution RGB camera-mounted aerial system and a ground-based LiDAR and depth camera systems to calculate tree characteristics such as height, trunk diameter, and canopy volume, which are crucial for determining precise agrochemical application rates and enabled a comparison between the two methods for assessing canopy characteristics. Additionally, a web application was developed to monitor disease severity and evaluate the efficacy of agrochemicals to quantify disease progression over time. These technologies help enhance agrochemical application efficacy, promoting sustainability, efficiency, and economic viability in ornamental crop management and spraying.

English

ISBN: 9798302135506Subjects--Topical Terms:

3168406
Agricultural engineering.
Subjects--Index Terms:

Deep learning

Precision Sprayer Technologies for Enhanced Ornamental Crop Management /
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100 1 $a Rayamajhi, Aleena, $e author. $3 3826155
245 1 0 $a Precision Sprayer Technologies for Enhanced Ornamental Crop Management / $c Aleena Rayamajhi.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2024
300 $a 1 electronic resource (180 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 86-07.
500 $a Advisors: Mahmud, Md. Sultan Committee members: Tollner, E. W. Bill; Williams-Woodward, Jean L.; Lu, Guoyu.
502 $b M.S. $c University of Georgia $d 2024.
520 $a Woody ornamentals are essential to landscapes, yet technological advancements in their cultivation often lag behind other agricultural sectors. Traditional spraying methods for ornamental crops can lead to over or under-application of agrochemicals, posing health, environmental, and economic risks. This research aimed to improve precision spraying through advanced technologies, for reducing agrochemical usage while optimizing management practices. This study utilized a high-resolution RGB camera-mounted aerial system and a ground-based LiDAR and depth camera systems to calculate tree characteristics such as height, trunk diameter, and canopy volume, which are crucial for determining precise agrochemical application rates and enabled a comparison between the two methods for assessing canopy characteristics. Additionally, a web application was developed to monitor disease severity and evaluate the efficacy of agrochemicals to quantify disease progression over time. These technologies help enhance agrochemical application efficacy, promoting sustainability, efficiency, and economic viability in ornamental crop management and spraying.
546 $a English
590 $a School code: 0077
650 4 $a Agricultural engineering. $3 3168406
650 4 $a Computer engineering. $3 621879
653 $a Deep learning
653 $a Depth camera
653 $a Drone
653 $a Precision spraying
653 $a Woody ornamentals
690 $a 0539
690 $a 0503
690 $a 0464
710 2 $a University of Georgia. $b Agricultural Engineering - MS. $e degree granting institution. $3 3826156
720 1 $a Mahmud, Md. Sultan $e degree supervisor.
773 0 $t Masters Abstracts International $g 86-07.
790 $a 0077
791 $a M.S.
792 $a 2024
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31633772