How intelligent agriculture cloud helps maximize crop yield

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Understanding population growth in relation to food production is significant for sustainable development in the 21st century. The world population is projected to grow from 8 billion in 2022 to 9.7 billion in 2050, and demand for food is projected to reach 3 billion tonnes by 2050. Overall food production is expected to increase by approximately 70% between 2007 and 2050.

The increasing population and demand for food, coupled with declining arable land and agricultural labor, have compelled stakeholders in agri-business to consider intelligent options to improve agriculture productivity. Adopting sustainable agriculture practices is gaining popularity to beat the threat of climate change.

How to increase crop yield with agri-intelligence

Agriculture, one of the oldest industries, has been shaped by various technological innovations over the last few years. We are constantly innovating to increase crop yield to meet the demand of a growing population. Quality seeds, irrigation facilities, fertilizers, and pesticides have helped farmers increase crop yield.

Today, climate change, increasing population, growing demand for food, diminishing arable land and freshwater resources, etc., have made it imperative to leverage technology to transform the agri-food system. Modern technology can be used in several aspects of agriculture such as the application of herbicides, pesticides, fertilizers, and improved seed production. Thanks to technology, farmers can grow crops in areas that were earlier considered impossible for cultivation and make every process more efficient to improve production.

Featured Case Study: Learn how a leading food and beverage manufacturer maximized crop yield with predictive intelligence and remote sensing.

Factors influencing crop yield

Crop yield that indicates a farmer's agricultural output at a given period measures produce harvested per unit of land area. Farmers are always considering ways to increase crop yield. Numerous factors, including technology, play a significant role in increasing crop yield. Here are the five factors influencing crop yield, and technology is helping achieve that.

Seed quality

Good quality certified seeds are essential to maximizing crop yield. To increase yield, plant breeding companies must select the right hybrid seed, for which historical analysis of various environmental factors, along with the variable weather and pests and the greatest asset soil must be done. Using artificial intelligence models, farmers are assisted in choosing the ideal seed variety for their farms. On the other hand, to produce excellent quality seeds, seed companies face challenges such as grading seed varieties, ensuring data accuracy before the seed multiplication stage, on-ground fleet management, harvesting at the right time, loss due to fake hybrid seeds and counterfeit products, etc. Leveraging intelligent agriculture cloud, seed companies can reduce time spent on R&D while meeting standards for seed certification, implement traceability systems to eliminate counterfeiting, engage with farmers to optimize yield, and enjoy accurate demand forecasting that ensures timely availability of seeds.

Field productivity

To improve field productivity, analysis of various factors like enhancing soil fertility, decreasing pests, diseases, and weather predictions from sowing to harvest is done by integrating agri-data from a wide variety of data types, including location, images/videos, spatiotemporal feeds, and satellite monitoring of crops. Knowledge sharing with farmers in the form of Package of Practices (PoP) specific to seed variety and region, alerts, details on agri-input availability, timely advisories, remote monitoring of in-field activities, etc., helps to increase crop yield. Data collated from AI/ML models provide actionable intelligence that allows farmers to reduce operational costs. Pest and disease alerts help thwart the issue at an early stage and arrest losses.

Weather prediction

Along with climate change, erratic weather conditions can cause havoc to crop and impact the harvest. Although it is impossible to avert the effects of severe weather conditions, farmers can manage them by preparing in advance. Crop and environmental monitoring machine learning models use weather and satellite data to arrive at predictive agri-intelligence. Agriculture technology provides advisories on the quantum and time to apply various agri-input resources depending on the weather.

Optimum use of agri-input resources

By protecting crops from pests and diseases or adding necessary fertilizers and pesticides, agri-input companies play a critical role in increasing crop productivity. However, the proper usage of chemicals would depend on an appropriate understanding of which areas would benefit most from what kind of input. An intelligent agriculture cloud leverages data collated by various methods and provides data-driven insights to farmers on the quantum of agri-input resource usage. This is specific even to particular patches within a farm and has the dual benefit of improving yield and optimizing operational costs for the farmers.

Seamless communication between stakeholders

Communication between various stakeholders – farmers, seed companies, agri-input companies, food processing companies, and others – is important for maximizing per-acre value. Digitalization in agriculture offers a platform for seamless communication among various stakeholders and improves the visibility of farmers. Such an engagement helps with remote monitoring, sends early warning alerts and advisory for risk mitigation, ensures farmers’ enablement with precise information on the availability of agri-input resources and market advisories, details on farm equipment and new loan schemes, etc.

Intelligent agriculture cloud platform connects farmers and businesses

To ensure the above factors are implemented successfully to increase agricultural productivity, nurturing a healthy relationship with farmers and other stakeholders becomes vital. Pioneers in the field like Cropin leverage Internet of Things (IoT), Artificial Intelligence (AI), robots, drones for remote sensing, apps and devices, satellite farming, etc., for the digital transformation of agriculture and to connect farmers with various stakeholders seamlessly. This empowers farmers to become better decision-makers and maximize their crop yield.

Cropin Connect is a mobile application on the Cropin Cloud platform that aids seamless business-to-farmer engagement. The app educates farmers with automated advisories through SMS. Cropin Cloud provides access to real-time farm data management dashboards and on-demand reports to monitor, measure, and take actions and details about crop health and yield estimation. Cropin Cloud also provides information and consultation with weather-based disease predictions/alerts and crop advisories in the local language. Apart from assisting farmers, the app also aids businesses in increasing efficiency and profitability through digitalizing complex processes and workflows.

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Know more about Cropin Cloud - the world's first intelligent agriculture cloud platform

Cropin Apps

Applications for
digitization

Cropin Apps is an integrated portfolio of highly customizable apps and solutions that capture and digitise agri-data from the farm to the warehouse to the fork. These applications are designed to scale digital transformation across agriculture and allied industries including forestry, commodity, banking and insurance.

DataHub

ML-ready data pipelines for enhanced analytics

Cropin Data Hub is designed to deliver the power of unified data by enabling interfacing with all agri-data sources from on-the-field farm management apps, IoT devices, mechanization data from farming resources, drones in agriculture, remote sensing satellite information, weather data, and many more.                                                      

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Access to field-tested machine learning models

Cropin Intelligence enables access to over 22 of Cropin’s contextual deep-learning AI models to help agri-businesses with insights and predictive intelligence. Built using the world's largest crop knowledge graph, these models have been field-tested and deployed worldwide while being fine-tuned to work with a range of specific crop varieties, conditions, and locations.

Rajesh Jalan

About the Author

Rajesh Jalan is the Chief Technology Officer and Head of Engineering at Cropin, the Agritech pioneer who has built the world's first purpose-built industry cloud for Agriculture - Cropin Cloud. He has over 25 years of experience building and leading software products and services engineering teams that are globally scaled, always available, and trusted. An inventor and innovator at heart, over the course of his career, Rajesh has been awarded 10 patents in various areas including code analysis, code optimization, and operating systems. At Cropin, Rajesh oversees the continued evolution of the company’s suite of SaaS-based Agri solutions and building the world’s first Intelligent Agriculture Cloud platform.