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Rice Crop Counting Using Aerial Imagery and GIS for the Assessment of Soil Health to Increase Crop Yield

Rice is one of the vital foods consumed in most countries throughout the world. To estimate the yield, crop counting is used to indicate improper growth, identification of loam land, and control of weeds. It is becoming necessary to grow crops healthy, precisely, and proficiently as the demand incre...

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Autores principales: Hassan, Syeda Iqra, Alam, Muhammad Mansoor, Zia, Muhammad Yousuf Irfan, Rashid, Muhammad, Illahi, Usman, Su’ud, Mazliham Mohd
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9659203/
https://www.ncbi.nlm.nih.gov/pubmed/36366269
http://dx.doi.org/10.3390/s22218567
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author Hassan, Syeda Iqra
Alam, Muhammad Mansoor
Zia, Muhammad Yousuf Irfan
Rashid, Muhammad
Illahi, Usman
Su’ud, Mazliham Mohd
author_facet Hassan, Syeda Iqra
Alam, Muhammad Mansoor
Zia, Muhammad Yousuf Irfan
Rashid, Muhammad
Illahi, Usman
Su’ud, Mazliham Mohd
author_sort Hassan, Syeda Iqra
collection PubMed
description Rice is one of the vital foods consumed in most countries throughout the world. To estimate the yield, crop counting is used to indicate improper growth, identification of loam land, and control of weeds. It is becoming necessary to grow crops healthy, precisely, and proficiently as the demand increases for food supplies. Traditional counting methods have numerous disadvantages, such as long delay times and high sensitivity, and they are easily disturbed by noise. In this research, the detection and counting of rice plants using an unmanned aerial vehicle (UAV) and aerial images with a geographic information system (GIS) are used. The technique is implemented in the area of forty acres of rice crop in Tando Adam, Sindh, Pakistan. To validate the performance of the proposed system, the obtained results are compared with the standard plant count techniques as well as approved by the agronomist after testing soil and monitoring the rice crop count in each acre of land of rice crops. From the results, it is found that the proposed system is precise and detects rice crops accurately, differentiates from other objects, and estimates the soil health based on plant counting data; however, in the case of clusters, the counting is performed in semi-automated mode.
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spelling pubmed-96592032022-11-15 Rice Crop Counting Using Aerial Imagery and GIS for the Assessment of Soil Health to Increase Crop Yield Hassan, Syeda Iqra Alam, Muhammad Mansoor Zia, Muhammad Yousuf Irfan Rashid, Muhammad Illahi, Usman Su’ud, Mazliham Mohd Sensors (Basel) Article Rice is one of the vital foods consumed in most countries throughout the world. To estimate the yield, crop counting is used to indicate improper growth, identification of loam land, and control of weeds. It is becoming necessary to grow crops healthy, precisely, and proficiently as the demand increases for food supplies. Traditional counting methods have numerous disadvantages, such as long delay times and high sensitivity, and they are easily disturbed by noise. In this research, the detection and counting of rice plants using an unmanned aerial vehicle (UAV) and aerial images with a geographic information system (GIS) are used. The technique is implemented in the area of forty acres of rice crop in Tando Adam, Sindh, Pakistan. To validate the performance of the proposed system, the obtained results are compared with the standard plant count techniques as well as approved by the agronomist after testing soil and monitoring the rice crop count in each acre of land of rice crops. From the results, it is found that the proposed system is precise and detects rice crops accurately, differentiates from other objects, and estimates the soil health based on plant counting data; however, in the case of clusters, the counting is performed in semi-automated mode. MDPI 2022-11-07 /pmc/articles/PMC9659203/ /pubmed/36366269 http://dx.doi.org/10.3390/s22218567 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Hassan, Syeda Iqra
Alam, Muhammad Mansoor
Zia, Muhammad Yousuf Irfan
Rashid, Muhammad
Illahi, Usman
Su’ud, Mazliham Mohd
Rice Crop Counting Using Aerial Imagery and GIS for the Assessment of Soil Health to Increase Crop Yield
title Rice Crop Counting Using Aerial Imagery and GIS for the Assessment of Soil Health to Increase Crop Yield
title_full Rice Crop Counting Using Aerial Imagery and GIS for the Assessment of Soil Health to Increase Crop Yield
title_fullStr Rice Crop Counting Using Aerial Imagery and GIS for the Assessment of Soil Health to Increase Crop Yield
title_full_unstemmed Rice Crop Counting Using Aerial Imagery and GIS for the Assessment of Soil Health to Increase Crop Yield
title_short Rice Crop Counting Using Aerial Imagery and GIS for the Assessment of Soil Health to Increase Crop Yield
title_sort rice crop counting using aerial imagery and gis for the assessment of soil health to increase crop yield
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9659203/
https://www.ncbi.nlm.nih.gov/pubmed/36366269
http://dx.doi.org/10.3390/s22218567
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