Evaluation of nitrogen status in a wheat crop using unmanned aerial vehicle images
The excessive use of N in agriculture has created various environmental and economic problems. Remote sensing and unmanned aerial vehicles (UAV) are feasible solutions to infer the status of a crop and enable a better management during the growing season. The objective of this study was to correlate...
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Veröffentlicht in: | Chilean journal of agricultural research 2021-07, Vol.81 (3), p.408-419 |
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container_title | Chilean journal of agricultural research |
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creator | Gordillo-Salinas, Víctor Manuel Flores-Magdaleno, Héctor Ortiz-Solorio, Carlos Alberto Arteaga-Ramírez, Ramón |
description | The excessive use of N in agriculture has created various environmental and economic problems. Remote sensing and unmanned aerial vehicles (UAV) are feasible solutions to infer the status of a crop and enable a better management during the growing season. The objective of this study was to correlate experimental N content and wheat (Triticum aestivum L.) crop aboveground biomass data with vegetation indices estimated using UAV images. In this study, the N nutrition index and N dilution curve were used as indicators of the state of plant N; input variables to estimate these indicators were the N content and aboveground biomass. Four flight campaigns were conducted at different phenological stages of a wheat crop and seven N doses were evaluated. A linear relationship of blue normalized difference vegetation index (BNDVI) and green normalized difference vegetation index (GNDVI) with aboveground biomass and N content was identified. BNDVI and biomass demonstrated high [R.sup.2] during boots swollen and end of anthesis growth stages (0.62 and 0.68, respectively), while GNDVI showed the highest [R.sup.2] during the ear half emerged and beginning of anthesis growth stages (0.84 and 0.79, respectively). For N content estimation, GNDVI showed a higher correlation than BNDVI, and the adjustment curve showed an [R.sup.2] up to 0.81 only for the last flight (end of anthesis), BNDVI showed an [R.sup.2] of 0.78. Remote sensing and vegetation indices estimated from UAV images can be reliably used to estimate N content and wheat biomass, contributing to knowing the crop N status. Key words: Blue normalized difference vegetation index, critical nitrogen dilution curve, green normalized difference vegetation index, nitrogen nutrition index, Triticum aestivum. |
doi_str_mv | 10.4067/S0718-58392021000300408 |
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Remote sensing and unmanned aerial vehicles (UAV) are feasible solutions to infer the status of a crop and enable a better management during the growing season. The objective of this study was to correlate experimental N content and wheat (Triticum aestivum L.) crop aboveground biomass data with vegetation indices estimated using UAV images. In this study, the N nutrition index and N dilution curve were used as indicators of the state of plant N; input variables to estimate these indicators were the N content and aboveground biomass. Four flight campaigns were conducted at different phenological stages of a wheat crop and seven N doses were evaluated. A linear relationship of blue normalized difference vegetation index (BNDVI) and green normalized difference vegetation index (GNDVI) with aboveground biomass and N content was identified. BNDVI and biomass demonstrated high [R.sup.2] during boots swollen and end of anthesis growth stages (0.62 and 0.68, respectively), while GNDVI showed the highest [R.sup.2] during the ear half emerged and beginning of anthesis growth stages (0.84 and 0.79, respectively). For N content estimation, GNDVI showed a higher correlation than BNDVI, and the adjustment curve showed an [R.sup.2] up to 0.81 only for the last flight (end of anthesis), BNDVI showed an [R.sup.2] of 0.78. Remote sensing and vegetation indices estimated from UAV images can be reliably used to estimate N content and wheat biomass, contributing to knowing the crop N status. Key words: Blue normalized difference vegetation index, critical nitrogen dilution curve, green normalized difference vegetation index, nitrogen nutrition index, Triticum aestivum.