Papers by Sellaperumal Pazhanivelan
Agriculture
New agronomic opportunities for more informed agricultural decisions and enhanced crop management... more New agronomic opportunities for more informed agricultural decisions and enhanced crop management have been made possible by drone-based near-ground remote sensing. Obtaining precise non-destructive information regarding crop biophysical characteristics at spatial and temporal scales is now possible. Drone-mounted multispectral and thermal sensors were used to assess crop phenology, condition, and stress by profiling spectral vegetation indices in crop fields. In this study, vegetation indices, viz., Atmospherically Resistant Vegetation Index (ARVI), Modified Chlorophyll Absorption Ratio Index (MCARI), Wide Dynamic Range Vegetation Index (WDRVI), Normalized Red–Green Difference Index (NGRDI), Excess Green Index (ExG), Red–Green Blue Vegetation Index (RGBVI), and Visible Atmospherically Resistant Index (VARI) were generated. Furthermore, Pearson correlation analysis showed a better correlation between WDRVI and VARI with LAI (R = 0.955 and R = 0.982) ground truth data. In contrast, a...
International Journal of Environment and Climate Change
Crop cover mapping is an essential tool for controlling and enhancing agricultural productivity. ... more Crop cover mapping is an essential tool for controlling and enhancing agricultural productivity. By determining the spatial distribution of different crop types, solidified judgements regarding crop planning, crop management, and risk management can be made. Crop cover classification using optical data pose constraints in terms of spatial and spectral resolution. With Sentinel – 2 data providing the ground information at 10m resolution, users may choose the best spectral band combinations and temporal frame by analysing the spectral-temporal information of different crops. The crop categorization map for the Kallakurichi and Villupuram districts were created in this study using the Random Forest (RF) and Decision tree (C5.0) classifiers. The study mainly focuses on comparing the classification accuracy of two classifiers and figuring out the best classifiers for crop cover mapping with respect to the study area. The ground truth information collected, were partitioned into calibrati...
The Indian Journal of Agricultural Sciences
A field experiment was conducted at the Agricultural Research Station, Tamil Nadu Agricultural Un... more A field experiment was conducted at the Agricultural Research Station, Tamil Nadu Agricultural University, Bhavanisagar, during 2021–23 to study the effect of spray volume (SV) on deposition characteristics of a fuel-operated UAV sprayer (25 L/ha, 37.5 L/ha and 50 litre/ha) and knapsack sprayer (KS) (500 litre/ha) in the rice (Oryza sativa L.) field. Results showed that herbicides spraying using UAV (37.5 litre/ha) had a higher droplet deposition (0.077 and 0.075 μL/cm2) than knapsack spraying of 500 litre/ha (0.06 and 0.049 μL/cm2) in the ground layer of first (PE) and second (PoE) spraying, respectively. KS (500 litre/ha) had significantly higher droplet coverage rate, droplet size (Dv0.5) over other UAV spray volumes. Subsequently, variation in spray uniformity was found between two sprayers. Among UAV spray volumes, application of 50 litre/ha had better deposition, coverage rate and number of spray deposits/cm2 compared to UAV (37.5 litre/ha), with no significant difference betw...
International Journal of Plant & Soil Science
In modern crop production, essential factors that contribute to narrowing yield gaps and minimizi... more In modern crop production, essential factors that contribute to narrowing yield gaps and minimizing production costs include making informed decisions about the selection of plant varieties, determining optimal sowing dates, determining appropriate plant populations, selecting suitable fertilizer rates, and implementing effective pest control methods. Two field experiments were conducted during the Rabi seasons of 2021 and 2022 at ICAR-Indian Institute of Pulses Research (IIPR), Kanpur using split-plot experimental design, where the main plots were three different sowing dates (20-25th October, November 10-15th, and 25th November-5th December), and the sub-plots were four chickpea cultivars (JG 16, RVG 202, IPC-07-66, and IPC-05-62), each with three replications. The genetic coefficients of the cultivars were estimated using both the iterative process (IP) and Generalized Likelihood Uncertainty Estimation (GLUE) methods in DSSAT v 4.7 to simulate the yields. Upon model validation, i...
Agronomy
Crop yield data are critical for managing agricultural sustainability and assessing national food... more Crop yield data are critical for managing agricultural sustainability and assessing national food security. This study aims at increasing peanut productivity from its current levels by analyzing the yield gap (difference) of potential production between theoretical yield and actual farmers’ yields. The spatial yield gap of peanut for the Tiruvannamalai district of Tamil Nadu is examined in this investigation by integrating the products of microwave remote sensing (SAR Sentinel-1A) with the DSSAT CROPGRO Peanut simulation model. The CROPGRO (crop growth) Peanut model was calibrated and validated by conducting a field experiment at Oilseeds Research Station, Tindivanam during Rabi (spring) 2019 for predominant cultivars, i.e., TMV 7, TMV 13, VRI 2 and G 7. Actual attainable yield was recorded by organizing crop cutting experiments (CCEs) with the help of the Department of Agriculture Economics and Statistics in the respective monitoring villages. The regression analysis between the ma...
