Relevant bibliographies by topics / AGMARKNET

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  2. Dissertations / Theses

Academic literature on the topic 'AGMARKNET'

Author: Grafiati
Published: 11 September 2023
Last updated: 31 July 2025

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Journal articles on the topic "AGMARKNET"

1

Suri, P. K., and Sushil. "E-Governance through Collaborations - A Case of NICNET based Agricultural Marketing Information Network (AGMARKNET)." Management Dynamics 7, no. 1 (2022): 33–44. http://dx.doi.org/10.57198/2583-4932.1198.

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A., Praveenkumar, Manoj Varma, Srinatha T. N., et al. "From Traditional to Advanced Models: A Comparative Study between Time Series and Machine Leaning Models in Agriculture." Journal of Scientific Research and Reports 30, no. 9 (2024): 314–25. http://dx.doi.org/10.9734/jsrr/2024/v30i92356.

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The agricultural sector plays a crucial role in the global economy, with edible oil crops like groundnut being vital commodities. Accurate price forecasting is essential for stakeholders, including farmers, traders, and policymakers. The primary aim of this study is to evaluate and compare the effectiveness of traditional time series models (such as ARIMA) and advanced deep learning models (such as RNN, GRU, and LSTM) in forecasting the monthly wholesale prices of groundnut. The analysis covers data from January 2014 to December 2023, collected from Agmarknet. Our results reveal that deep lear
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3

Kumar, Midathana Anil, Arunava Ghosh, Vinay H T, Parthendu Poddar, and Md Wasim Reza. "Forecasting Green Chilli Prices: Using Data Analytics to Gain Market Understanding." Journal of Scientific Research and Reports 30, no. 10 (2024): 671–79. http://dx.doi.org/10.9734/jsrr/2024/v30i102492.

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Green chilli is a commercially significant vegetable crop grown year-round due to its high demand for both nutritional and health benefits. India stands as the largest producer and consumer of chilli globally, with West Bengal leading in area under cultivation and ranking sixth in production. This study aims to compare and identify the most accurate model for forecasting green chilli prices in the Haldibari market of Cooch Behar district, West Bengal. Price data from January 2015 to May 2024, sourced from AGMARKNET, was used for model development, with 85% of the data allocated for training an
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RAGINI NAIKOTI, SATYVEER SINGH MEENA AND VIKASH*. "MARKET INTEGRATION OF SWEET LIME BETWEEN DOMESTIC AND INTERNATIONAL MARKETS." Journal of Research ANGRAU 51, no. 3 (2023): 134–39. http://dx.doi.org/10.58537/jorangrau.2023.51.3.15.

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The study focused on the integration of domestic and international markets for sweet limes during 2021. The co-integration of commodity prices was considered to be necessary for the implementation of a successful marketing reform for which both domestic and international market prices are required. Due to the lack of information regarding international prices, export price information was gathered from thewebsite of the Agricultural and Processed Food Products Export Development Authority (APEDA), and secondary data regarding domestic prices of sweet lime was gathered from the website of the A
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Kiran, Gadhe, A. S. Shaikh, and Mohit Kumar. "Seasonal Patterns in Cumin Arrivals and Prices in Indian Markets: A Post-COVID 19 Analysis." Asian Journal of Agricultural Extension, Economics & Sociology 42, no. 5 (2024): 283–89. http://dx.doi.org/10.9734/ajaees/2024/v42i52438.

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Cumin known as jeera in India, holds significant economic and cultural importance in the country's spice industry. My research paper explores the seasonal dynamics of cumin arrivals and prices in selected Indian markets, considering the profound impact of the COVID-19 pandemic. Utilizing data from the Agmarknet portal spanning from January, 2006 to December, 2021, this study employs rigorous statistical techniques to analyze the patterns. The study reveals distinctive characteristics in cumin arrivals and prices across different markets. Notably, markets like Unjha, Jamnagar, Gondal, Merta Cit
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Prakash, P., D. Jaganathan, Sheela Immanuel, Achal Lama, J. Sreekumar, and P. S. Sivakumar. "Forecasting of Sweet Potato (Ipomoea batatas L.) Prices in India." Indian Journal of Extension Education 58, no. 2 (2022): 15–20. http://dx.doi.org/10.48165/ijee.2022.58203.

