Prasuna Rani Podila
@angrau.ac.in
Principal Scientist, Saline Water Scheme, ANGRAU, Bapatla
Registrar, Acharya NG Ranga Agril. University
EDUCATION
Ph.D in Soil Science
RESEARCH INTERESTS
Soil Taxonomy, Land evaluation, Geospatial technology for soil studies, soil fertility, management of problem soils and water
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Sunil Kumar Medida, P. Prasuna Rani, G.V. Suneel Kumar, P.V. Geetha Sireesha, K.C. Kranthi, V. Vinusha, L. Sneha, B.S.S.S. Naik, Biswajit Pramanick, Marian Brestic,et al.
Elsevier BV
P. Prasuna Rani, , M. Sunil Kumar, P.V. Geetha Sireesha, , and
Triveni Enterprises
Aim: To evaluate spectral indices as tools for separation of active aquaponds filled with water and engaged in shrimp/fish production from empty aquaponds using Landsat -8 data in coastal region of Guntur district, Andhra Pradesh. Methodology: The active and empty aquaponds were demarcated with Landsat satellite (Landsat-8) Operational Land Imager’s (OLI) multispectral images using maximum likelihood classifier (MLC) algorithm and spectral indices like Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Water Ratio Index (WRI) and Automated Water Extraction Index (AWEInsh) by means of thresholds. Results: The supervised classification using maximum likelyhood classifier recorded the highest active aquapond area whereas; NDWI, combination of indices and WRI resulted in lower but almost similar extents. Evaluation of confusion matrix using validation points revealed that NDWI, WRI and combination of indices resulted in all most perfect agreement with a kappa value of more than 0.9. Maximum likelihood classifier, NDVI and MNDWI could separate active ponds and empty ponds from other land uses with strong agreement, while AWEInsh could separate different land uses only with moderate agreement. Interpretation: The study indicates that spectral indices like NDWI, WRI and combination of indices are able to delineate aquaponds that were cultured for shrimp/fish and kept empty at a given time with noticeably high accuracy using satellite data for better managing of resources in coastal ecosystem.
Anjali bhadra Vijay and P Prasuna Rani
Diva Enterprises Private Limited
G. G. Ponnurangam, T. D. Setiyono, A. Maunahan, S. S. Satapathy, E. Quicho, L. Gatti, G. Romuga, C. Garcia, P. Prasadini, M. S. Kumar,et al.
Copernicus GmbH
<p><strong>Abstract.</strong> Mapping the extent of damage due to natural calamities remains one of the thrust areas in monitoring resource inventory through geo-spatial techniques. The effect of the cyclone ‘Titli’ and heavy rains during first fortnight of October 2018 in Srikakulam district, Andhra Pradesh State has been demonstrated using geo-spatial technology in terms of flood inundated rice area and corresponding yield and production loss. The pre- and post-cyclone (5 and 13 October 2018) flood inundation maps were generated using Sentinel-1A and TerraSAR-X Synthetic Aperture Radar (SAR) data respectively. The pre-cyclone rice area estimates were derived from multi-temporal Sentinel-1A SAR data, while yield forecast is based on the combination of satellite observations and yield simulation using ORYZA crop growth model. An intensive ground truth data collection had been carried out for the validation of satellite-derived rice area estimation of pre-cyclone event. An accuracy assessment has been carried out for district, mandal and village level. An overall accuracy of 96% with kappa coefficient 0.92 has been achieved. With the help map flood inundation and rice area maps, mandal-wise flood affected rice area and corresponding yield loss have been estimated. The post-cyclone ground truth data had been collected for quantitative assessment of crop damaged area. An overall accuracy of the flood affected rice map was 85% with kappa coefficient 0.70. It was estimated that rice crop damage assessment with SAR data indicated 53312 ha out of 205174 ha were affected and corresponding estimated yield as well as production are 0.8 t/ha and 189160 t respectively.</p>
N. Veronica, Y. Asoka Rani, D. Subrahmanyam, K. L. Narasimha Rao, M. Lal Ahamad, and P. Prasuna Rani
Gaurav Publications
Rice is the staple food crop and is the livelihood for most of the people across the globe. Keeping the present climate change scenario in view, there is a severe threat due to rise in temperature that can affect rice yield potential. Heat stress is one of the major abiotic stresses hampering the growth of rice. Temperature at every growth stage plays a critical role in deciding the rice yields. The major effects of heat stress in rice on its morphoagronomical parameters include reduced germination, poor seedling growth, reduction in plant height and tillering, reduction in number of pollen grains, poor anther dehiscence, increased sterility, reduced grain filling and poor grain quality that ultimately lead to yield reduction. From the physiological point of view, there is an inhibition of photosynthesis and related gas exchange traits, reduction in chlorophyll content and other pigments, reduction in chlorophyll fluorescence (Fv/Fm), reduction in cell membrane thermostability as well as an imbalance between photosynthesis and respiration. Biochemically, there is an increase in accumulation of osmoprotectants (praline and glycine betaine), increase in activity of antioxidants and increase in hormone accumulation (abscisic acid and ethylene). A complete understanding of mechanisms conferring thermotolerance and identification of genotypes possessing tolerance is the pre-requisite.