Estimation of wheat nitrogen status under drip irrigation with canopy spectral indices (original) (raw)
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Model for detecting nitrogen deficiency in wheat crop using spectral indices
Journal of Agrometeorology
An experiment was conducted four years (2007-08 to 20010-11) during rabi at Anand, India to study nitrogen stress response of wheat (Triticum aestivum L.) on spectral signature using spectroradiometer (Model - UniSpec DC Dual Channel Spectrometer, PP System, USA). The experiment was carried out with two wheat cultivars viz., GW496 and Lok 1 and five levels of nitrogen 120, 90, 60, 30 and 0 kg ha-1. The NDVI (normalized difference vegetation index) which is an indicator of status of crop biomass was found higher at 45 to 65 DAS of the crop age. The same characteristics were also observed in case of NDRE (normalize difference red edge) index at the 45 to 65 DAS of the crop age. Based on the index value of NDVI & NDRE at different growth stages of wheat crop, it was revealed that the crop biomass under the 120 N kg ha-1 could be more healthy which resulted in better yield. The variety wise analysis showed that no significant varietal differences were observed for NDVI, mSR and NDRE dur...
Nitrogen stress sensors are based on reflectance measurement controlled by the chlorophyll content. Reflectance of canopy is spectral dependent and more sensitive narrow spectral band can be exploited for reflectance measurement sensors.The experiments for present study were conducted in split plot design on two widely grown wheat (Triticumaestivum L.) cultivars (GW 496 and LOK 1) during rabi seasons of three consecutive years 2007-08 to 2009-10 at Anand. The two cultivars viz; GW 496 and LOK 1 were taken as the main treatments and five nitrogen fertilizer application rates 120, 90, 60, 30 and 0 kg N ha-1 as sub-treatments were randomized in four replications. Spectral reflectance measurements were taken over wheat canopy at different crop growth stages with a dual channel spectroradiometer.T he ratio based and soil based indices (viz; RVI, DVI, NRI, RDVI, OSAVI,SAVI2,TSAVI and PVI) were used to find optimal wavebands.The optimum wavebands were explored using contours of R 2 values ...
In-Season Estimation of Wheat Response to Nitrogen Using Normalized Difference Vegetation Index
International Journal of Plant Production
Applying fertilizer nitrogen (N) only when a crop response is predicted may enhance use efficiency and profitability while protecting the environment. The crop response index at harvest (RI-harvest, the ratio of the maximum grain yield and that of the plot in question) indicates the actual crop response to applied fertilizer N, although it is calculated after harvest. The objective of this study was to predict RI-harvest of wheat using normalized difference vegetation index (NDVI) response index (RI-NDVI, defined as the ratio of the NDVI in an N-sufficient plot and that in the field in question) captured at Feekes 6 stage. Field experiments were carried out across seven site-years (2017/18 to 2020/21) on wheat. In the first three seasons, the relationships between RI-harvest and RI-NDVI were established by applying a range of fertilizer N levels (0–320 kg N ha− 1), whereas the fourth season was used for validation. The results indicated that RI-NDVI could explain 79% of the variatio...
2013
A field experiment was carried out during rabi 2010-11 and 2011-12 to study the canopy reflectance and to predict the grain and biomass yield of wheat (Triticum aestivum L.) under different irrigation and nitrogen management practices using canopy reflectance spectra model. Wheat (cv. PBW 502) was grown with four levels of irrigation, i.e. 0.4, 0.6, 0.8 and 1.0 IW/CPE and three N sources, i e 120 kg N/ha as urea, 60 kg N/ha as urea + 60 kg N/ha as farmyard manure (FYM) and 120 kg N/ha as FYM. Three spectral reflectance indices, viz. Red Normalized Difference Vegetation Index (RNDVI), Green Normalized Difference Vegetation Index (GNDVI) and Simple Ratio (SR) were computed using the spectral reflectance data. It was observed that across the treatments, the RNDVI, GNDVI, and SR increased from crown root initiation (CRI) to booting stage and thereafter decreased progressively till harvest. The pooled yield data of both the years showed significantly higher yield in 0.8 and 1.0 IW/CPE irrigation levels than 0.4 and 0.6 IW/CPE irrigation levels. The pooled data of grain yield under different nitrogen practices showed significantly higher yield in urea treatment followed by urea+FYM treatment and FYM treatment. The biomass yield under different nitrogen management practices followed trend similar to grain yield. A significant and positive correlation coefficient was observed between grain and biomass yield and spectral reflectance indices (RNDVI, GNDVI, SR) for all the phenological stages except at CRI stage and maturity stage. Highest correlation coefficient (0.97 for grain yield and 0.93 for biomass yield) was observed for GNDVI measured at milking stage. The model could account for 79 % variation in the grain yield of wheat with root mean square error (RMSE) (%) of 17.1. Similarly the model could account for 86% variation in the biomass yield of wheat with RMSE (%) of 12.7. The models slightly underestimate the grain and biomass yield of wheat with coefficient of residual mass (CRM) value of 0.13 and 0.08, respectively.