Land
The soil–environmental relationship identified and standardised over the years has expedited the ... more The soil–environmental relationship identified and standardised over the years has expedited the growth of digital soil-mapping techniques; hence, various machine learning algorithms are involved in predicting soil attributes. Therefore, comparing the different machine learning algorithms is essential to provide insights into the performance of the different algorithms in predicting soil information for Indian landscapes. In this study, we compared a suite of six machine learning algorithms to predict quantitative (Cubist, decision tree, k-NN, multiple linear regression, random forest, support vector regression) and qualitative (C5.0, k-NN, multinomial logistic regression, naïve Bayes, random forest, support vector machine) soil information separately at a regional level. The soil information, including the quantitative (pH, OC, and CEC) and qualitative (order, suborder, and great group) attributes, were extracted from the legacy soil maps using stratified random sampling procedures...
Agriculture
Smart farming is a development that has emphasized information and communication technology used ... more Smart farming is a development that has emphasized information and communication technology used in machinery, equipment, and sensors in network-based hi-tech farm supervision cycles. Innovative technologies, the Internet of Things (IoT), and cloud computing are anticipated to inspire growth and initiate the use of robots and artificial intelligence in farming. Such ground-breaking deviations are unsettling current agriculture approaches, while also presenting a range of challenges. This paper investigates the tools and equipment used in applications of wireless sensors in IoT agriculture, and the anticipated challenges faced when merging technology with conventional farming activities. Furthermore, this technical knowledge is helpful to growers during crop periods from sowing to harvest; and applications in both packing and transport are also investigated.
Agronomy
Accurate and consistent information on the area and production of field crops is vital for nation... more Accurate and consistent information on the area and production of field crops is vital for national and state planning and ensuring food security in India. Satellite-based remote sensing offers a suitable and cost-effective technique for regional- and national-scale crop monitoring. The use of remote sensing data for crop yield estimation has been demonstrated using a semi-physical approach with reasonable success. Assimilating remote sensing data with the DSSAT model and spectral indices-based regression analysis are promising methods for spatially estimating rice crop yields. Rice area and yield in the Cauvery delta zone of Tamil Nadu, India was estimated during samba (August–January) season in the years 2020–2021 using Sentinel 1A Synthetic Aperture Radar satellite data with three different spatial yield estimation methods, namely a spectral indices-based regression analysis, semi-physical approach, and integrating remote products with DSSAT crop growth model. A rice area map was...
Monitoring of Meteorological Drought Based on Rainfall Departure Using Remotely Sensed CHIRPS Precipitation Product over Tamil Nadu, India
Anthropogeomorphology, 2022
Rice is the most important food security crop in Asia. Information on its seasonal extent forms p... more Rice is the most important food security crop in Asia. Information on its seasonal extent forms part of the national accounting of many Asian countries. Synthetic Aperture Radar (SAR) imagery is highly suitable for detecting lowland rice, especially in tropical and subtropical regions, where pervasive cloud cover in the rainy seasons precludes the use of optical imagery. Here, we present a simple, robust, rule-based classification for mapping rice area with regularly acquired, multi-temporal, X-band, HH-polarized SAR imagery and site-specific parameters for classification. The rules for rice detection are based on the well-studied temporal signature of rice from SAR backscatter and its relationship with crop stages. We also present a procedure for estimating the parameters based on "temporal feature descriptors" that concisely characterize the key information in the rice signatures in monitored field locations within each site. We demonstrate the robustness of the approach on a very large dataset. A total of 127 images across 13 footprints in six countries in Asia were obtained between October 2012, and April 2014, covering 4.78 m ha. More than 1900 in-season site visits were conducted across 228 monitoring locations in the footprints for classification purposes, and more than 1300 field observations were made for accuracy assessment. Some 1.6 m ha of rice were mapped with classification accuracies from 85% to 95% based on the parameters that were closely related to the observed temporal feature descriptors derived for Remote Sens. 2014, 6 10775 each site. The 13 sites capture much of the diversity in water management, crop establishment and maturity in South and Southeast Asia. The study demonstrates the feasibility of rice detection at the national scale using multi-temporal SAR imagery with robust classification methods and parameters that are based on the knowledge of the temporal dynamics of the rice crop. We highlight the need for the development of an open-access library of temporal signatures, further investigation into temporal feature descriptors and better ancillary data to reduce the risk of misclassification with surfaces that have temporal backscatter dynamics similar to those of rice. We conclude with observations on the need to define appropriate SAR acquisition plans to support policies and decisions related to food security.
