Agricultural Transformation with Digital Farming- Exploring new geographies for food production

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Agricultural transformation to lower global carbon footprint

Agricultural activities account for approximately 30 percent of greenhouse gas emitted worldwide, which primarily comes from the use of chemical fertilizers, pesticides, and animal wastes.

Unless immediately addressed, emissions from the agricultural sector are likely to increase as the global population and food production increase exponentially. Lowering the carbon footprint from farming is achievable only through a major agricultural transformation using technology. It could impact how we farm; where we farm; what we eat; the way we store, pack and transport food; where we source, etc.

Certain things food-producing companies can do to reduce this carbon footprint and drive agricultural transformation include:

  • Digital and precision farming
  • Carbon sequestration
  • Switching to green fuels
  • Ensuring farm-to-fork traceability
  • Finding new geographies for agricultural activity

Responsible sourcing is critical

As countries worldwide race to reach net zero carbon emissions globally by 2050, carbon-neutral sourcing is becoming a key goal for agri-input and food processing organizations. To achieve net carbon neutrality, companies are looking to reduce greenhouse gas emissions associated with their operations and offset them by funding equivalent carbon dioxide saving elsewhere.

Most companies in the agricultural sector are actively looking to transform their operations with responsible sourcing and zero carbon farming, which in turn leads to:

benefits-of-responsible-sourcing-for-agricultural-transformation

Exploring newer geographies for food production

With the increasing population, the need for grains, vegetables, and fruits will only increase. Climate-change-induced weather variability, shifting agri-ecosystems, increasing temperatures, invasive weeds, and pests, and extreme weather events are driving the need to explore new geographies that hold the promise of better yield.

Climate-related issues that have cropped up in traditional agricultural geographies have resulted in the emergence of new food-producing regions such as Sub-Saharan Africa and East Asia. In such a scenario, a farm-to-fork traceability application can track produce from its origin – with details of the farm, farmer, time of harvest, etc. – to the moment it reaches the consumer’s table.

The role of farm-to-fork traceability in carbon-neutral sourcing

One of the easiest ways for organizations to ensure responsible agriculture is to identify areas of higher carbon emissions and mitigate them. However, this is easier said than done. Most emissions originate further down the supply chain where the buyer – the agri-input or food processing company – does not have a direct connect. This makes it harder to engage with the supplier and measure the emissions. This is where farm-to-fork traceability comes into play by using cutting-edge Agtech to revolutionize farming and the agricultural supply chain with much-needed transparency.

Smart farming – the way towards zero carbon farming

The main challenges in food production are:

  • Lowered output predictability – which can have a trickle-down effect on replenishment planning, and stock and inventory management for food processing companies
  • Lack of expertise in farming – resulting in a higher probability of errors, inefficient decision-making, and increased cost of operations, etc., which require technology intervention (digitization) to mitigate

With digitalization, food production becomes more sustainable and efficient. Using innovative technologies like AI, ML, and big data, Agtech provides accurate yield estimates that go a long way in production efficiency.

Crop management software helps automate farm activities, streamline production, and work schedules, and improve agricultural productivity. The software collects data, analyzes it, and generates reports that farmers can rely upon to make informed decisions as to when to initiate crop rotation, the appropriate fertilizer to apply, the best pest control method to use, the right time to harvest, etc. All these drive sustainable farming.

Consumers today are concerned about climate change, which in turn is driving the demand for sustainable food production. Consumers want to know what is in their food, where it comes from, and how is it made. Data-driven digital farming solutions can make food supply chains efficient and traceable so that agricultural commodities can be traced from the rural farm to the urban end-consumer.

As more and more companies turn to sourcing agricultural products from across the world, farm-to-fork traceability is becoming essential to provide comprehensive information about the safety and purity of produce and visibility into the supply chain.

A pioneer in farm-to-fork traceability solutions

A global agri-ecosystem intelligence provider, Cropin uses cutting-edge technology such as AI, ML, data science, satellite imagery, and remote sensing to help organizations digitize their operations from farm to fork. Intelligent, interconnected data platforms deliver accurate real-time insights in the form of customizable reports. This empowers organizations with data-driven insights for farm management by tracking, managing, and monitoring every step to increase productivity.

Read Spice Up your Agri-Business: Ways to Enhance Traceability in a Sustainable Spice Business to learn more about how Cropin helps to enhance traceability in agriculture.

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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.

Abishek Keerthi Narayan

About the Author

A results-driven and strategic leader with over 18 years of experience in customer success, SaaS, management consulting and technology enablement. Proven track record of implementing customer-centric strategies to realize the key business outcomes of clients. Strong leader with a track record of building and scaling high-performing teams. Passionate about solving customer problems, creating value, and driving success.