Prediction of Wheat Yield Using Spectral Reflectance Indices Under Different Tillage, Residue 
and Nitrogen Management Practices

Adak, Sujan; Bandyopadhyay, K. K.; Sahoo, Rabi Narayan; Mridha, Nilimesh; Shrivastava, Manoj; Purakayastha, T. J.

doi:10.18520/cs/v121/i3/402-413

Cited by 13 publications

(5 citation statements)

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“…Though there was comparable wheat yield under different tillage and residue management, while it increased significantly with the increase in the doses of nitrogen (Figures 4C,D). Similar findings were also reported by Adak et al (2021). The wheat yield was expressed in terms of maize equivalent yield (MEY) and was added to the yield of maize to find out system productivity.…”

Section: Maize-wheat System Productivitysupporting

confidence: 70%

Impact of contrasting tillage, residue mulch and nitrogen management on soil quality and system productivity under maize-wheat rotation in the north-western Indo-Gangetic Plains

Adak,

Bandyopadhyay,

Purakayastha

et al. 2023

Front. Sustain. Food Syst.

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The sustainability of dominant rice-wheat rotation is under threat due to numerous water-, nutrients-, weeds- and environment-related problems, mainly, due to rice cultivation in north-western Indo-Gangetic Plains (NWIGP) of India. It needs crop- and soil- appropriate management techniques with a focus on conservation agriculture (CA) that can maintain soil health which in turn is essential for long-term sustainability of intensive cereal-based systems. Thus, rice-wheat rotation may be diversified with maize as feasible substitute for rice. But, there is a dearth of comprehensive investigation on the impact of short-term CA in maize-wheat rotation, on soil quality. Hence, an attempt has been made to assess the system productivity (SP) and soil quality in a four-year-old CA-based maize-wheat rotation. Contrasting tillage as the main plot [Conventional tillage (CT), No–tillage (NT)], crop residue mulch as subplot [residue mulch (M+), no residue (M0)], and nitrogen [50 (N1), 100 (N2), 150% (N3) of recommended nitrogen dose] as sub-sub plot was laid out in split-split plot design. Soils sampled from 0–0.05, 0.05– 0.15, and 0.15–0.30 m soil layers were examined to develop a unified soil quality index (SQI) through principal component analysis (PCA) and expert opinion. The available K, P, total organic carbon (TOC), EC, bulk density (BD), dehydrogenase activity (DHA), and soil microbial biomass C (SMBC) were identified as the crucial minimum data set for SQI using PCA. Results showed that, NT and M+ plots had 10.52 and 17.39% higher mean weight diameter (MWD) than CT and M0, respectively at 0–0.05 m soil depth. NT and M+ plots increased TOC by 5.26 and 8% than CT and M0 plots, respectively in 0–0.05 m soil layer. Available K and P were found to be significantly higher in M+ plots than that of M0. NTM+ treatments improved SMBC and DHA than CTM0 treatments. The highest and lowest SQI was registered with NTM + N3 and CTM0N1, respectively. SP was significantly and positively correlated with SQI. Diversification of rice-wheat system with maize-wheat rotation following CA practices appears to have a positive impact on soil health. Therefore, CA-based maize-wheat rotation may be recommended to improve soil quality and system productivity in NWIGP region.

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Section: Maize-wheat System Productivitysupporting

confidence: 70%

Impact of contrasting tillage, residue mulch and nitrogen management on soil quality and system productivity under maize-wheat rotation in the north-western Indo-Gangetic Plains

Adak,

Bandyopadhyay,

Purakayastha

et al. 2023

Front. Sustain. Food Syst.

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“…The amplitude of the red edge peak decreases with the increase in severity levels. Fahrentrapp et al (2019) and Adak et al (2021) reported similar findings for gray mold leaf infections and nitrogen stress in wheat, respectively. The maximum rate of change value at REP is called red edge value (REV) which has good relation with stress levels.…”

