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  1. Article: Field-scale Assessment of Sugarcane for Mill-level Production Forecasting using Indian Satellite Data

    Kumar, Mukesh / Das, Ayan / Chaudhari, K. N. / Dutta, Sujay / Dakhore, K. K. / Bhattacharya, B. K.

    Journal of the Indian Society of Remote Sensing. 2022 Feb., v. 50, no. 2

    2022  

    Abstract: Estimating sugarcane (Saccharum officinarum L.) production at micro-scale prior to harvest is required for fixing of Fair and Remunerative Price (FRP) payable by sugar factories, levy price of sugar and its supply for public distribution systems and ... ...

    Abstract Estimating sugarcane (Saccharum officinarum L.) production at micro-scale prior to harvest is required for fixing of Fair and Remunerative Price (FRP) payable by sugar factories, levy price of sugar and its supply for public distribution systems and regulating supply of free-sale sugar. This may also help the sugar mill owners to plan for crushing the expected cane biomass, estimate the production of sugar in each mill and look for opportunities to sell or buy from nearest sugar mills if expected production is more or less than factory’s crushable capacity. A pilot-scale study was carried out in four sugar mills of Gujarat and Maharashtra states during 2017–2019 period. Multi-date multispectral data from LISS IV, LISS III of Resourcesat-2&2A, GPS and mobile-based ground truth data and Crop Cutting Experiment data (CCE) were used. Crop discrimination in the form of fresh and ratoon, field-scale crop health assessment, yield-model development and mill-level crop acreage and production estimation were carried out. LISS IV data along with error-free GPS-based polygons could lead to discrimination with 95% accuracy and between 88–91% with mobile-based point locations. The mill-level production was found to have less than 10% deviation from reported production. The field-scale assessment and enumeration could lead to mill-level crushable cane production forecast 2 months before harvest. Future efforts are needed to utilize agro-met products and SAR-based metrics to improve the production forecasting.
    Keywords Saccharum officinarum ; biomass ; crop acreage ; health effects assessments ; prices ; remote sensing ; sugarcane ; sugars ; India
    Language English
    Dates of publication 2022-02
    Size p. 313-329.
    Publishing place Springer India
    Document type Article
    ZDB-ID 2439566-3
    ISSN 0974-3006 ; 0255-660X
    ISSN (online) 0974-3006
    ISSN 0255-660X
    DOI 10.1007/s12524-021-01442-2
    Database NAL-Catalogue (AGRICOLA)

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  2. Article: Comparison of different methods for estimation of reference evapotranspiration at Parbhani, Maharashtra

    Phad, S. V. / Dakhore, K. K. / Sayyad, R. S.

    Journal of agrometeorology

    2019  Volume 21, Issue 2, Page(s) 236

    Language English
    Document type Article
    ZDB-ID 2235052-4
    ISSN 0972-1665
    Database Current Contents Nutrition, Environment, Agriculture

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  3. Article: Analysis of rainfall trend of Parbhani, Maharshtra using Mann-Kendall test

    Sayyad, R. S. / Dakhore, K. K. / Phad, S. V.

    Journal of agrometeorology

    2019  Volume 21, Issue 2, Page(s) 239

    Language English
    Document type Article
    ZDB-ID 2235052-4
    ISSN 0972-1665
    Database Current Contents Nutrition, Environment, Agriculture

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  4. Article ; Online: Simulating Potential Impacts of Future Climate Change on Post-Rainy Season Sorghum Yields in India

    Chadalavada, K / Gummadi, S / Kundeti, K R / Kadiyala, D M / Deevi, K C / Dakhore, K K / Diana, R K B / Thiruppathi, S K

    2021  

    Abstract: Given the wide use of the multi-climate model mean (MMM) for impact assessment studies, this work examines the fidelity of Coupled Model Intercomparison Project Phase 5 (CMIP5) in simulating the features of Indian summer monsoons as well as the post- ... ...

    Abstract Given the wide use of the multi-climate model mean (MMM) for impact assessment studies, this work examines the fidelity of Coupled Model Intercomparison Project Phase 5 (CMIP5) in simulating the features of Indian summer monsoons as well as the post-rainy seasons for assessing the possible impacts of climate change on post-rainy season sorghum crop yields across India. The MMM simulations captured the spatial patterns and annual cycles of rainfall and surface air temperatures. However, bias was observed in the precipitation amounts and daily rainfall intensity. The trends in the simulations of MMM for both precipitation and temperatures were less satisfactory than the observed climate means. The Crop Environment Resource Synthesis (CERES)-sorghum model was used to estimate the potential impacts of future climate change on post-rainy season sorghum yield values. On average, post-rainy season sorghum yields are projected to vary between
    Keywords Crop Yield ; Sorghum ; Climate Change ; India
    Subject code 333 ; 550
    Language English
    Publishing date 2021-12-29
    Publisher MDPI
    Publishing country in
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. 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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