</description><identifier>ISSN: 0718-5839</identifier><identifier>ISSN: 0718-5820</identifier><identifier>EISSN: 0718-5839</identifier><identifier>DOI: 10.4067/S0718-58392021000300408</identifier><language>eng</language><publisher>Chillán: Instituto de Investigaciones Agropecuarias</publisher><subject>Agriculture ; AGRICULTURE, MULTIDISCIPLINARY ; AGRONOMY ; Analysis ; Biomass ; Cereal crops ; Crops ; Digital cameras ; Dilution ; Drone aircraft ; Flight ; Growing season ; Indicators ; Nitrogen ; Normalized difference vegetative index ; Nutrition ; Nutrition assessment ; Remote sensing ; Software ; Unmanned aerial vehicles ; Vegetation ; Vegetation index ; Wheat ; Wheat industry</subject><ispartof>Chilean journal of agricultural research, 2021-07, Vol.81 (3), p.408-419</ispartof><rights>COPYRIGHT 2021 Instituto de Investigaciones Agropecuarias</rights><rights>2021. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c494t-74c5410d4a2e5d8b0a5eee38e73f251f3eb0859f902ab07e4d7eb6209eff5fd23</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,27901,27902</link.rule.ids></links><search><creatorcontrib>Gordillo-Salinas, Víctor Manuel</creatorcontrib><creatorcontrib>Flores-Magdaleno, Héctor</creatorcontrib><creatorcontrib>Ortiz-Solorio, Carlos Alberto</creatorcontrib><creatorcontrib>Arteaga-Ramírez, Ramón</creatorcontrib><title>Evaluation of nitrogen status in a wheat crop using unmanned aerial vehicle images</title><title>Chilean journal of agricultural research</title><addtitle>Chil. j. agric. res</addtitle><description>The excessive use of N in agriculture has created various environmental and economic problems. Remote sensing and unmanned aerial vehicles (UAV) are feasible solutions to infer the status of a crop and enable a better management during the growing season. The objective of this study was to correlate experimental N content and wheat (Triticum aestivum L.) crop aboveground biomass data with vegetation indices estimated using UAV images. In this study, the N nutrition index and N dilution curve were used as indicators of the state of plant N; input variables to estimate these indicators were the N content and aboveground biomass. Four flight campaigns were conducted at different phenological stages of a wheat crop and seven N doses were evaluated. A linear relationship of blue normalized difference vegetation index (BNDVI) and green normalized difference vegetation index (GNDVI) with aboveground biomass and N content was identified. BNDVI and biomass demonstrated high [R.sup.2] during boots swollen and end of anthesis growth stages (0.62 and 0.68, respectively), while GNDVI showed the highest [R.sup.2] during the ear half emerged and beginning of anthesis growth stages (0.84 and 0.79, respectively). For N content estimation, GNDVI showed a higher correlation than BNDVI, and the adjustment curve showed an [R.sup.2] up to 0.81 only for the last flight (end of anthesis), BNDVI showed an [R.sup.2] of 0.78. Remote sensing and vegetation indices estimated from UAV images can be reliably used to estimate N content and wheat biomass, contributing to knowing the crop N status. Key words: Blue normalized difference vegetation index, critical nitrogen dilution curve, green normalized difference vegetation index, nitrogen nutrition index, Triticum aestivum.