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District-wise yearly area, yield and production. This file group has two files: 1. Area, production and yield and 2. High yielding varieties The area, production yield file includes data on 20 major crops that include cereals, pulses, oilseeds, cotton, sugarcane, total fruits and vegetables. Yield is calculated based on area and production.

The data are for the annual area and production under the crops. The percent area under each crop is calculated by dividing crop area by Gross Cropped Area (GCA variable generated using a defined methodology).

For more details see definition and standards and in the data documentation manual the section on ‘data clarification and anomalies’.For season wise crop area and production data refer to season wise area and production of crops under additional data); for breakup of fruits and vegetables data by type also see files on area and vegetables under additional data.

The second file is on High Yielding Varieties (HYV / hybrids) has data on area under HYVs for 5 major cereal crops. The data on HYVs has a number of gaps in recent years implying that the area is completely under HYVs and hence no longer reported / some states do not publish this data.

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India Agricultural Production: Major Crops: Achievements: Pulses data was reported at 27.504 Ton mn in 2023. This records an increase from the previous number of 27.302 Ton mn for 2022. India Agricultural Production: Major Crops: Achievements: Pulses data is updated yearly, averaging 12.840 Ton mn from Mar 1956 (Median) to 2023, with 68 observations. The data reached an all-time high of 27.504 Ton mn in 2023 and a record low of 8.350 Ton mn in 1967. India Agricultural Production: Major Crops: Achievements: Pulses data remains active status in CEIC and is reported by Directorate of Economics and Statistics, Department of Agriculture and Farmers Welfare. The data is categorized under India Premium Database’s Agriculture Sector – Table IN.RIB002: Agricultural Production: Targets & Achievement of Major Crops.

Firm-specific data is used to study the impact of AI on Total Factor Productivity Growth(TFPG) for the agriculture sector. Another part of this research is to find out the effect of artificial intelligence on the output of the firms, which produce crops

TFPGit = α + B1Sizeit + B2DisembodiedTechintit + B3AIintit + B4ADVinit+ B5EmbodiedTechintit + B6R&Dintit + ε

Definitions of Variables: TFPGit is the measure for total factor productivity growth for firm i in the agriculture sector in year t. B1Sizeit is the measure of firms’ size denoted by log(total assets) for firm i belonging to the agriculture sector in the year t. B2DisembodiedTechintit is the measure of technological intensity for firm i in the agriculture Sector in the year t. Disembodied technological intensity is calculated as the ratio of royalty and technical know-how to sales of the firm. B3AIintit is measured as the ratio of software and computer machinery investments to total sales for firm i in agriculture sector in a given year t. This is the primary variable of interest and it’s hypothesized that β3 will be positive. B4ADVintit is a measure of advertisement intensity for firm i in agriculture sector in a given year t. Advertisement intensity is the ratio of expenditure on advertisement to total sales. B5EmbodiedTechintit is a measure of embodied technological intensity and is calculated as the ratio of the import of capital goods to the sales of the firm i in the agriculture sector in year t. B6R&Dintit is a measure of research and development intensity and is calculated as the ratio of R&D expenditure to sales of the firm i in the agriculture sector in year t. ε is the error term

The Agriculture Industry in India Report is Segmented by Commodity Type (Cereals and Grains, Pulses and Oilseed, and More). The Report Includes Production Analysis (Volume), Consumption Analysis (Value and Volume), Export Analysis (Value and Volume), Import Analysis (Value and Volume), and Price Trend Analysis. The Market Forecasts are Provided in Terms of Value (USD) and Volume (Metric Tons).

🌾 Indian Agriculture Crop Production and Yield (District-level, 1998–2021)

📖 Description

This dataset provides district-level crop production, cultivated area, and yield data for India covering the years 1998 to 2020-21. It includes details of major food grains, pulses, oilseeds, and commercial crops across all districts of India.

The dataset is curated from:

Kaggle – India Agriculture Crop Production Open Government Data Platform, India (data.gov.in)

This makes it one of the most detailed publicly available datasets for Indian agriculture, enabling district-level mapping and visualization of crop performance.

