Big Data Transforms Agriculture in This Way

Sometimes, we can only discover the changes that have taken place by looking back at the past. However, today we can already clearly see the innovations and changes taking place in the agricultural field.

To obtain more food, agricultural production needs more new products, new methods, and new technologies to provide support. To protect the earth, we need to reduce the use of chemicals and save water resources. Farmers hope to increase yields per unit area, save costs, and obtain better returns. Consumers need safer and healthier food.

Big data is bringing changes to these needs

First of all, it is to meet the processing needs of massive data generated from gene technology, water resource management, fertilizers, climate, soil, agricultural machinery to plant protection, and provide new methods for acquiring and using data for agricultural production and crop genetics. In the field of data analysis and processing, the industrial chain is shifting from large companies to small companies and farms, and of course, large companies are also continuing to innovate.

Change requires great ideas, new business models, and bold and innovative people. The big data industry will give birth to a batch of independent companies based on this, and these companies will bring new concepts, methods, and practices. Agricultural companies on the traditional supply chain must adapt to this change if they want to keep up with the times.

I think big data can be applied to four aspects of the agricultural production chain.

• R&D of new seeds Use new products and new methods such as new gene sequencing and chromosome maps to discover and create new plant genes more quickly.
• Precision agriculture Although big data and precision agriculture are sometimes confused, they are not the same thing. Big data uses data obtained from precision agriculture in different farms to make decisions, and precision agriculture performs farming operations based on big data analysis results and decision instructions.
• Food traceability Use sensors and analytical decision-making to prevent food spoilage and foodborne diseases.
• Impact on the supply chain Information technology will bring huge changes to the two supply chains of products and agricultural means of production.

Big data accelerates crop breeding

Traditional breeding methods to obtain a good crop variety require a lot of labor, a lot of money, and no less than ten years. Big data will accelerate the crop breeding process. Gene technology has brought about the explosive development of biological information: first, because a large number of model organisms need gene sequencing, and second, due to the promotion and application of high-throughput and fully automated technologies, gene sequencing has become more convenient.

Now a large number of test steps can be completed in the cloud. Biological tests that previously needed to be carried out in greenhouses and fields can now be analyzed, planned, and hypothesized on chips. Now, only through preliminary screening, seeds with good potential will undergo planting trials. I have seen this gratifying change, and I no longer need to wear boots to go to the breeding station, and most of the work is completed in the laboratory in advance. New technology is not only cheap and fast, but can also do more things.

Traditional genetic engineering has bred drought-resistant, insect-resistant, and herbicide-resistant varieties, and new technologies will bring more new crop varieties with excellent quality, economical and environmentally friendly. High-calcium carrots, antioxidant tomatoes, allergy-free nuts, antibacterial oranges, water-saving wheat, and nutrient-rich cassava are key research and development directions in the future.

In the future, using big data analysis, field production will become faster and more convenient. Small laboratories with few resources will play an increasingly important role. Through sharing databases, more startups will be born in the fields of plant genomics and cloud biology.

Here are some startups in the field of plant genomics:

• Caribou Biosciences: CRISPR-Cas gene company (received $44.6 million in investment).
• Benson Hill Biosystems: Plant biotechnology, big data analysis and cloud service platform (received $8.05 million in investment).
• Intrexon: Obtaining excellent plant traits through new technologies.
• Cibus: Using gene technology to develop new herbicide-resistant crops.
• Arcadia Biosciences: Using advanced screening, breeding methods and biotechnology to screen new crop varieties.
• Precision Biosciences: Gene technology company, built an agricultural R&D team (received $25.65 million in investment).
• DuPont/Dow, Syngenta, Monsanto, Bayer, BASF are actively laying out this field through internal cultivation and mergers and acquisitions.

Data-driven agricultural production, better results

Agricultural production is extremely complex: biological, meteorological, and human activities interact. In recent years, producers have begun to try to adopt precision agriculture technology. Using GPS and supporting technologies, producers can track yields, manipulate equipment, monitor field conditions, and precisely manage agricultural inputs, greatly improving production efficiency. Precision agriculture equipment has collected a large amount of data, and without software-assisted analysis, humans can no longer analyze and use these data. Artificial intelligence based on machine learning is becoming smarter in interacting with data, equipment, and humans. Through machine learning, they can provide accurate farming decision reference for farms.

Big data companies can test crop genetic traits, inputs, and environmental conditions under different farms, soils, and climate conditions. They can conduct real field plot trials on tens of millions of acres of land to obtain experimental data. These data help farmers develop planting plans for specific seeds in specific fields and specific climate conditions. For crop protection vendors, this means that for specific plots, they can provide personalized agrochemical products and crop solutions.