Section: Discussionsupporting

confidence: 56%

Spectral characterization and severity assessment of rice blast disease using univariate and multivariate models

et al. 2023

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Rice is the staple food of more than half of the population of the world and India as well. One of the major constraints in rice production is frequent occurrence of pests and diseases and one of them is rice blast which often causes yield loss varying from 10 to 30%. Conventional approaches for disease assessment are time-consuming, expensive, and not real-time; alternately, sensor-based approach is rapid, non-invasive and can be scaled up in large areas with minimum time and effort. In the present study, hyperspectral remote sensing for the characterization and severity assessment of rice blast disease was exploited. Field experiments were conducted with 20 genotypes of rice having sensitive and resistant cultivars grown under upland and lowland conditions at Almora, Uttarakhand, India. The severity of the rice blast was graded from 0 to 9 in accordance to International Rice Research Institute (IRRI). Spectral observations in field were taken using a hand-held portable spectroradiometer in range of 350-2500 nm followed by spectral discrimination of different disease severity levels using Jeffires–Matusita (J-M) distance. Then, evaluation of 26 existing spectral indices (r≥0.8) was done corresponding to blast severity levels and linear regression prediction models were also developed. Further, the proposed ratio blast index (RBI) and normalized difference blast index (NDBI) were developed using all possible combinations of their correlations with severity level followed by their quantification to identify the best indices. Thereafter, multivariate models like support vector machine regression (SVM), partial least squares (PLS), random forest (RF), and multivariate adaptive regression spline (MARS) were also used to estimate blast severity. Jeffires–Matusita distance was separating almost all severity levels having values >1.92 except levels 4 and 5. The 26 prediction models were effective at predicting blast severity with R2 values from 0.48 to 0.85. The best developed spectral indices for rice blast were RBI (R1148, R1301) and NDBI (R1148, R1301) with R2 of 0.85 and 0.86, respectively. Among multivariate models, SVM was the best model with calibration R2=0.99; validation R2=0.94, RMSE=0.7, and RPD=4.10. The methodology developed paves way for early detection and large-scale monitoring and mapping using satellite remote sensors at farmers’ fields for developing better disease management options.

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“…Amplitude of score 0 and 9 was 0.00929 and 0.002301, respectively for upland land condition whereas the amplitude of the score 0 and 9 was 0.010421 and 0.00193, respectively for upland land rice (Table 3). Fahrentrapp et al (2019) and Adak et al (2021) reported similar findings for gray mold leaf infections and nitrogen stress in wheat, respectively. Max rate of change value at REP is called red edge value (REV) which has good relation with stress levels.…”

Section: Effect Of Disease Severity On Spectral Reflectance In Red Ed...supporting

confidence: 56%

Assessing rice blast disease severity through hyperspectral remote sensing

et al. 2022

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Remote sensing is being increasingly used in stress management in different agricultural practices. It is useful for real time analysis for crop stress which is not possible for visual observation alone. Rice blast caused by fungus Pyricularia Oryzae is a serious constrain in rice production in India. There is hardly any basic information available for spectral characteristics of rice blast disease for its real-time detection and management. Present study is to characterize spectral reflectance of blast affected rice in order to identify the sensitive spectral range. Disease severity of 10 different genotypes of rice was graded 0 to 9 based on the extent of host organ covered by symptom or lesion. Result shows that severely infected plant (score 9) have higher reflectance at visible region and lower reflectance at NIR region. Change in the reflectance for the infected plant as compare to the healthy plant was more pronounced in the VNIR, 550 to 760 nm and 1140 and 1300 nm having correlation coefficient above 0.6. The study of change in the reflectance with the change in wavelength (1st derivative) revealed that VNIR region have high correlation with the disease severity. Maximum rate of change value at red edge position (REP) is called as red edge value (REV) which has good relation with disease severity levels. Amplitude of the red edge peak decreases with the increase in severity levels. Amplitude of score 0 and 9 was 0.00929 and 0.002301, respectively for upland land condition whereas the amplitude of the score 0 and 9 was 0.010421 and 0.00193, respectively for upland land rice. This study identifies that VNIR and red edge region are sensitive for detecting rice blast, which could be utilized to aerial or satellite based monitoring blast affected rice cropping region.

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Prediction of Wheat Yield Using Spectral Reflectance Indices Under Different Tillage, Residue and Nitrogen Management Practices

Cited by 13 publications

References 0 publications

Impact of contrasting tillage, residue mulch and nitrogen management on soil quality and system productivity under maize-wheat rotation in the north-western Indo-Gangetic Plains

Impact of contrasting tillage, residue mulch and nitrogen management on soil quality and system productivity under maize-wheat rotation in the north-western Indo-Gangetic Plains

Spectral characterization and severity assessment of rice blast disease using univariate and multivariate models

Assessing rice blast disease severity through hyperspectral remote sensing

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