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Article: Criteria based decisions for determining agroclimatic onset of the crop growing season

Bal, Santanu Kumar / Manikandan, N. / Sandeep, V.M. / Vijaya Kumar, P. / Lunagaria, M.M. / Subba Rao, A.V.M. / Pramod, V.P. / Singh, V.K.

Agricultural and forest meteorology. 2022 Apr. 15, v. 317

2022

Abstract: Success of rainfed crop production is highly dependent on timely sowing/planting decisions. Variability in sowing/planting dates between years affect crop planning and thus could decrease farm profitability. Therefore, information on the optimum crop ... ...

Abstract	Success of rainfed crop production is highly dependent on timely sowing/planting decisions. Variability in sowing/planting dates between years affect crop planning and thus could decrease farm profitability. Therefore, information on the optimum crop sowing window for the season will facilitate crop planning by farmers and other stakeholders. To determine optimum sowing window over 19 Agro-Ecological Regions (AER) of India, three methods viz., Soil Water Balance (SWB), Depth and modified Morris & Zandesta methods were evaluated to identify the most suitable method for working out the onset dates of the crop growing season. The onset dates of growing season determined by three methods were found to be similar over northeastern (hot sub-humid and warm per-humid eco-region), west coast (hot humid to per-humid), cold and hot arid eco-regions in India. However, differences in onset dates of the crop growing season were observed over hot semi-arid to sub-humid eco-region. SWB method was found to be the most suitable based on validating with observed crop sowing dates, false start and number of undefined onset years criteria. However, as SWB method is data-intensive, onset was determined using an alternative Modified Threshold Combination (MTC) method comprising 40 combinations of threshold values viz. rainfall amount, wet spell duration, dry spell duration and dry spell search period. The onset dates determined by MTC and SWB methods were validated and subsequently, appropriate threshold values were identified to work out onset dates in 19 AERs of India. This study revealed that the onset is not influenced by threshold combinations in per-humid, humid and sub-humid regions. However, in semi-arid and arid regions, critical evaluation of criteria for determining onset is vital to avoid false starts and undefined onset years. Information on agroclimatic onset dates for each AER is useful for improving practical utility/decision making, especially in the semi-arid and arid regions of India.
Keywords	coasts ; cold ; crop production ; ecoregions ; farm profitability ; forests ; meteorology ; rain ; soil water balance ; stakeholders ; India
Language	English
Dates of publication	2022-0415
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	409905-9
ISSN	0168-1923
ISSN	0168-1923
DOI	10.1016/j.agrformet.2022.108903
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Identifying appropriate prediction models for estimating hourly temperature over diverse agro-ecological regions of India.

Bal, Santanu Kumar / Pramod, V P / Sandeep, V M / Manikandan, N / Sarath Chandran, M A / Subba Rao, A V M / Vijaya Kumar, P / Vanaja, M / Singh, V K

Scientific reports

2023 Volume 13, Issue 1, Page(s) 7789

Abstract: The present study tests the accuracy of four models in estimating the hourly air temperatures in different agroecological regions of the country during two major crop seasons, kharif and rabi, by taking daily maximum and minimum temperatures as input. ... ...

Abstract	The present study tests the accuracy of four models in estimating the hourly air temperatures in different agroecological regions of the country during two major crop seasons, kharif and rabi, by taking daily maximum and minimum temperatures as input. These methods that are being used in different crop growth simulation models were selected from the literature. To adjust the biases of estimated hourly temperature, three bias correction methods (Linear regression, Linear scaling and Quantile mapping) were used. When compared with the observed data, the estimated hourly temperature, after bias correction, is reasonably close to the observed during both kharif and rabi seasons. The bias-corrected Soygro model exhibited its good performance at 14 locations, followed by the WAVE model and Temperature models at 8 and 6 locations, respectively during the kharif season. In the case of rabi season, the bias-corrected Temperature model appears to be accurate at more locations (21), followed by WAVE and Soygro models at 4 and 2 locations, respectively. The pooled data analysis showed the least error between estimated (uncorrected and bias-corrected) and observed hourly temperature from 04 to 08 h during kharif season while it was 03 to 08 h during the rabi season. The results of the present study indicated that Soygro and Temperature models estimated hourly temperature with better accuracy at a majority of the locations situated in the agroecological regions representing different climates and soil types. Though the WAVE model worked well at some of the locations, estimation by the PL model was not up to the mark in both kharif and rabi seasons. Hence, Soygro and Temperature models can be used to estimate hourly temperature data during both kharif and rabi seasons, after the bias correction by the Linear Regression method. We believe that the application of the study would facilitate the usage of hourly temperature data instead of daily data which in turn improves the precision in predicting phenological events and bud dormancy breaks, chilling hour requirement etc.
Language	English
Publishing date	2023-05-13
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-34194-9
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Article ; Online: Pest scenario of Helicoverpa armigera (Hub.) on pigeonpea during future climate change periods under RCP based projections in India.

