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Threshold values of canopy reflectance indices and chlorophyll meter readings for optimal nitrogen nutrition of tomato
Author(s) -
Padilla F.M.,
PeñaFleitas M.T.,
Gallardo M.,
Thompson R.B.
Publication year - 2015
Publication title -
annals of applied biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.677
H-Index - 80
eISSN - 1744-7348
pISSN - 0003-4746
DOI - 10.1111/aab.12181
Subject(s) - crop , canopy , normalized difference vegetation index , reflectivity , vegetation (pathology) , chlorophyll , mathematics , agronomy , environmental science , leaf area index , biology , horticulture , botany , physics , optics , medicine , pathology
Sustainable and optimal economic N management requires correct and timely on‐farm assessment of crop N status to detect N deficiency or excess. Optical sensors are promising tools to assess crop N status throughout a crop or at critical times. The ability of optical sensor measurements of canopy reflectance (Crop Circle ACS 470) and leaf chlorophyll ( SPAD 502 chlorophyll meter) to assess crop N status was evaluated weekly throughout an indeterminate tomato crop. Strong linear relationships with the optical sensor measurements were obtained, throughout most of the crop, for both (a) crop N content for ranges of 1.5–4.5%, and (b) the nitrogen nutrition index ( NNI ) for ranges of 0.4–1.3. The relationships of the optical sensor measurements to crop NNI were generally equal to or slightly better than with crop N content. Indices based on reflectance in the red, the normalised difference vegetation index ( NDVI ) and the red vegetation index ( RVI ), were the best predictors of crop N status in terms of goodness of fit, earliness and maintenance of relationships throughout the crop. SPAD chlorophyll readings and reflectance indices based on reflectance in the green, the normalised difference vegetation index on greenness ( GNDVI ) and the green vegetation index ( GVI ), were good indicators of crop N status for most of the crop, but with lower goodness of fit in the latter part of the crop. The linear relationships between sensor indices and readings with NNI or crop N content, each week, demonstrated the potential for using proximal canopy reflectance indices such as NDVI and RVI , and chlorophyll meter for monitoring crop N status of indeterminate tomato crops. Threshold values for optimal crop N nutrition for canopy reflectance indices and for chlorophyll meter readings were derived for each day of measurement from the relationships between optical sensor measurements and NNI by solving for NNI = 1. The threshold values obtained for each index and type of measurement varied during the crop cycle. The approach developed for determining threshold values from NNI can facilitate on‐farm use of optical sensors for monitoring crop N status, by enabling assessment of whether crop N status is excessive, deficient or adequate.