</description><subject>Agriculture</subject><subject>AGRICULTURE, MULTIDISCIPLINARY</subject><subject>AGRONOMY</subject><subject>Analysis</subject><subject>Biomass</subject><subject>Cereal crops</subject><subject>Crops</subject><subject>Digital cameras</subject><subject>Dilution</subject><subject>Drone aircraft</subject><subject>Flight</subject><subject>Growing season</subject><subject>Indicators</subject><subject>Nitrogen</subject><subject>Normalized difference vegetative index</subject><subject>Nutrition</subject><subject>Nutrition assessment</subject><subject>Remote sensing</subject><subject>Software</subject><subject>Unmanned aerial vehicles</subject><subject>Vegetation</subject><subject>Vegetation index</subject><subject>Wheat</subject><subject>Wheat industry</subject><issn>0718-5839</issn><issn>0718-5820</issn><issn>0718-5839</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp1kW1LwzAQx4soOKefwYCvNy9p0rQvx5gPMBB8eF3S9tJltMlM2onf3urEOUTuxR1397s7_hdFlxSmHBJ5_QSSphORxhkDRgEgBuCQHkWjn8Lxr_g0OgthDZBwSeNR9LjYqqZXnXGWOE2s6byr0ZLQqa4PxFiiyNsKVUdK7zakD8bWpLetshYrotAb1ZAtrkzZIDGtqjGcRydaNQEvvv04erlZPM_vJsuH2_v5bDkpeca7ieSl4BQqrhiKKi1ACUSMU5SxZoLqGAtIRaYzYKoAibySWCQMMtRa6IrF42i6mxtKg43L1673dliYfymS_1FkAK52wMa71x5Dt0eYSNKYUiaTfVetGsyN1a7zqmxNKPNZIqkQgjK6X37QNViFrSmdRW2G_AEgd8CgYwgedb7xg17-PaeQfz7y37M_AIshjLQ</recordid><startdate>20210701</startdate><enddate>20210701</enddate><creator>Gordillo-Salinas, Víctor Manuel</creator><creator>Flores-Magdaleno, Héctor</creator><creator>Ortiz-Solorio, Carlos Alberto</creator><creator>Arteaga-Ramírez, Ramón</creator><general>Instituto de Investigaciones Agropecuarias</general><general>Chilean Journal of Agricultural Research</general><general>Instituto de Investigaciones Agropecuarias, INIA</general><scope>AAYXX</scope><scope>CITATION</scope><scope>INF</scope><scope>3V.</scope><scope>7WY</scope><scope>7X2</scope><scope>7XB</scope><scope>883</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>CLZPN</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>HCIFZ</scope><scope>K60</scope><scope>K6~</scope><scope>L.-</scope><scope>M0F</scope><scope>M0K</scope><scope>PIMPY</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>GPN</scope></search><sort><creationdate>20210701</creationdate><title>Evaluation of nitrogen status in a wheat crop using unmanned aerial vehicle images</title><author>Gordillo-Salinas, Víctor Manuel ; 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Remote sensing and unmanned aerial vehicles (UAV) are feasible solutions to infer the status of a crop and enable a better management during the growing season. The objective of this study was to correlate experimental N content and wheat (Triticum aestivum L.) crop aboveground biomass data with vegetation indices estimated using UAV images. In this study, the N nutrition index and N dilution curve were used as indicators of the state of plant N; input variables to estimate these indicators were the N content and aboveground biomass. Four flight campaigns were conducted at different phenological stages of a wheat crop and seven N doses were evaluated. A linear relationship of blue normalized difference vegetation index (BNDVI) and green normalized difference vegetation index (GNDVI) with aboveground biomass and N content was identified. BNDVI and biomass demonstrated high [R.sup.2] during boots swollen and end of anthesis growth stages (0.62 and 0.68, respectively), while GNDVI showed the highest [R.sup.2] during the ear half emerged and beginning of anthesis growth stages (0.84 and 0.79, respectively). For N content estimation, GNDVI showed a higher correlation than BNDVI, and the adjustment curve showed an [R.sup.2] up to 0.81 only for the last flight (end of anthesis), BNDVI showed an [R.sup.2] of 0.78. Remote sensing and vegetation indices estimated from UAV images can be reliably used to estimate N content and wheat biomass, contributing to knowing the crop N status. Key words: Blue normalized difference vegetation index, critical nitrogen dilution curve, green normalized difference vegetation index, nitrogen nutrition index, Triticum aestivum.</abstract><cop>Chillán</cop><pub>Instituto de Investigaciones Agropecuarias</pub><doi>10.4067/S0718-58392021000300408</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Agriculture AGRICULTURE, MULTIDISCIPLINARY AGRONOMY Analysis Biomass Cereal crops Crops Digital cameras Dilution Drone aircraft Flight Growing season Indicators Nitrogen Normalized difference vegetative index Nutrition Nutrition assessment Remote sensing Software Unmanned aerial vehicles Vegetation Vegetation index Wheat Wheat industry |
title | Evaluation of nitrogen status in a wheat crop using unmanned aerial vehicle images |
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