Leaf versus whole-canopy remote sensing methodologies for crop monitoring under conservation agriculture: a case of study with maize in Zimbabwe

Enhancing nitrogen fertilization efficiency for improving yield is a major challenge for smallholder farming systems. Rapid and cost-effective methodologies with the capability to assess the effects of fertilization are required to facilitate smallholder farm management. This study compares maize leaf and canopy-based approaches for assessing N fertilization performance under different tillage, residue coverage and top-dressing conditions in Zimbabwe. Among the measurements made on individual leaves, chlorophyll readings were the best indicators for both N content in leaves (R < 0.700) and grain yield (GY) (R < 0.800). Canopy indices reported even higher correlation coefficients when assessing GY, especially those based on the measurements of the vegetation density as the green area indices (R < 0.850). Canopy measurements from both ground and aerial platforms performed very similar, but indices assessed from the UAV performed best in capturing the most relevant information from the whole plot and correlations with GY and leaf N content were slightly higher. Leaf-based measurements demonstrated utility in monitoring N leaf content, though canopy measurements outperformed the leaf readings in assessing GY parameters, while providing the additional value derived from the affordability and easiness of using a pheno-pole system or the high-throughput capacities of the UAVs.

Saved in:
Bibliographic Details
Main Authors: Gracia-Romero, A., Kefauver, S.C., Vergara Diaz, O., Hamadziripi, E., Zaman-Allah, M., Thierfelder, C., Prasanna, B.M., Cairns, J.E., Araus, J.L.
Format: Article biblioteca
Language:English
Published: Nature Publishing Group 2020
Subjects:AGRICULTURAL SCIENCES AND BIOTECHNOLOGY, AGROECOLOGY, IMAGE ANALYSIS, REMOTE SENSING, PLANT PHYSIOLOGY, STRESS,
Online Access:https://hdl.handle.net/10883/20964
Tags: Add Tag
No Tags, Be the first to tag this record!
id dig-cimmyt-10883-20964
record_format koha
spelling dig-cimmyt-10883-209642023-10-31T15:09:38Z Leaf versus whole-canopy remote sensing methodologies for crop monitoring under conservation agriculture: a case of study with maize in Zimbabwe Gracia-Romero, A. Kefauver, S.C. Vergara Diaz, O. Hamadziripi, E. Zaman-Allah, M. Thierfelder, C. Prasanna, B.M. Cairns, J.E. Araus, J.L. AGRICULTURAL SCIENCES AND BIOTECHNOLOGY AGROECOLOGY IMAGE ANALYSIS REMOTE SENSING PLANT PHYSIOLOGY STRESS Enhancing nitrogen fertilization efficiency for improving yield is a major challenge for smallholder farming systems. Rapid and cost-effective methodologies with the capability to assess the effects of fertilization are required to facilitate smallholder farm management. This study compares maize leaf and canopy-based approaches for assessing N fertilization performance under different tillage, residue coverage and top-dressing conditions in Zimbabwe. Among the measurements made on individual leaves, chlorophyll readings were the best indicators for both N content in leaves (R < 0.700) and grain yield (GY) (R < 0.800). Canopy indices reported even higher correlation coefficients when assessing GY, especially those based on the measurements of the vegetation density as the green area indices (R < 0.850). Canopy measurements from both ground and aerial platforms performed very similar, but indices assessed from the UAV performed best in capturing the most relevant information from the whole plot and correlations with GY and leaf N content were slightly higher. Leaf-based measurements demonstrated utility in monitoring N leaf content, though canopy measurements outperformed the leaf readings in assessing GY parameters, while providing the additional value derived from the affordability and easiness of using a pheno-pole system or the high-throughput capacities of the UAVs. 2020-10-10T00:05:15Z 2020-10-10T00:05:15Z 2020 Article Published Version https://hdl.handle.net/10883/20964 10.1038/s41598-020-73110-3 English https://www.nature.com/articles/s41598-020-73110-3#Sec23 CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose Open Access PDF London (United Kingdom) Nature Publishing Group 1 10 2045-2322 Nature Scientific Reports
institution CIMMYT
collection DSpace
country México
countrycode MX
component Bibliográfico
access En linea
databasecode dig-cimmyt
tag biblioteca
region America del Norte
libraryname CIMMYT Library
language English
topic AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
AGROECOLOGY
IMAGE ANALYSIS
REMOTE SENSING
PLANT PHYSIOLOGY
STRESS
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
AGROECOLOGY
IMAGE ANALYSIS
REMOTE SENSING
PLANT PHYSIOLOGY
STRESS
spellingShingle AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
AGROECOLOGY
IMAGE ANALYSIS
REMOTE SENSING
PLANT PHYSIOLOGY
STRESS
AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
AGROECOLOGY
IMAGE ANALYSIS
REMOTE SENSING
PLANT PHYSIOLOGY
STRESS
Gracia-Romero, A.