Srinivasa Rao, M / Rama Rao, C A / Raju, B M K / Subba Rao, A V M / Gayatri, D L A / Islam, Adlul / Prasad, T V / Navya, M / Srinivas, K / Pratibha, G / Srinivas, I / Prabhakar, M / Yadav, S K / Bhaskar, S / Singh, V K / Chaudhari, S K

Scientific reports

2023 Volume 13, Issue 1, Page(s) 6788

Abstract: Gram pod borer, Helicoverpa armigera (Hub.) is the major insect pest of pigeonpea and prediction of number of generations (no. of gen.) and generation time (gen. time) using growing degree days (GDD) approach during three future climate change periods ... ...

Abstract	Gram pod borer, Helicoverpa armigera (Hub.) is the major insect pest of pigeonpea and prediction of number of generations (no. of gen.) and generation time (gen. time) using growing degree days (GDD) approach during three future climate change periods viz., Near (NP), Distant (DP) and Far Distant (FDP) periods at eleven major pigeonpea growing locations of India was attempted. Multi-model ensemble of Maximum (Tmax) and Minimum (Tmin) temperature data of four Representative Concentration Pathways viz., RCP 2.6, 4.5, 6.0 and 8.5 of Coupled Model Inter comparison Project 5 (CMIP5) models was adopted here. The increase in projected Tmax and Tmin are significant during 3 climate change periods (CCPs) viz., the NP, DP and FDP over base line (BL) period under four RCP scenarios at all locations and would be higher (4.7-5.1 °C) in RCP 8.5 and in FDP. More number of annual (10-17) and seasonal (5-8) gens. are expected to occur with greater percent increase in FDP (8 to 38%) over base line followed by DP (7 to 22%) and NP (5to 10%) periods with shortened annual gen. time (4 to 27%) across 4 RCPs. The reduction of crop duration was substantial in short, medium and long duration pigeonpeas at all locations across 4 RCPs and 3 CCPs. The seasonal no.of gen. is expected to increase (5 to 35%) with shortened gen. time (4 to 26%) even with reduced crop duration across DP and FDP climate periods of 6.0 and 8.5 RCPs in LD pigeonpea. More no. of gen. of H. armigera with reduced gen. time are expected to occur at Ludhiana, Coimbatore, Mohanpur, Warangal and Akola locations over BL period in 4 RCPs when normal duration of pigeonpeas is considered. Geographical location (66 to 72%), climate period (11 to 19%), RCPs (5-7%) and their interaction (0.04-1%) is vital and together explained more than 90% of the total variation in future pest scenario. The findings indicate that the incidence of H. armigera would be higher on pigeonpea during ensuing CCPs in India under global warming context.
MeSH term(s)	Animals ; Climate Change ; Moths ; Global Warming ; Temperature ; India
Language	English
Publishing date	2023-04-26
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-32188-1
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Article ; Online: Evaluating area-specific adaptation strategies for rainfed maize under future climates of India.

Subba Rao, A V M / Sarath Chandran, M A / Bal, Santanu Kumar / Pramod, V P / Sandeep, V M / Manikandan, N / Raju, B M K / Prabhakar, M / Islam, Adlul / Naresh Kumar, S / Singh, V K

The Science of the total environment

2022 Volume 836, Page(s) 155511

Abstract: This study investigates the spatio-temporal changes in maize yield under projected climate and identified the potential adaptation measures to reduce the negative impact. Future climate data derived from 30 general circulation models were used to assess ... ...