📑 Dataset Content

The dataset contains 575,879 rows × 8 columns with district-level agricultural data. State_Name → Name of the State/UT (e.g., West Bengal, Maharashtra, Tamil Nadu) District_Name → Name of the District (e.g., Purulia, Akola, Madurai) Crop_Year → Year of crop production (1997 – 2020-21) Season → Agricultural season (Kharif, Rabi, Summer, Whole Year, Autumn, Winter) Crop → Name of the crop grown (e.g., Rice, Wheat, Sugarcane, Banana, Cotton) Area (Hectares) → Total cultivated area under the crop (in hectares) Production (Quintals) → Total crop output (in Quintals) Yield (Quintals/Hectare) → Calculated crop productivity = Production / Area

This Dataset consists of Fiscal Year and Crop-wise Area, Production and Yield statistics for All India.

India Agricultural Production: Major Crops: Target: Cotton data was reported at 355.000 Ton mn in 2019. This records an increase from the previous number of 35.500 Ton mn for 2018. India Agricultural Production: Major Crops: Target: Cotton data is updated yearly, averaging 24.000 Ton mn from Mar 1998 (Median) to 2019, with 22 observations. The data reached an all-time high of 355.000 Ton mn in 2019 and a record low of 14.500 Ton mn in 2002. India Agricultural Production: Major Crops: Target: Cotton data remains active status in CEIC and is reported by Department of Agriculture and Cooperation. The data is categorized under India Premium Database’s Agriculture Sector – Table IN.RIB002: Agricultural Production: Targets & Achievement of Major Crops.

📘 Overview

This dataset is a comprehensive agricultural data collection for Tamil Nadu, India, curated and compiled manually using authentic local and government-based records. It provides detailed insights into crop yield, rainfall, land usage, and production patterns across multiple districts and years.

🌾 Included Files

Tamilnadu agriculture yield data.csv – District-wise crop yield values with factors such as soil type, rainfall, fertilizer use, and productivity (2015–2025).

Tamilnadu Crop-Production.csv – Annual and seasonal crop production details by district and crop type.

rainfall_data.csv – Historical monthly and annual rainfall data across Tamil Nadu districts.

land_use.csv – Agricultural land distribution, irrigation coverage, and cropping pattern details.

crop_production_history.csv – Past crop production records with multi-year trends and average yield values.

rice_production.csv – Rice-specific yield and production data (key crop of Tamil Nadu).

🎯 Purpose

This dataset is intended to help data scientists, researchers, and students working on:

Crop yield prediction models

Land-use optimization

Rainfall vs yield correlation studies

Sustainable agriculture planning

Machine learning and deep learning applications for smart farming

🧠 Example Applications

Predicting yield based on climatic and soil factors

Building rainfall forecasting models

Analyzing agricultural trends district-wise

Studying the relationship between rainfall and productivity

🧾 Data Format

All files are in CSV format and can be directly loaded into Python (Pandas), R, or Excel.

📅 Time Period

Data covers approximately 2015–2025, with records compiled from multiple verified sources and cleaned manually for machine learning use.

📍 Geographic Coverage

State: Tamil Nadu, India Districts covered: All major agricultural districts including Thanjavur, Erode, Coimbatore, Villupuram, Madurai, and more.

📊 Suggested Columns (example fields)

District

Year

Crop

Soil Type

Rainfall (mm)

Temperature (°C)

Humidity (%)

Fertilizer Used (kg/ha)

Yield (kg/ha or tonnes)

📈 Potential Uses

Regression models for crop yield prediction

Classification models for suitable crop selection

Time series analysis for rainfall and production trends

🔖 Tags

tamil-nadu, agriculture, crop-yield, machine-learning, rainfall, india, farming, data-science

The Indian agriculture market size was approximately USD 457.26 Billion in 2024. The market is projected to grow at a CAGR of 4.90% between 2025 and 2034, reaching a value of around USD 737.77 Billion by 2034.

Data and insights on the Agriculture sector in India - production and yield per hectare, minimum support price (MSP), and comparison with global peers.

India Agricultural Production: Major Crops: Achievements: Wheat data was reported at 112.743 Ton mn in 2023. This records an increase from the previous number of 107.742 Ton mn for 2022. India Agricultural Production: Major Crops: Achievements: Wheat data is updated yearly, averaging 51.980 Ton mn from Mar 1956 (Median) to 2023, with 68 observations. The data reached an all-time high of 112.743 Ton mn in 2023 and a record low of 7.990 Ton mn in 1958. India Agricultural Production: Major Crops: Achievements: Wheat data remains active status in CEIC and is reported by Directorate of Economics and Statistics, Department of Agriculture and Farmers Welfare. The data is categorized under India Premium Database’s Agriculture Sector – Table IN.RIB002: Agricultural Production: Targets & Achievement of Major Crops.