Kefauver, S.C.
Vergara Diaz, O.
Hamadziripi, E.
Zaman-Allah, M.
Thierfelder, C.
Prasanna, B.M.
Cairns, J.E.
Araus, J.L.
Leaf versus whole-canopy remote sensing methodologies for crop monitoring under conservation agriculture: a case of study with maize in Zimbabwe
description Enhancing nitrogen fertilization efficiency for improving yield is a major challenge for smallholder farming systems. Rapid and cost-effective methodologies with the capability to assess the effects of fertilization are required to facilitate smallholder farm management. This study compares maize leaf and canopy-based approaches for assessing N fertilization performance under different tillage, residue coverage and top-dressing conditions in Zimbabwe. Among the measurements made on individual leaves, chlorophyll readings were the best indicators for both N content in leaves (R < 0.700) and grain yield (GY) (R < 0.800). Canopy indices reported even higher correlation coefficients when assessing GY, especially those based on the measurements of the vegetation density as the green area indices (R < 0.850). Canopy measurements from both ground and aerial platforms performed very similar, but indices assessed from the UAV performed best in capturing the most relevant information from the whole plot and correlations with GY and leaf N content were slightly higher. Leaf-based measurements demonstrated utility in monitoring N leaf content, though canopy measurements outperformed the leaf readings in assessing GY parameters, while providing the additional value derived from the affordability and easiness of using a pheno-pole system or the high-throughput capacities of the UAVs.
format Article
topic_facet AGRICULTURAL SCIENCES AND BIOTECHNOLOGY
AGROECOLOGY
IMAGE ANALYSIS
REMOTE SENSING
PLANT PHYSIOLOGY
STRESS
author Gracia-Romero, A.
Kefauver, S.C.
Vergara Diaz, O.
Hamadziripi, E.
Zaman-Allah, M.
Thierfelder, C.
Prasanna, B.M.
Cairns, J.E.
Araus, J.L.
author_facet Gracia-Romero, A.
Kefauver, S.C.
Vergara Diaz, O.
Hamadziripi, E.
Zaman-Allah, M.
Thierfelder, C.
Prasanna, B.M.
Cairns, J.E.
Araus, J.L.
author_sort Gracia-Romero, A.
title Leaf versus whole-canopy remote sensing methodologies for crop monitoring under conservation agriculture: a case of study with maize in Zimbabwe
title_short Leaf versus whole-canopy remote sensing methodologies for crop monitoring under conservation agriculture: a case of study with maize in Zimbabwe
title_full Leaf versus whole-canopy remote sensing methodologies for crop monitoring under conservation agriculture: a case of study with maize in Zimbabwe
title_fullStr Leaf versus whole-canopy remote sensing methodologies for crop monitoring under conservation agriculture: a case of study with maize in Zimbabwe
title_full_unstemmed Leaf versus whole-canopy remote sensing methodologies for crop monitoring under conservation agriculture: a case of study with maize in Zimbabwe
title_sort leaf versus whole-canopy remote sensing methodologies for crop monitoring under conservation agriculture: a case of study with maize in zimbabwe
publisher Nature Publishing Group
publishDate 2020
url https://hdl.handle.net/10883/20964
work_keys_str_mv AT graciaromeroa leafversuswholecanopyremotesensingmethodologiesforcropmonitoringunderconservationagricultureacaseofstudywithmaizeinzimbabwe
AT kefauversc leafversuswholecanopyremotesensingmethodologiesforcropmonitoringunderconservationagricultureacaseofstudywithmaizeinzimbabwe
AT vergaradiazo leafversuswholecanopyremotesensingmethodologiesforcropmonitoringunderconservationagricultureacaseofstudywithmaizeinzimbabwe
AT hamadziripie leafversuswholecanopyremotesensingmethodologiesforcropmonitoringunderconservationagricultureacaseofstudywithmaizeinzimbabwe
AT zamanallahm leafversuswholecanopyremotesensingmethodologiesforcropmonitoringunderconservationagricultureacaseofstudywithmaizeinzimbabwe
AT thierfelderc leafversuswholecanopyremotesensingmethodologiesforcropmonitoringunderconservationagricultureacaseofstudywithmaizeinzimbabwe
AT prasannabm leafversuswholecanopyremotesensingmethodologiesforcropmonitoringunderconservationagricultureacaseofstudywithmaizeinzimbabwe
AT cairnsje leafversuswholecanopyremotesensingmethodologiesforcropmonitoringunderconservationagricultureacaseofstudywithmaizeinzimbabwe
AT arausjl leafversuswholecanopyremotesensingmethodologiesforcropmonitoringunderconservationagricultureacaseofstudywithmaizeinzimbabwe
_version_ 1781883736120360960