Abstract	This study investigates the spatio-temporal changes in maize yield under projected climate and identified the potential adaptation measures to reduce the negative impact. Future climate data derived from 30 general circulation models were used to assess the impact of future climate on yield in 16 major maize growing districts of India. DSSAT model was used to simulate maize yield and evaluate adaptation strategies during mid (2040-69) and end-centuries (2070-99) under RCP 4.5 and 8.5. Genetic coefficients were calibrated and validated for each of the study locations. The projected climate indicated a substantial increase in mean seasonal maximum (0.9-6.0 °C) and minimum temperatures (1.1-6.1 °C) in the future (the range denotes the lowest and highest change during all the four future scenarios). Without adaptation strategies, climate change could reduce maize yield in the range of 16% (Tumkur) to 46% (Jalandhar) under RCP 4.5 and 21% (Tumkur) to 80% (Jalandhar) under RCP 8.5. Only at Dharwad, the yield could remain slightly higher or the same compared to the baseline period (1980-2009). Six adaptation strategies were evaluated (delayed sowing, increase in fertilizer dose, supplemental irrigation, and their combinations) in which a combination of those was found to be effective in majority of the districts. District-specific adaptation strategies were identified for each of the future scenarios. The findings of this study will enable in planning adaptation strategies to minimize the negative impact of projected climate in major maize growing districts of India.
MeSH term(s)	Adaptation, Physiological ; Agriculture ; Climate Change ; Crops, Agricultural ; Zea mays
Language	English
Publishing date	2022-04-28
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	121506-1
ISSN	1879-1026 ; 0048-9697
ISSN (online)	1879-1026
ISSN	0048-9697
DOI	10.1016/j.scitotenv.2022.155511
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Article: Evaluating area-specific adaptation strategies for rainfed maize under future climates of India

Subba Rao, A.V.M. / Sarath Chandran, M.A. / Bal, Santanu Kumar / Pramod, V.P. / Sandeep, V.M. / Manikandan, N. / Raju, B.M.K. / Prabhakar, M. / Islam, Adlul / Naresh Kumar, S. / Singh, V.K.

Science of the total environment. 2022 Aug. 25, v. 836

2022

Abstract	This study investigates the spatio-temporal changes in maize yield under projected climate and identified the potential adaptation measures to reduce the negative impact. Future climate data derived from 30 general circulation models were used to assess the impact of future climate on yield in 16 major maize growing districts of India. DSSAT model was used to simulate maize yield and evaluate adaptation strategies during mid (2040-69) and end-centuries (2070-99) under RCP 4.5 and 8.5. Genetic coefficients were calibrated and validated for each of the study locations. The projected climate indicated a substantial increase in mean seasonal maximum (0.9–6.0 °C) and minimum temperatures (1.1–6.1 °C) in the future (the range denotes the lowest and highest change during all the four future scenarios). Without adaptation strategies, climate change could reduce maize yield in the range of 16% (Tumkur) to 46% (Jalandhar) under RCP 4.5 and 21% (Tumkur) to 80% (Jalandhar) under RCP 8.5. Only at Dharwad, the yield could remain slightly higher or the same compared to the baseline period (1980–2009). Six adaptation strategies were evaluated (delayed sowing, increase in fertilizer dose, supplemental irrigation, and their combinations) in which a combination of those was found to be effective in majority of the districts. District-specific adaptation strategies were identified for each of the future scenarios. The findings of this study will enable in planning adaptation strategies to minimize the negative impact of projected climate in major maize growing districts of India.
Keywords	climate ; climate change ; corn ; environment ; fertilizer rates ; irrigation ; meteorological data ; India
Language	English
Dates of publication	2022-0825
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	121506-1
ISSN	1879-1026 ; 0048-9697
ISSN (online)	1879-1026
ISSN	0048-9697
DOI	10.1016/j.scitotenv.2022.155511
Database	NAL-Catalogue (AGRICOLA)

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Article: Pest scenario of Spodoptera litura (Fab.) on groundnut under representative concentration pathways (RCPs) based climate change scenarios.

Srinivasa Rao, M / Rama Rao, C A / Sreelakshmi, P / Islam, Adlul / Subba Rao, A V M / Ravindra Chary, G / Bhaskar, S

Journal of thermal biology

2020 Volume 94, Page(s) 102749

Abstract: Multi-model ensemble of Maximum (Tmax) and Minimum (Tmin) temperature data of four Representative Concentration Pathways viz., RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 of Coupled Model Intercomparison Project 5 (CMIP5) models were generated for ten major ... ...

