G. Gururaja Rao

Central Research Institute for Dryland Agriculture

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Anil R. Chinchmalatpure

Central Soil Salinity Research Institute

A. K. Nayak

Central Rice Research Institute

Y. S. Ramakrishna

ICAR - Central Island Agricultural Research Institute

V. U. M. Rao

Acharya Nagarjuna University

A. V. M. Subba Rao

Central Research Institute for Dryland Agriculture

M. K. Khandelwal

University of Petroleum and Energy Studies

Sanjay Arora

Central Soil Salinity Research Institute

B. V. Ramana Rao

Central Research Institute for Dryland Agriculture

A. S. R. A. S. Sastri

Indira Gandhi Agricultural University

Y. S. Rama Krishna

Amrita Institute of Medical Sciences and Research Centre

Cooperative Institutions

Central Research Institute for Dryland Agriculture

Indian Council of Agricultural Research

Central Soil Salinity Research Institute

Indian Agricultural Research Institute

Central Arid Zone Research Institute

Andhra University

International Crops Research Institute for the Semi-Arid Tropics

Tamil Nadu Agricultural University

Punjab Agricultural University

National Bureau of Soil Survey and Land Use Planning

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Influence of environmental variables on canopy- air temperature in castor beans (Ricinus communis L.) under low and high moisture regimes

Journal of Agrometeorology (2005)

Praveen Kumar Y. S. Ramakrishna N. N. SRIVASTAVA U.S. Victor G. Gururaja Rao

Castor beans

10.54386/jam.v7i1.809

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Advance estimation of rice production in India using weather indices

Zenodo (CERN European Organization for Nuclear Research) (2003)

G. Nageswara Rao Y. S. Ramakrishna A V R K Rao G. Gururaja Rao

Estimation of crop production from area and yield estimates based on sample surveys and crop-cutting experiments, an approach currently being followed in India, can give final estimates only after the crops are actually harvested. However, various policy decisions related to pricing, marketing, export/import, distribution, etc., necessitate the use of advance estimates. A simple model based on weather indices can be used to obtain accurate estimates of annual rice production even before the crop is harvested. Crop production in India largely depends on the summer monsoon (June to September), which provides about 80–90% of annual rainfall in most parts of the country. The summer monsoon rainfall is the main source of water for the kharif crop. Rainwater stored as soil moisture and other water resources (lakes, reservoirs, and rivers) are also important for the– rabi– and other irrigated crops. Parthasarathy et al (1988) have estimated the annual food-grain production in the country using the all-India summer monsoon rainfall data. The rainfall data, however, showed significant variations in time and space. To obtain more accurate production estimates, the temporal and spatial variations of monsoon rainfall were also included in the model through suitable weather indices.

10.5281/zenodo.6823688

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Microclimatic studies of grasslands in the arid zone of north-west India

Annals of Arid Zone (1989)

G. Gururaja Rao A. S. R. A. S. Sastri A. Krishnan

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Use of remote sensing for drought stress monitoring, yield prediction and varietal evaluation in castor beans (Ricinus communisL.)

International Journal of Remote Sensing (2005)

Praveen Kumar Y. S. Ramakrishna D. V. Bhaskara Rao G. Sridhar G. Srinivasa Rao

The current study was taken up to investigate the utility of remote sensing tools like infrared thermometer and spectral radiometer for screening of germplasm, stress monitoring and yield prediction in castor beans (Ricinus communis L.). The study was carried out through field experiments conducted for six years (1994–1999) at Hayatnagar Research Farm, Hyderabad, India. In each year, four cultivars of castor beans, viz. VP‐1, 48‐1, GCH‐4 and Aruna, were planted on two different dates maintaining an interval of 6–8 weeks so as to expose the crop to different environments. The infrared thermometric observations like canopy–air temperature differential (T c–T a) explained 50–60% variation in soil moisture status and showed a significant relationship with soil moisture. Yield of castor beans exhibited significant inverse relationship with T c–T a, which explained 59% of variation in yield. The hybrid GCH‐4, registering comparatively lesser mean T c–T a over the entire growing period, established itself as a better cultivar. The spectrometer observations also proved GCH‐4 to be a superior genotype in view of its higher reflectance in near‐infrared region of the spectrum. The significant negative relationship of T c–T a of GCH‐4 with saturation vapour pressure deficit brought out its drought tolerance trait over the other genotypes studied. These findings at field level can be extended to wider spatial level using satellite imageries.

Germ plasm

10.1080/01431160500285258

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Impact Assessment of Aniline Plant Treated Effluent Irrigation in Vertisols Surrounding Bharuch

Journal of the Indian Society of Soil Science (2014)

Anil R. Chinchmalatpure G. Gururaja Rao Sanjay Arora M. K. Khandelwal Divakar Sharma

Vertisol

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Temperature trends in different regions of India

Journal of Agrometeorology (2010)

A. V. M. Subba Rao P. SANTHI BHUSAN CHOWDARY N. Manikandan G. Gururaja Rao V. U. M. Rao

Time series analysis of annual mean, maximum and minimum temperature revealed of 47 stations spread acress different regions in India revealed the increasing trend in maximum temperature, lowest in 20 per cent stations in north zone and highest in 75 percent of the stations in south zone. On the other hand, increase in minimum temperature is observed in above 60 per cent of stations over all zones of India. Same trend is noticed in average temperature trend except in north zone where 45 per cent of stations have shown increasing trend.

Trend analysis

Maximum temperature

Mean radiant temperature

10.54386/jam.v12i2.1302

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Conjunctive use of surface water for dill (Anethum graveolens) cultivation in salt-affected black soils with saline ground water*

The Indian Journal of Agricultural Sciences (2000)

A. K. Nayak G. Gururaja Rao Anil R. Chinchmalatpure

Anethum graveolens

Salt water

Saline water

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Development of prediction models for bacterial leaf blight (Xanthomonas axonopodis pv malvacearum) of cotton (Gossypium hirsutum) in Andhra Pradesh and Maharashtra

The Indian Journal of Agricultural Sciences (2007)

Y. G. Prasad T. J. Nagalakshmi M. Prabhakar D. Y. lla Reddy N.H. Rao

Historical data on bacterial leaf blight disease incidence was analyzed vis-a-vis corresponding weather for identification of conducive weather conditions for disease development at three important cotton-growing locations situated in Andhra Pradesh and Maharashtra. Bacterial leaf blight incidence showed significant negative correlation with minimum temperature at all the three locations. Significant positive correlation was observed with rainfall and number of rainy days at Guntur. Multiple regression analysis between disease incidence (initiation to peak data) and weather variables yielded location-specific models for disease prediction one week in advance. Co-efficient of determination was lowest (57%) when input weather variables were simple weekly averages and improved when moving averages were introduced (61%) and was highest (92%) when preceding disease incidence level was included in the model for Guntur. However, simple weekly averages of significant weather variables along with previous week's disease level resulted in equations that explained 78% and 70% variation in disease incidence for Parbhani and Akola, respectively. Validation of the equations with independent data sets led to the identification of the best-fit model for each location based on chi-square test for goodness of fit. The utility of location-specific models is discussed.

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Stomatal characteristics, endogenous cytokinins, and absicic acid - like inhibitors in pegeon pea and gingelley leaves under NaCl salinity

Turrialba (1985)

G. Gururaja Rao G. R. K. Rao

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Water Management — Water Use in Rainfed Regions of India

Springer eBooks (2008)

Y. S. Ramakrishna G. Gururaja Rao V. U. M. Rao A. V. M. Subba Rao K. V. Rao

Water use

10.1007/978-3-540-72746-0_15

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Citations (3)