Information is power

This transparency brought about by big data may break the traditional agricultural supply chain and cause resentment from many retailers, dealers, and seed and agrochemical enterprise producers. Information drives growers’ income by reducing the input of agricultural products. Growers use very precise methods to invest very few chemical inputs, but can obtain better benefits than using brand-name products all over the field. According to statistics, precision fertilization schemes can reduce input usage by about 30-40%, which will further compress the profit space of large agrochemical companies and lead to further integration of the agricultural materials supply chain.

Despite low agricultural product prices and unsatisfactory farm benefits, the usage rate of new agricultural technology is constantly increasing. A market research report by Robert Hill of Caledonia shows: Between 2013 and 2019, growers will double the use of new technologies. 51% of respondents said they are very interested in technologies related to their vital interests.

Many new companies take collecting, aggregating, and analyzing data from different farms as their main business. Their goal is to provide personalized services for different crops in different farms by collecting farm climate, soil, crop, and income data. Data collected from farms helps data companies improve their models and provide better services. Based on data, these companies constantly adjust products to meet different customer needs.

Here are a few typical companies in this field:

• Farmers Business Network: Agricultural information technology service company, helping farmers develop the best planting strategies and obtain the best returns (received $24 million in investment).
• 100M in venture funding to be acquired by Monsanto in 2013 for $1bn). (Note: There seems to be an error in the original text here, likely referring to The Climate Corporation acquired by Monsanto).
• Granular: Service platform providing visual data and decision reference for farmers (received $50 million in investment).
• Conservis: Cloud-based service platform, providing information tracking and data analysis services for farmers (received $126.5 million in investment).
• Trimble: Providing positioning solutions for surveying, construction, agriculture, and public safety.
• Farmers Edge: Software and hardware service platform. Providing data collection, analysis and aggregation, etc. (received $4.42 million in investment).
• Iteris: Providing information such as weather, water, soil, and crop growth status for farmers by calling APIs or APPs.
• John Deere, Bayer, BASF, DuPont, etc. are also creating their own data service platforms through self-construction or acquisition.

Food Traceability

Trace the circulation process of food from farm to consumer, prevent and control diseases, reduce waste, and increase income. With the growth of the supply chain, agricultural product traceability becomes increasingly important. Big data is being widely used in fresh produce warehouses and cold chain transportation links. Producers and transporters use sensors, scanners, and analysis software to monitor and analyze data on the food supply chain. Temperature and humidity sensors with GPS positioning functions monitor the environmental parameters of storage and transportation links, and provide timely early warning of abnormal conditions.

Impact on the Supply Chain

The largest agrochemical companies are facing challenges brought about by new technologies such as big data. These new technologies help farmers solve the problems of what to plant, how to plant, and how to plant, and help farmers obtain maximum benefits with minimum inputs. In the past, technological innovation was concentrated in large companies with R&D strength. Now, small companies have also begun to step onto the stage of technological innovation, especially in gene technology and genetic breeding.

Traditional large agrochemical companies may not necessarily be able to provide farmers with the best agricultural means of production and services. Innovation helps new companies create more possibilities. First, because farmers want their data privacy to be well protected, they do not like large companies that provide them with means of production to control these data. Crop gene data is the same. Even if independent seed companies are willing to contribute their own data to public databases, it does not mean they want these data to be used by giants. The second reason is that everyone wants to see objective and fair views and two-way flow of information. Even if large companies can develop the best data platforms, it is difficult to provide objective and fair information.

There are many examples showing that large companies cannot adapt well to the changes brought about by new technologies. The application of new technologies requires different completely different cultures, working styles, and behavior patterns. Previously, large agricultural companies could use cumbersome technologies and large R&D engines to study genetic traits. Now, using gene technology and cloud biotechnology, small companies can also carry out related work using few equipment. Another example is that the traditional supply chain will also undergo changes. In the existing circulation process, manufacturers, distributors, and retailers have caused price confusion and opaque channels. Just as Google changed many industries and Uber and Lyft changed the way humans travel, big data will also change the circulation of agricultural means of production.

Large companies have begun a new round of integration. For example, Sinochem Group intends to acquire Syngenta for $43 billion. Dow and DuPont merged for $130 billion, and there may also be a merger between Bayer and Monsanto.

Summary

AgFunder’s investment analysis report shows that in 2015, there were more than 500 investment and financing events in the agricultural and food fields, involving an amount of $4.6 billion. Startups are carrying out many innovative developments in the fields of food, energy, and environment. Agricultural big data entrepreneurship is still in its early stages, and many fields have not yet been involved by anyone. However, big data entrepreneurship has entered the fast lane, and those entrepreneurs dedicated to using innovation to change traditional models may get good returns. I hope that the biggest beneficiaries of this revolution are innovators, the ecological environment, farmers, and consumers. This is the best time for agricultural entrepreneurship.

Published at: Jul 9, 2024 · Modified at: Jan 14, 2026