Abstract	Multi-model ensemble of Maximum (Tmax) and Minimum (Tmin) temperature data of four Representative Concentration Pathways viz., RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 of Coupled Model Intercomparison Project 5 (CMIP5) models were generated for ten major groundnut growing locations of the India to predict the number of generations of Spodoptera litura (Fab.) using Growing Degree Days approach during three future climate viz., Near (NF), Distant (DF) and Very Distant (VDF) periods and were compared over 1976-2005 baseline period (BL). Projections indicate significant increase in Tmax (0.7-4.7 °C) and Tmin (0.7-5.1 °C) in NF, DF and VDF periods under the four RCP scenarios at the ten groundnut growing locations. Higher percent increase of the number of generations of S. litura was predicted to occur in VDF (6-38%) over baseline, followed by DF (5-22%) and NF (4-9%) periods with reduction of generation time (5-26%) across the four RCP scenarios. Reduction of crop duration was higher (12-22 days) in long duration groundnut than in medium and short duration groundnut. Decrease in crop duration was higher in VDF (12.1-20.8 days) than DF (8.26-13.15 days) and NF (4.46-6.15 days) climate change periods under RCP 8.5 scenario. Increase in number of generations of S. litura was predicted even with altered crop duration of groundnut. Among locations, more number of generations of S. litura with reduced generation time are likely at Vridhachalam and Tirupathi locations. Geographical location (74-77%) and climate period (15-19%), together explained over 90 percent of the total variation in the number of generations and generation time of S. litura. These findings suggest that the incidence of S. litura on groundnut could be higher in future.
MeSH term(s)	Animals ; Arachis/parasitology ; Climate Change ; Host-Parasite Interactions ; Models, Theoretical ; Spodoptera/physiology ; Temperature
Language	English
Publishing date	2020-10-06
Publishing country	England
Document type	Journal Article
ZDB-ID	1498364-3
ISSN	1879-0992 ; 0306-4565
ISSN (online)	1879-0992
ISSN	0306-4565
DOI	10.1016/j.jtherbio.2020.102749
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Article: Pest scenario of Spodoptera litura (Fab.) on groundnut under representative concentration pathways (RCPs) based climate change scenarios

Srinivasa Rao, M / Rama Rao, C.A / Sreelakshmi, P / Islam, Adlul / Subba Rao, A.V.M / Ravindra Chary, G / Bhaskar, S

Journal of thermal biology. 2020 Dec., v. 94

2020

Abstract	Multi-model ensemble of Maximum (Tmax) and Minimum (Tmin) temperature data of four Representative Concentration Pathways viz., RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 of Coupled Model Intercomparison Project 5 (CMIP5) models were generated for ten major groundnut growing locations of the India to predict the number of generations of Spodoptera litura (Fab.) using Growing Degree Days approach during three future climate viz., Near (NF), Distant (DF) and Very Distant (VDF) periods and were compared over 1976–2005 baseline period (BL). Projections indicate significant increase in Tmax (0.7–4.7 °C) and Tmin (0.7–5.1 °C) in NF, DF and VDF periods under the four RCP scenarios at the ten groundnut growing locations. Higher percent increase of the number of generations of S. litura was predicted to occur in VDF (6–38%) over baseline, followed by DF (5–22%) and NF (4–9%) periods with reduction of generation time (5–26%) across the four RCP scenarios. Reduction of crop duration was higher (12–22 days) in long duration groundnut than in medium and short duration groundnut. Decrease in crop duration was higher in VDF (12.1–20.8 days) than DF (8.26–13.15 days) and NF (4.46–6.15 days) climate change periods under RCP 8.5 scenario. Increase in number of generations of S. litura was predicted even with altered crop duration of groundnut. Among locations, more number of generations of S. litura with reduced generation time are likely at Vridhachalam and Tirupathi locations. Geographical location (74–77%) and climate period (15–19%), together explained over 90 percent of the total variation in the number of generations and generation time of S. litura. These findings suggest that the incidence of S. litura on groundnut could be higher in future.
Keywords	Spodoptera litura ; climate ; climate change ; models ; peanuts ; pests ; temperature ; India
Language	English
Dates of publication	2020-12
Publishing place	Elsevier Ltd
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	1498364-3
ISSN	1879-0992 ; 0306-4565
ISSN (online)	1879-0992
ISSN	0306-4565
DOI	10.1016/j.jtherbio.2020.102749
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Article: Algorithms for weather‐based management decisions in major rainfed crops of India: Validation using data from multi‐location field experiments

Vijaya Kumar, P. / Bal, Santanu Kumar / Dhakar, Rajkumar / Sarath Chandran, M. A. / Subba Rao, A. V. M. / Sandeep, V. M. / Pramod, V. P. / Malleswari, S. N. / Sudhakar, G. / Solanki, N. S. / Shivaramu, H. S. / Lunagaria, M. M. / Dakhore, K. K. / Londhe, V. M. / Singh, Mahender / Kumari, Pragyan / Subbulakshmi, S. / Manjunatha, M. H. / Chaudhari, N. J.

Agronomy journal. 2021 Mar., v. 113, no. 2

2021

Abstract: Crop weather calendars (CWC) serve as tools for taking crop management decisions. However, CWCs are not dynamic, as they were prepared by assuming normal sowing dates and fixed occurrence as well as duration of phenological stages of rainfed crops. ... ...

