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9 Agritech startups making Indian farmers self-reliant - Agriculture Post


Agritech in India has seen a skyrocketing growth with numerous startups emerging with new technologies and advanced methods such as data analytics, machine learning and satellite imaging, among others to cater to the needs of Indian farmers and maximise their output. India with 118.7 million farmer households, accounting for more than half of the population is heavily dependent on agriculture as a primary source of income. But Indian agriculture is plagued by several problems both man made and natural such as; unavailability of seeds, small and fragmented land-holdings, problems with irrigation due to uncertain monsoon, shortage of finance among other necessities, leaving farmers helpless and with no option but to let their produce go at dirt cheap prices. Therefore, Agritech is clearly one of the most needed industries in India and here is a list of top 9 agritech startups helping Indian farmers by providing agronomic intelligence. Started in 2016 by Nishant Vats and Tauseef Khan, Gramophone is a one-stop e-commerce platform for farmers delivering agricultural inputs in more than 10,000 villages.

Mahindra expands Krish-e centres to Andhra Pradesh & Telangana - Agriculture Post


After successfully rolling out in Maharashtra, Mahindra & Mahindra's Farm Equipment Sector (FES), recently rolled out Krish-e centres in Tadepalligudem, Nandyala and Tenali in Andhra Pradesh along with Mahbubnagar, Miryalaguda and Kamareddy districts in Telangana as part of Mahindra's new'Farming as a Service' (FaaS) business. Parinaam Dikhaye' – Krish-e is a business vertical that provides technology driven services which are progressive, affordable and accessible to farmers. Krish-e aims to increase farmers' income through digitally enabled services, across the complete crop cycle. These include agronomy advisory, access to advanced farm equipment rentals and new-age precision farming solutions, all focused on bringing down overall farming costs and improving crop output and consequently the farmers' income. Besides Maharashtra, Adhra Pradesh and Telangana, Krish-e will also roll-out centres across other states in a phased manner.

CYPUR-NN: Crop Yield Prediction Using Regression and Neural Networks Artificial Intelligence

Our recent study using historic data of paddy yield and associated conditions include humidity, luminescence, and temperature. By incorporating regression models and neural networks (NN), one can produce highly satisfactory forecasting of paddy yield. Simulations indicate that our model can predict paddy yield with high accuracy while concurrently detecting diseases that may exist and are oblivious to the human eye. Crop Yield Prediction Using Regression and Neural Networks (CYPUR-NN) is developed here as a system that will facilitate agriculturists and farmers to predict yield from a picture or by entering values via a web interface. CYPUR-NN has been tested on stock images and the experimental results are promising.

How AI is helping Indian cotton farmers reduce pesticide use


There are more than 5.8 million cotton farmers in India according to the country's Textile Ministry. Every year, they face heavy losses due to pests attacking their crops. In 2017, farmers in the state of Maharashtra faced a loss of ₹15,000 crores ($2.1 billion) as 50% of the crop was under attack from pests. As a result, more than 55% of pesticide in India goes towards cotton farming. However, the wrong usage of these chemicals can damage the crop or reduce the quality.

How Technology can Benefit Agriculture and Farmers in India


The change in Indian agriculture began with the Green Revolution, which was trailed by accomplishments of large achievements: Blue revolution, white revolution, yellow and Bio-Technology revolutions. In India, agriculture is the core sector for food security, nutritional security, and sustainable development & for poverty alleviation. Around 64% of the total labor force is occupied with horticulture or agribusiness based businesses. After independence, there has been noteworthy development in Indian agriculture with the grain production ascending to 273.83 million tons this year. All things considered, there are enormous challenges to be analyzed to enhance the agricultural growth in India.

Artificial intelligence solutions built in India can serve the world


The RAISE 2020 summit (Responsible AI for Social Empowerment) has brought issues around artificial intelligence (AI) to the centre of policy discussions. Countries across the world are making efforts to be part of the AI-led digital economy, which is estimated to contribute around $15.7 trillion to the global economy by 2030. India, with its "AI for All" strategy, a vast pool of AI-trained workforce and an emerging startup ecosystem, has a unique opportunity to be a major contributor to AI-driven solutions that can revolutionise healthcare, agriculture, manufacturing, education and skilling. AI is the branch of computer science concerned with developing machines that can complete tasks that typically require human intelligence. With the explosion of available data expansion of computing capacity, the world is witnessing rapid advancements in AI, machine learning and deep learning, transforming almost all sectors of the economy.

AI is helping farmers in Andhra Pradesh to increase crop yields


"Technology's true promise lies in the good we can do and the challenges we can overcome together," says Som Satsangi, Managing Director, Hewlett Packard Enterprise, India. The farmers were prescribed the amount of water to be released and the type of manure to select using nine different metrics such as values of nitrogen, phosphorus, potassium (NPK), soil moisture, leaf wetness, acidic value, soil temperature and soil humidity captured by the IoT modules. This ensured the irrigation on the fields was based on scientific recommendations, and the correct manure and fertiliser were used according to the soil type and weather conditions.

Intelligent Farming


The 62-year-old owns 52 acres of land on which he grows rice, cotton, pulses, sugarcane and black gram. For years, pests had been attacking his black gram crop, and it took days, even weeks, to consult agricultural experts. By the time he got the remedies, the infection spread, resulting in crop loss. Last year, just as he spotted shrunken leaves, he downloaded an artificial intelligence (AI)-driven application on his phone and uploaded photographs of the leaves. The app, Plantix, took minutes to diagnose that the crop had crinkle virus infection and suggested remedies. The disease, if detected early, is easily controllable by tackling aphid, small sap-sucking insects that act as vectors for the virus. "The disease was diagnosed in two minutes. I started remedial measures that afternoon itself. I also used better irrigation methods and harvested 850 kg black gram per acre, all thanks to AI," says Ravichandran. The earlier output used to be 150 kg per acre. In 2017, Maharashtra, the country's biggest cotton producer, was hit by its worst pest infection on cotton in recent times.

Scope and Impact of AI in Agriculture - KDnuggets


The Green Revolution during the 1950s and 1960s remarkably drove up the global food production around the world, saving a billion people from starvation. The revolution led to the adoption of new technologies like high-yielding varieties (HYVs) of cereals, chemical fertilizers and agro-chemicals, better irrigation and mechanization of cultivation methods. India followed suite and adopted the use of hybrid seeds, machine, fertilisers and pesticides. While these practices solved the food shortage problem, they created some problems too in terms of excessive use of fertilisers and pesticides, depletion of ground-water, soil degradation etc. These problems were exacerbated by lack of training to use modern technology and awareness about the correct usage of chemicals etc.

How IoT and Big Data help farmers analyse and plan activities - Express Computer


Agritech company FarmERP was incepted as a part of Shivrai Technologies over a decade ago, keeping in mind the struggles of farmers and the pressure on them to grow exceeding produce by the day, on limited areas of land. Initially, as the digital divide was apparent in farming, incorporating IT solutions into farming was an exceedingly difficult idea. However, in 2001, the software platform firm got its break, when it developed its first multilingual multimedia content for farmers in India for Government agencies and grower associations. And there was no turning back thereafter. Today, FarmERP is a part of over 12 industry sub verticals including plantations and farms, contract farming, R&D institutions, Government bodies, export and pack house industry, farmer producer companies and various others.