Soil degradation is a growing threat to agricultural productivity, smallholder farmer incomes, and global food security. Varied estimates suggest that 20-40% of the Earth’s land area is either degraded or degrading, and around 70% has been altered to some degree.¹ Furthermore, since healthy soil is a key carbon sink, land degradation contributes to increased GHG emissions that fuel climate change.
Ironically, though existing food systems are impacted by this degradation, they also contribute significantly to the degradation of soils, especially those under conventional agricultural practices. Statistics suggest that global food systems represent roughly 80% of deforestation, 70% of freshwater use, and are the largest contributor to biodiversity loss.²
There are many ways to reduce degradation; regenerative agriculture represents one of our best options. Earlier this year at the 2022 ICTforAg conference, along with sector experts, we shared our perspective on how digital tools can facilitate the transition to regenerative agriculture and contribute to improved soils. Watch the full ICTforRegenAg presentation here.
Finding solutions to degradation in regeneration
Regenerative agriculture is an approach for restoring land quality and soil health that has been rapidly gaining momentum in food systems. Regenerative agriculture is a holistic agricultural approach that restores and maintains ecosystems in a healthy and resilient state with a focus on soil health. And the approach creates social and economic impact at the farmer level.³
Growing evidence indicates that the adoption of regenerative agricultural practices has several benefits beyond soil health, including improved yields, greater resilience against climate and weather impacts, and a reduction in emissions from food systems.4, 5 It can also be argued that by reducing dependence on external inputs and the corresponding price volatility, these practices could also improve the economic resilience of farmers.
However, there are several roadblocks that make the transition to regenerative agriculture challenging. Most importantly, the transition is often accompanied by the risk of temporary yield losses due to a shift in practices, which can result in lower farm-level revenue for the first few years. Furthermore, if the transition is not facilitated with sound technical know-how and risk-mitigation strategies, it may lead to longer-term damage to productivity and income. These risks are exacerbated by the fact that smallholder farmers in low- and middle-income countries often do not have the capacity or resources to make the needed investment and weather cash flow shortages that may result from productivity losses.
Using digital tools to smooth the transition to regenerative agriculture
Growing interest in digital tools in agriculture represent an opportunity to scale up the adoption of regenerative practices. In 2020, IDH in partnership with GSMA profiled over 700 digital service providers from the Global South that are offering a wide range of services, including extension support, market linkages, access to finance, tools to improve the efficiency and commercial viability of smallholder farming and reduce the environmental footprint of agriculture.6
Though regenerative agriculture and digital agriculture don’t appear to be natural partners at first, there are several synergies that can support the scaling up of both. There are multiple ways that digital tools can be used to facilitate a smoother transition as smallholders adopt regenerative practices.
Here are six of these use-cases to show how digital tools can be used to facilitate the transition:
- Using communication channels to standardize production principles: The transition to regenerative agriculture from conventional requires an increased awareness at the origin of supply chains and followed subsequently by a shift in production principles such as no-till cultivation, mulching, on-farm composting or cover cropping. There is also a requirement for to follow these principles at a landscape level, hence, requiring some-degree of standardization based on localized contexts. In these scenarios, digital tools can be used to standardize and provide extension services via SMS, Unstructured Supplementary Service Data (USSD), Interactive Voice Response, or bulk-messaging channels such as WhatsApp. Compared to in-person training, digital tools can be cost-effective, allow for mass-outreach, and limit deviation from the core message.
- Applying data-driven prescriptive and predictive advisory to mitigate production risk: Technologies, such as remote sensing and Internet-of-Things (IoT), can support the collection of localized data, including soil composition, weather, biodiversity and more. This localized data can inform customized prescriptive advisory to smallholder farmers. Data-backed advisory can also reduce the costs associated with nutrition, pest, and water management and increase productivity. Alongside prescriptive support, the data collected across farming seasons coupled with machine learning can be used to provide predictive advisory for pest and disease management, which allows farmers to take pre-emptive action to mitigate productivity risks. It is important to note that accurate modelling requires large quantum of structured data, which could take several years to accumulate. Data-sharing partnerships and open data ecosystems are a way to facilitate the quicker development of such data stacks for public good (Read our previous blog on data sharing here.).
- Introducing digital aggregation and market linkages to improve the economics of sourcing: To create a sustainable business case for regenerative agriculture production, producers must deliver consistent supply with sufficient volumes. However, it is difficult for smallholders to achieve the necessary volumes without aggregation. By digitizing farm data to optimize logistics, it is possible to predict production volumes, provide quality assessments and inform potential buyers in advance of harvest. Based on these commitments, digital tools can be used to link regenerative agriculture programs with other stakeholders, such as financing organizations, donors, and civil society. SourceUp, which launched last year, is a platform that connects sustainable and regenerative agriculture sourcing areas to like-minded partners globally.
- Building economic resilience through data-backed finance and payment: A key challenge for transitioning to regenerative agriculture is the lack of available finance to initiate and de-risk the transition. Digitalized farm data and remote monitoring, can create transparency on a farmer’s business model and potential risk, which can improve farmers’ credit-worthiness. This information can be used for loan origination and connecting farmers to financial institutions. Furthermore, if market linkages are established in advance, buyer commitments can be used to partially offset risks and make credit more affordable.
Besides commercial capital, there are IoT use cases where sensors can trigger result-based financing when farmers follow specific practices. For example, irrigation systems can be equipped with IoT sensors that monitor water usage and reward farmers that optimize water usage. Similarly, IoT based smart contracts can automatically trigger payments if certain outcomes, such as improved soil health, are achieved. The latest use-case for digital tools is in facilitating trade on carbon markets. Digital tools can reduce the costs for monitoring carbon sequestration, certifying carbon credits, and enabling transactions between buyers and sellers.
- Leveraging end-to-end traceability for price-premiums: Digital platforms can help regenerative agriculture programs connect with global buyers offering price premiums. Farm-to-fork or jurisdictional traceability are a prerequisite for such premiums. Digital traceability solutions enable buyers to map whether produce is sourced from a verified or certified sourcing area and build an assurance value for premiums to be paid. These price premiums could help farmers overcome some of the risk of revenue loss from transitioning.
- Using remote monitoring for course-correction and learning: For instance, there are use-cases for checking plant health, changes in soil composition, change in fallow land, and other sustainability indicators. This data helps farmers understand if practices are achieving the desired results and also allows for timely course correction. Digital tools can also enable affordable true-cost accounting of production costs, which can be used to build a business case for price premiums. In the absence of digitalization, collecting and analyzing of such data is expensive, and often time-delayed.[As a disclaimer, it is important to highlight that satellite-based remote sensing, currently may not be as accurate for smallholder farms that are not uniform, have multiple crops, have cover cropping, and ground vegetation, as compared to organized mono-crop farms.]
The article leverages insights from the IDH co-curated Session on ICTforRegenerative Agriculture at the ICTforAg2022 Conference. The session was made possible due to contributions of the following speakers:
- Annelies Withofs, Programme Manager, IKEA Foundation
- Kunal Prasad, Chief Operating Officer, CropIn Technologies
- Tanja Lubbers, AgroCares
3 Please note: Regenerative agriculture in and by itself does not necessarily create this impact; hence, it is important to be intentional towards these impact areas while delivering a regenerative agriculture program.