Abstract	Crop weather calendars (CWC) serve as tools for taking crop management decisions. However, CWCs are not dynamic, as they were prepared by assuming normal sowing dates and fixed occurrence as well as duration of phenological stages of rainfed crops. Sowing dates fluctuate due to variability in monsoon onset and phenology varies according to crop duration and stresses encountered. Realizing the disadvantages of CWC for issuing accurate agromet advisories, a protocol of dynamic crop weather calendar (DCWC) was developed by All India Coordinated Research Project on Agrometeorology (AICRPAM). The DCWC intends to automatize agromet advisories using prevailing and forecasted weather. Different modules of DCWC, namely, Sowing & irrigation schedules, crop contingency plans, phenophase‐wise crop advisory, and advisory for harvest were prepared using long‐term data of ten crops at nine centers of AICRPAM in eight states in India. Modules for predicting sowing dates and phenology were validated for principal crops and varieties at selected locations. The predicted sowing dates of 10 crops pooled over nine centers showed close relationships with observed values (r² of .93). Predicted phenology showed better agreement with observed in all crops except cotton (Gossypium L.; at Parbhani) and pigeon pea [Cajanus cajan (L.) Millsp.] (at Bangalore). Predicted crop phenology using forecasted and realized weather by DCWC are close to each other, but number of irrigations differed, and it failed for accurate prediction in groundnut at Anantapur in drought year (2014). The DCWCs require further validation for making it operational to issue agromet advisories in all 732 districts of India.
Keywords	Cajanus cajan ; Gossypium ; agrometeorology ; agronomy ; cotton ; crop management ; drought ; monsoon season ; peanuts ; phenology ; pigeon peas ; prediction ; protocols ; research projects ; India
Language	English
Dates of publication	2021-03
Size	p. 1816-1830.
Publishing place	John Wiley & Sons, Ltd
Document type	Article
Note	JOURNAL ARTICLE
ZDB-ID	410332-4
ISSN	1435-0645 ; 0002-1962
ISSN (online)	1435-0645
ISSN	0002-1962
DOI	10.1002/agj2.20518
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Indian summer heat wave of 2015: a biometeorological analysis using half hourly automatic weather station data with special reference to Andhra Pradesh.

Sarath Chandran, M A / Subba Rao, A V M / Sandeep, V M / Pramod, V P / Pani, P / Rao, V U M / Visha Kumari, V / Srinivasa Rao, Ch

International journal of biometeorology

2017 Volume 61, Issue 6, Page(s) 1063–1072

Abstract: Heat wave is a hazardous weather-related extreme event that affects living beings. The 2015 summer heat wave affected many regions in India and caused the death of 2248 people across the country. An attempt has been made to quantify the intensity and ... ...

Abstract	Heat wave is a hazardous weather-related extreme event that affects living beings. The 2015 summer heat wave affected many regions in India and caused the death of 2248 people across the country. An attempt has been made to quantify the intensity and duration of heat wave that resulted in high mortality across the country. Half hourly Physiologically Equivalent Temperature (PET), based on a complete heat budget of human body, was estimated using automatic weather station (AWS) data of four locations in Andhra Pradesh state, where the maximum number of deaths was reported. The heat wave characterization using PET revealed that extreme heat load conditions (PET >41) existed in all the four locations throughout May during 2012-2015, with varying intensity. The intensity and duration of heat waves characterized by "area under the curve" method showed good results for Srikakulam and Undi locations. Variations in PET during each half an hour were estimated. Such studies will help in fixing thresholds for defining heat waves, designing early warning systems, etc.
Language	English
Publishing date	2017-06
Publishing country	United States
Document type	Journal Article
ZDB-ID	280324-0
ISSN	1432-1254 ; 0020-7128
ISSN (online)	1432-1254
ISSN	0020-7128
DOI	10.1007/s00484-016-1286-9
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Book: Atlas of cropping systems in India

Yadav, R. L / Subba Rao. A. V. M

(PDCSR bulletin ; no. 2001-2)

2001

Author's details	by R.L. Yadav and A.V.M. Subba Rao
Series title	PDCSR bulletin ; no. 2001-2
Keywords	Cropping systems ; Atlases
Language	English
Size	95 p. :, col. maps ;, 28 cm.
Publisher	Project Directorate for Cropping Systems Research (ICAR)
Publishing place	Meerut
Document type	Book
Database	NAL-Catalogue (AGRICOLA)

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