Spectral considerations for modeling yield of canola
Prominent yellow flowers that are present in a Brassica oilseed crop such as canola require careful consideration when selecting a spectral index for yield estimation. This study evaluated spectral indices for multispectral sensors that correlate with the seed yield of Brassica oilseed crops. A smal...
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description | Prominent yellow flowers that are present in a Brassica oilseed crop such as canola require careful consideration when selecting a spectral index for yield estimation. This study evaluated spectral indices for multispectral sensors that correlate with the seed yield of Brassica oilseed crops. A small-plot experiment was conducted near Adams, Oregon in which spring canola was grown under varying water regimes and nitrogen treatments to create a wide range in oilseed yield. Plot measurements consisted of canopy reflectance at flowering using a hand-held spectroradiometer and seed yield at physiological maturity. Spectroradiometric measurements were converted to MODIS band equivalent reflectance. Selected indices were computed from spectra obtained with the radiometer and correlated with seed yield. A normalized difference yellowness index (NDYI), computed from the green and blue wavebands, overcame limitations of the normalized difference vegetation index (NDVI) during flowering and best modeled variability in relative yield potential. NDYI was more linear and correlated with county-wide oilseed yield data and MODIS satellite data from North Dakota (r2≤0.72) than NDVI (r2≤0.66). NDYI only requires wavebands in the visible region of the spectrum and can be applied to any satellite or aerial sensor that has blue and green channels. These findings highlight the benefit of using a spectral index that is sensitive to reproductive growth of vegetation instead of vegetative growth for crops with spectrally prominent reproductive canopy elements. Our results indicate that NDYI is a better indicator of yield potential than NDVI during mid-season development stages, especially peak flowering.
•We evaluate the performance of NDVI for statistically modeling canola yield.•A contrast of Green and Blue wavebands is better related to yield than NIR and Red.•NIR is not necessary for within-field mapping of yield potential during flowering. |
doi_str_mv | 10.1016/j.rse.2016.06.016 |
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•We evaluate the performance of NDVI for statistically modeling canola yield.•A contrast of Green and Blue wavebands is better related to yield than NIR and Red.•NIR is not necessary for within-field mapping of yield potential during flowering.</description><identifier>ISSN: 0034-4257</identifier><identifier>EISSN: 1879-0704</identifier><identifier>DOI: 10.1016/j.rse.2016.06.016</identifier><language>eng</language><publisher>Elsevier Inc</publisher><subject>Brassica oilseed ; Canola ; Correlation ; Crops ; Flowering ; Oilseeds ; Optical remote sensing ; Reflectance ; Seeds ; Spectra ; Vegetation ; Yield estimation</subject><ispartof>Remote sensing of environment, 2016-10, Vol.184, p.161-174</ispartof><rights>2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c472t-5f0e9aabbfd468b3524a3c81d79aae569852528081707fff281b17d0557d3bc63</citedby><cites>FETCH-LOGICAL-c472t-5f0e9aabbfd468b3524a3c81d79aae569852528081707fff281b17d0557d3bc63</cites><orcidid>0000-0003-4637-0886 ; 0000-0002-2752-7414</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.rse.2016.06.016$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Sulik, John J.</creatorcontrib><creatorcontrib>Long, Dan S.</creatorcontrib><title>Spectral considerations for modeling yield of canola</title><title>Remote sensing of environment</title><description>Prominent yellow flowers that are present in a Brassica oilseed crop such as canola require careful consideration when selecting a spectral index for yield estimation. This study evaluated spectral indices for multispectral sensors that correlate with the seed yield of Brassica oilseed crops. A small-plot experiment was conducted near Adams, Oregon in which spring canola was grown under varying water regimes and nitrogen treatments to create a wide range in oilseed yield. Plot measurements consisted of canopy reflectance at flowering using a hand-held spectroradiometer and seed yield at physiological maturity. Spectroradiometric measurements were converted to MODIS band equivalent reflectance. Selected indices were computed from spectra obtained with the radiometer and correlated with seed yield. A normalized difference yellowness index (NDYI), computed from the green and blue wavebands, overcame limitations of the normalized difference vegetation index (NDVI) during flowering and best modeled variability in relative yield potential. NDYI was more linear and correlated with county-wide oilseed yield data and MODIS satellite data from North Dakota (r2≤0.72) than NDVI (r2≤0.66). NDYI only requires wavebands in the visible region of the spectrum and can be applied to any satellite or aerial sensor that has blue and green channels. These findings highlight the benefit of using a spectral index that is sensitive to reproductive growth of vegetation instead of vegetative growth for crops with spectrally prominent reproductive canopy elements. Our results indicate that NDYI is a better indicator of yield potential than NDVI during mid-season development stages, especially peak flowering.
