Soil Tech and It's Role in Regenerative Agriculture

Soil tech plays an essential but often undervalued role in soil health and sustainability.

Most farmers would agree that soil health is the bedrock of success in agriculture, whether it be yield or the quality of crops. Simply put, good soil combined with state-of-the-art farming strategies, high-quality seeds, optimal water and fertilizer levels, and ideal weather can mean a robust harvest, the goal of precision farming. Unfortunately, the antithesis of this, whether it be overfertilizing, using the wrong fertilizer, or over or under-watering, can lead to declining crop yields and lost revenue.

Specifically, how does Agtech bolster soil health? Innovation in this area can be broken down into three tiers:

Soil testing
Soil data acquisition and analysis
Data management

The upshot of using technology in soil monitoring can be immense. Understanding the details of one’s soil is even more critical under the realities of climate change. Soil erosion has been increasing due in part to climate change and certain farming practices (tilling the land or land clearing that includes grazing, logging, and mining).

Precision Analysis

Soil health analysis gives farmers more consideration and opportunities to care for their soil, whether cover cropping or reducing tillage. Finally, it indirectly promotes regenerative agriculture, which includes farming strategies that promote topsoil regeneration.

In recent years there have been a growing number of soil testing companies in the Agtech space. In addition, many companies incorporate science and machine learning in their products. This is good news for farmers. While soil testing is a pivotal component of farming, it has traditionally been relatively costly, considering the equipment and analysis involved.

Trace Genomics, a Bay Area-based company, uses artificial intelligence (AI) to analyze microbes in the soil and provides detailed analysis on soil sustainability. For example, it can list specific diseases in the ground, so farmers know what fertilizers to apply.

The company was started by Diane Wu and Poornima Parameswaran, two Stanford graduates who earned their PhDs in genetics and microbiology, respectively. The impact is that the product has the potential to save farmers money, resources, and time.

Persistence Data Mining Inc. (PDMI), a San Diego-based Agtech company, uses soil spectroscopy – measuring light absorption – for field soil testing. This is considered a less expensive alternative since infrared technology can work well for many samples, often in thousands.

Penelope Nagel, PDMI’s co-founder, notes that soil spectroscopy also “tests soil directly without altering the chemical state of the soil in the process.” As a result, “Farmers can test more samples in a field less expensively and see variations on a more granular level to promote actionable data to prevent yield lags and wasted inputs,” she says.

An Investment in Soil Tech

Investing in companies that focus on soil testing or analysis remains strong. Last year Hone, an Australian Agtech startup that provides real-time soil carbon testing using spectrometry, raised $4.7 million in capital.

Startups in the soil space have attracted a variety of funding channels, from federal grants to non-profits. In 2021 The Nature Conservancy announced that it had invested in several soil health-centric startups. The portfolio companies included Pattern Ag, which offers soil microbiome analysis and recommendations for farmers who grow corn and soybeans.

The connection between soil health and innovation seems clear to farmers and Agtech entrepreneurs. The Western Growers Center for Innovation and Technology (WGCIT) has hosted several Agtech startups in the soil space, including Trace Genomics.

“There is a relation between soil health and technology. Changes in the regulatory environment along with drought and climate change can lead to an increase in pest pressures, more or new disease pressures,” says Dennis Donohue, executive director of WGCIT. As a result, the innovation involving imagery, sensors, and machine learning that help collect and analyze data is much needed and valued. Inputs and new analytical tools “provide information to growers to make more informed decisions while the crop is in the ground,” Donohue notes. The goal is ultimately to attain sustainable soil that can feed generations in environmentally friendly ways.

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