In fiscal year 2024, the export value of agriculture and allied products was nearly ** billion U.S. dollars from India. Rice, marine products, and spices made up the leading commodities exported in this segment.

Agricultural land in India amounted to over *** million hectares in financial year 2023. This was a decrease in agricultural land when compared to the previous year. That year, Haryana and Punjab were the leading Indian states with land available for agricultural purposes.  Cultivation and farming Of all agricultural land in India, *** million hectares has been cultivated. This makes India one of the largest agricultural economies globally. Major land types include alluvial soil in the Indo-Gangetic plains, black soil in Deccan, and red and laterite soils in the southern and eastern regions – all supporting the cultivation of rice, wheat, pulses, cotton, and oilseeds across varying climatic zones. Digitalization in farming Of recent policy developments from the central government towards agriculture has been the promotion of natural farming and digital land records. Initiatives like PM-KISAN provide income support to farmers. Additionally, states including Madhya Pradesh and Uttar Pradesh are digitizing land ownership data to reduce disputes. While controversial, several other states have eased land leasing laws to attract private investment and improve land utilization.

Actual value and historical data chart for India Agriculture Value Added Annual Percent Growth

The India Agricultural Biologicals Market Report is Segmented by Function (Crop Nutrition and Crop Protection) and Crop Type (Cash Crops, Horticultural Crops, and Row Crops). The Market Forecasts are Provided in Terms of Value (USD) and Volume (Metric Tons).

Actual value and historical data chart for India Employment In Agriculture Percent Of Total Employment

GDP from Agriculture in India decreased to 5683.74 INR Billion in the second quarter of 2025 from 6773.89 INR Billion in the first quarter of 2025. This dataset provides - India Gdp From Agriculture- actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Indian agricultural product warehousing services market is poised for significant growth, driven by increasing agricultural production, rising demand for efficient supply chain management, and the government's push for improved post-harvest infrastructure. Between 2019 and 2024, the market likely experienced a Compound Annual Growth Rate (CAGR) of around 8%, considering India's economic growth and agricultural sector expansion during this period. Projecting this forward, a conservative estimate for the market size in 2029 would be approximately ₹800 billion (assuming a value unit of INR Billion and a continued CAGR of 7% from 2025 onwards, reflecting some potential moderation in growth as the market matures). Key drivers include the growing adoption of technology in warehousing, such as automated systems and inventory management software, increasing cold storage capacity to reduce post-harvest losses, and the rising popularity of organized retail and e-commerce platforms, all of which increase the demand for reliable warehousing solutions. Trends indicate a shift toward integrated warehousing solutions that offer value-added services like processing, packaging, and quality control, catering to the needs of a sophisticated agricultural supply chain. However, constraints such as infrastructure limitations in certain regions, high land costs, and the seasonal nature of agricultural production continue to pose challenges. The market is segmented based on storage type (cold storage, ambient storage), product type (grains, pulses, fruits & vegetables etc.), and location (rural, urban). The growth is anticipated to be spread across various regions in India, with states having high agricultural output benefiting most. The competitive landscape involves both global and domestic players, with a mix of large corporations and smaller, regional operators. The future growth trajectory will likely be shaped by the government's continued investments in infrastructure development, advancements in technology, and the adoption of better agricultural practices by farmers. The market's success hinges on addressing challenges related to land acquisition, regulatory hurdles, and the training of skilled workforce to manage technologically advanced warehousing facilities. Investment in technological upgrades and sustainable practices will play a crucial role in optimizing operations and ensuring the long-term sustainability of the industry. A focus on efficient supply chain management and reducing post-harvest losses will be critical in maximizing the returns for farmers and ensuring food security.

Dataset

This dataset was created by prarthana1994

Contents

India's agriculture sector plays a pivotal role in the nation's economy, culture, and food security. With a diverse agro-climatic landscape, India is one of the world's leading agricultural producers, contributing significantly to both domestic consumption and global trade. Conclude the analysis by discussing the future prospects of India's agriculture production. Highlight emerging trends, opportunities for innovation, and the role of research and development in shaping the sector's trajectory.