•We evaluate the performance of NDVI for statistically modeling canola yield.•A contrast of Green and Blue wavebands is better related to yield than NIR and Red.•NIR is not necessary for within-field mapping of yield potential during flowering.</description><subject>Brassica oilseed</subject><subject>Canola</subject><subject>Correlation</subject><subject>Crops</subject><subject>Flowering</subject><subject>Oilseeds</subject><subject>Optical remote sensing</subject><subject>Reflectance</subject><subject>Seeds</subject><subject>Spectra</subject><subject>Vegetation</subject><subject>Yield estimation</subject><issn>0034-4257</issn><issn>1879-0704</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNqNkEtLAzEUhYMoWB8_wN0s3Uy9N5NMMriS4gsKLtR1yOQhKdNJTaZC_72pdS3CgXu5nHPgfoRcIcwRsL1ZzVN2c1rWORRhe0RmKEVXgwB2TGYADasZ5eKUnOW8AkAuBc4Ie904MyU9VCaOOViX9BTKVvmYqnW0bgjjR7ULbrBV9JXRYxz0BTnxesju8neek_eH-7fFU718eXxe3C1rwwSdau7BdVr3vbeslX3DKdONkWhFuTredpJTTiVIFCC891Rij8IC58I2vWmbc3J96N2k-Ll1eVLrkI0bBj26uM0KZcNbykHgP6xUdEgZ7lvxYDUp5pycV5sU1jrtFILaw1QrVWCqPUwFRT-Z20PGlXe_gksqm-BG42xIhZ-yMfyR_gbwHHtb</recordid><startdate>201610</startdate><enddate>201610</enddate><creator>Sulik, John J.</creator><creator>Long, Dan S.</creator><general>Elsevier Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SN</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>L.G</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>KR7</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0003-4637-0886</orcidid><orcidid>https://orcid.org/0000-0002-2752-7414</orcidid></search><sort><creationdate>201610</creationdate><title>Spectral considerations for modeling yield of canola</title><author>Sulik, John J. ; Long, Dan S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c472t-5f0e9aabbfd468b3524a3c81d79aae569852528081707fff281b17d0557d3bc63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Brassica oilseed</topic><topic>Canola</topic><topic>Correlation</topic><topic>Crops</topic><topic>Flowering</topic><topic>Oilseeds</topic><topic>Optical remote sensing</topic><topic>Reflectance</topic><topic>Seeds</topic><topic>Spectra</topic><topic>Vegetation</topic><topic>Yield estimation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sulik, John J.</creatorcontrib><creatorcontrib>Long, Dan S.</creatorcontrib><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Remote sensing of environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sulik, John J.</au><au>Long, Dan S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spectral considerations for modeling yield of canola</atitle><jtitle>Remote sensing of environment</jtitle><date>2016-10</date><risdate>2016</risdate><volume>184</volume><spage>161</spage><epage>174</epage><pages>161-174</pages><issn>0034-4257</issn><eissn>1879-0704</eissn><abstract>Prominent yellow flowers that are present in a Brassica oilseed crop such as canola require careful consideration when selecting a spectral index for yield estimation. This study evaluated spectral indices for multispectral sensors that correlate with the seed yield of Brassica oilseed crops. A small-plot experiment was conducted near Adams, Oregon in which spring canola was grown under varying water regimes and nitrogen treatments to create a wide range in oilseed yield. Plot measurements consisted of canopy reflectance at flowering using a hand-held spectroradiometer and seed yield at physiological maturity. Spectroradiometric measurements were converted to MODIS band equivalent reflectance. Selected indices were computed from spectra obtained with the radiometer and correlated with seed yield. A normalized difference yellowness index (NDYI), computed from the green and blue wavebands, overcame limitations of the normalized difference vegetation index (NDVI) during flowering and best modeled variability in relative yield potential. NDYI was more linear and correlated with county-wide oilseed yield data and MODIS satellite data from North Dakota (r2≤0.72) than NDVI (r2≤0.66). NDYI only requires wavebands in the visible region of the spectrum and can be applied to any satellite or aerial sensor that has blue and green channels. These findings highlight the benefit of using a spectral index that is sensitive to reproductive growth of vegetation instead of vegetative growth for crops with spectrally prominent reproductive canopy elements. Our results indicate that NDYI is a better indicator of yield potential than NDVI during mid-season development stages, especially peak flowering.
•We evaluate the performance of NDVI for statistically modeling canola yield.•A contrast of Green and Blue wavebands is better related to yield than NIR and Red.•NIR is not necessary for within-field mapping of yield potential during flowering.</abstract><pub>Elsevier Inc</pub><doi>10.1016/j.rse.2016.06.016</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0003-4637-0886</orcidid><orcidid>https://orcid.org/0000-0002-2752-7414</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Brassica oilseed Canola Correlation Crops Flowering Oilseeds Optical remote sensing Reflectance Seeds Spectra Vegetation Yield estimation |
title | Spectral considerations for modeling yield of canola |
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