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Due to the semi-perishable nature of sweet potato the price fluctuation occur based on demand and supply. Hence, it becomes necessary to precisely forecast market price of sweet potato. Price forecasting of sweet potato was carried out for six selected states in India using time series monthly market price, collected from AGMARKNET price portal from January 2010 to December 2021. Exponential Smoothing Models (ESM), Seasonal Autoregressive Integrated Moving Average (SARIMA) model and Time Delay Neural Network (TDNN) model were used for forecasting of sweet potato price. It was observed that amo
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7

Chavan, Sanket D., Virendra Singh, Shyam Mani Tripathi, and Katta Sravan Naga Parimala Kumar. "Analysis of Spatio-Temporal Behaviour of Arrivals and Prices in Major Onion Markets of India." International Journal of Environment and Climate Change 13, no. 10 (2023): 822–33. http://dx.doi.org/10.9734/ijecc/2023/v13i102722.

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The present study was an attempt to examine the behaviour of arrivals and prices of onion in major markets of India over the period from 2008 to 2022. The entire investigation relies on data obtained from secondary sources. Data on monthly wholesale prices and arrivals of selected markets was gathered from Agmarknet, Directorate of Marketing & Inspection, Government of India. Six markets were selected purposively, of which one each market was from four top onion producing states (Lasalgaon, Bangalore, Indore and Ahmadabad) and two were from top consuming cities (Mumbai and Delhi). Various
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8

Kumar, K. Sathees, T. Ilakiya, and T. Gowthaman. "Price instability, seasonal index and modelling for major vegetables in India." Journal of Applied Horticulture 25, no. 02 (2023): 219–23. http://dx.doi.org/10.37855/jah.2023.v25i02.39.

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Vegetable production plays a pivotal role in the horticulture industry, yet the availability of vegetable crops remains unpredictable. Seasonal volatility contributes to unclear supply, resulting in price fluctuations. This study aimed to assess the seasonal indices and price instability of key vegetables in India using the Cuddy-Della Instability Index and the Ratio to Moving Average approach. Monthly price series spanning January 2010 to December 2021 were collected from the AGMARKNET website. Seasonality in the price series was examined using the Kruskal-Wallis test. The results indicated t
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9

Vedika Sanjay Sardeshmukh, Sneha Babaso Patil, and Prof. Sanmati Bedage. "An AI-Driven Smart Crop Recommendation and Advisory Framework." International Research Journal on Advanced Engineering Hub (IRJAEH) 3, no. 07 (2025): 3209–18. https://doi.org/10.47392/irjaeh.2025.0472.

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In the face of escalating climate variability, market uncertainties, and resource constraints, farmers increasingly require intelligent decision-support systems to sustain agricultural productivity. This study presents an AI-driven smart crop recommendation and advisory framework that integrates supervised machine learning algorithms with natural language processing to support sustainable agriculture in diverse agro-climatic regions of India. The system utilizes a curated dataset comprising soil nutrient values (N, P, K), pH, rainfall, and temperature, combined with crop price data from Agmark
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PAUL, RANJIT KUMAR, DIPANKAR MITRA, HIMADRI SHEKHAR ROY, A. K. PAUL, and M. D. YEASIN. "Forecasting price of Indian mustard (Brassica juncea) using long memory time series model incorporating exogenous variable." Indian Journal of Agricultural Sciences 92, no. 7 (2022): 825–30. http://dx.doi.org/10.56093/ijas.v92i7.103633.

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The objective of present study was to investigate the efficiency of Autoregressive fractionally integrated movingaverage model with exogenous input (ARFIMAX) in forecasting price of Indian mustard [Brassica juncea (L.) Czern.& Coss]. The daily modal price and arrival data of mustard for two major markets of India, viz. Bharatpur and Agrawere collected during 2008–2018 from AGMARKNET and used for the present investigation. It was observed thateach of the price series under consideration is stationary but autocorrelation function of both the series decay in ahyperbolic pattern. This indicate
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Dissertations / Theses on the topic "AGMARKNET"

1

BAKSHI, SOHAIL. "DEVELOPING A DIAGNOSTIC TOOL AND TIME SERIES ANALYSIS IN RESPECT OF WHEAT ARRIVALS AND PRICES." Thesis, 2017. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16998.

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Timely disseminating marketing related information of agricultural commodities throughout the country is essential in today’s scenario. AGMARKNET portal is one such initiative to collect, compile and disseminate prices and arrival data of agricultural commodities. The information that this portal provides is critical to all the stakeholders associated with agriculture. AGMARKNET aims to deliver correct and complete information to the farmers in order to strengthen their economic position. Farmers can know before going to the markets the price at which the crop can be sold which brings them in
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