Remote Sensing of Environment, 2017
Agricultural monitoring systems require spatio-temporal information on widely cultivated staple c... more Agricultural monitoring systems require spatio-temporal information on widely cultivated staple crops like rice. More emphasis has been made on area estimation and crop detection than on the temporal aspects of crop cultivation, but seasonal and temporal information such as i) crop duration, ii) date of crop establishment and iii) cropping intensity are as important as area for understanding crop production. Rice cropping systems are diverse because genetic, environmental and management factors (GxExM combinations) influence the spatio-temporal patterns of cultivation. We present a rule based algorithm called PhenoRice for automatic extraction of temporal information on the rice crop using moderate resolution hypertemporal optical imagery from MODIS. Performance of PhenoRice against spatially and temporally explicit reference information was tested in three diverse sites: rice-fallow (Italy), rice-other crop (India) and rice-rice (Philippines) systems. Regional product accuracy assessments showed that PhenoRice made a conservative, spatially representative and robust detection of rice cultivation in all sites (r 2 between 0.75 and 0.92) and crop establishment dates were in close agreement with the reference data (r 2 = 0.98, Mean Error = 4.07 days, Mean Absolute Error = 9.95 days, p < 0.01). Variability in algorithm performance in different conditions in each site (irrigated vs rainfed, direct seeding vs transplanting, fragmented vs clustered rice landscapes and the impact of cloud contamination) was analysed and discussed. Analysis of the maps revealed that cropping intensity and season length per site matched well with local information on agro-practices and cultivated varieties. The results show that PhenoRice is robust for deriving essential temporal descriptions of rice systems in both temperate and tropical regions at a level of spatial and temporal detail that is suitable for regional crop monitoring on a seasonal basis. This work is licensed under a Creative Commons "Attribution-NonCommercial-NoDerivatives 4.0 International" license.
Remote Sensing, 2014
Rice is the most important food security crop in Asia. Information on its seasonal extent forms p... more Rice is the most important food security crop in Asia. Information on its seasonal extent forms part of the national accounting of many Asian countries. Synthetic Aperture Radar (SAR) imagery is highly suitable for detecting lowland rice, especially in tropical and subtropical regions, where pervasive cloud cover in the rainy seasons precludes the use of optical imagery. Here, we present a simple, robust, rule-based classification for mapping rice area with regularly acquired, multi-temporal, X-band, HH-polarized SAR imagery and site-specific parameters for classification. The rules for rice detection are based on the well-studied temporal signature of rice from SAR backscatter and its relationship with crop stages. We also present a procedure for estimating the parameters based on "temporal feature descriptors" that concisely characterize the key information in the rice signatures in monitored field locations within each site. We demonstrate the robustness of the approach on a very large dataset. A total of 127 images across 13 footprints in six countries in Asia were obtained between October 2012, and April 2014, covering 4.78 m ha. More than 1900 in-season site visits were conducted across 228 monitoring locations in the footprints for classification purposes, and more than 1300 field observations were made for accuracy assessment. Some 1.6 m ha of rice were mapped with classification accuracies from 85% to 95% based on the parameters that were closely related to the observed temporal feature descriptors derived for Remote Sens. 2014, 6 10775 each site. The 13 sites capture much of the diversity in water management, crop establishment and maturity in South and Southeast Asia. The study demonstrates the feasibility of rice detection at the national scale using multi-temporal SAR imagery with robust classification methods and parameters that are based on the knowledge of the temporal dynamics of the rice crop. We highlight the need for the development of an open-access library of temporal signatures, further investigation into temporal feature descriptors and better ancillary data to reduce the risk of misclassification with surfaces that have temporal backscatter dynamics similar to those of rice. We conclude with observations on the need to define appropriate SAR acquisition plans to support policies and decisions related to food security.
Water
The prevalence of the frequent water stress conditions at present was found to be more frequent d... more The prevalence of the frequent water stress conditions at present was found to be more frequent due to increased weather anomalies and climate change scenarios, among other reasons. Periodic drought assessment and subsequent management are essential in effectively utilizing and managing water resources. For effective drought monitoring/assessment, satellite-based precipitation products offer more reliable rainfall estimates with higher accuracy and spatial coverage than conventional rain gauge data. The present study on satellite-based drought monitoring and reliability evaluation was conducted using four high-resolution precipitation products, i.e., IMERGH, TRMM, CHIRPS, and PERSIANN, during the northeast monsoon season of 2015, 2016, and 2017 in the state of Tamil Nadu, India. These four precipitation products were evaluated for accuracy and confidence level by assessing the meteorological drought using standard precipitation index (SPI) and by comparing the results with automatic...
A field experiment was conducted at Agricultural College and Research Institute Farm, Trichy in a... more A field experiment was conducted at Agricultural College and Research Institute Farm, Trichy in an alkali soil (EC 0.18 dSm , pH 8.65 and ESP 25.6) receiving an average annual rainfall of 754 mm. -1 Tamarind (Tamarindus indicus) seedlings were planted during 1999. Three planting techniques viz., pit system (0.6 x 0.6 x 0.6 m), pit with auger hole (0.30 m dia, 0. 60 m deep) and pit with auger hole (0.30 m dia,1.20 m deep) were fitted in the main plot and three amendments viz., gypsum @ 50 % gypsum requirement (GR), distillery spent wash @ 150 ml kg of soil, gypsum at 25% GR + 50% DSW 75 ml kg -1 -1 of soil were assigned to sub plots. The experiment was conducted in a split plot design and replicated four times. The results revealed that pit with augur hole for 120 cm deep among the planting methods and combined application of gypsum @ 25 % GR and DSW @ 75 ml Kg of excavated soil recorded better -1 growth in terms of survival per cent, tree height , GSH and GBH by reducing soil pH and...
Influence of Increased Plant Density and Fertilizer Levels on Physiological Parameters and Yield of Greengram (Vigna radiata (L.) Wilczek)
Field experiments were conducted during kharif 2002, rabi 2002 and summer 2003 at the College of ... more Field experiments were conducted during kharif 2002, rabi 2002 and summer 2003 at the College of Agricultural Engineering, Kumulur, Tiruchirappalli district of Tamil Nadu to study the effect of increased plant density and nutrient management on the physiological parameters and yield of 12 3 greengram. Three inter row spacings of 20 cm (S), 25 cm (S) and 30 cm (S) with a constant intra row spacing of 10 cm accommodating 5.0, 4.0 and 3.33 lakh plants ha were tried in the main plot. -1 11 The treatments tried in sub plot were recommended N and P (N), N with foliar spraying of one per cent 21 2 sulphate of potash (SOP) (N), N with soil application of 25 kg K O ha as muriate of potash (MOP) -1 34 (N), 125 per cent N and P with foliar spraying of one per cent SOP (N), 150 per cent N and P with 5 foliar spraying of one per cent SOP (N) and 50 per cent N and P with foliar spraying of two per cent 6 Diammonium phosphate (DAP) and one per cent SOP (N). The treatments were fitted in a split pl...
International Journal of Agricultural Research, 2006
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015
Rice is the most important cereal crop governing food security in Asia. Reliable and regular info... more Rice is the most important cereal crop governing food security in Asia. Reliable and regular information on the area under rice production is the basis of policy decisions related to imports, exports and prices which directly affect food security. Recent and planned launches of SAR sensors coupled with automated processing can provide sustainable solutions to the challenges on mapping and monitoring rice systems. High resolution (3m) Synthetic Aperture Radar (SAR) imageries were used to map and monitor rice growing areas in selected three sites in TamilNadu, India to determine rice cropping extent, track rice growth and estimate yields. A simple, robust, rule-based classification for mapping rice area with multi-temporal, X-band, HH polarized SAR imagery from COSMO Skymed and TerraSAR X and site specific parameters were used. The robustness of the approach is demonstrated on a very large dataset involving 30 images across 3 footprints obtained during 2013-14. A total of 318 in-seaso...
An operation remote sensing based service for rice production estimation at national scale
One goal of the Remote Sensing based Information and Insurance for Crops in emerging Economies (R... more One goal of the Remote Sensing based Information and Insurance for Crops in emerging Economies (RIICE) project is to estimate, on an operational basis, rice production at national scale in primis targeted to food security and crop insurance purposes. There are two unique elements to this proposed service: 1. Multi-year, annual, and seasonal SAR data are acquired from all existing operational spaceborne systems are used and complemented by MODIS 250/500 m 16-/8-days composite data. This solution: − overcomes the spatial-temporal problem, hence assuring an appropriate temporal repetition at an adequate scale (i.e. spatial resolution) even over large areas; − provides sensor independent operational monitoring with sufficient data redundancy to ensure information delivery. 2. A crop growth simulation model estimates yield and hence production using dedicated remote sensing products in addition to the usual meteorological, soil, and plant parameters. This remote sensing-crop model approa...
Influence of Organic Manures on the Nutrient Uptake and Soil Fertility of Cassava (Manihot esculenta Crantz.) Intercropping Systems
International Journal of Agricultural Research, 2007
... The application of organic manure increased soil available N (Venkateswara Rao, 1985), soil a... more ... The application of organic manure increased soil available N (Venkateswara Rao, 1985), soil available P (Yadav et al., 1991) whereas available NPK declined in no organic manured plot (Rajendra Prasad and Goswami, 1992). ...
Journal of Agronomy, 2006
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Papers by Sellaperumal Pazhanivelan