For millennia, humans have modified plant genes in order to develop crops best suited for food, fiber, feed, and energy production. Conventional plant breeding remains inherently random and slow, constrained by the availability of desirable traits in closely related plant species. In contrast, agricultural biotechnology employs the modern tools of genetic engineering to reduce uncertainty and breeding time and to transfer traits from more distantly related plants.

Agricultural biotechnology and, specifically, the development of genetically modified (GM) crops have been controversial for several reasons, including concerns that the technology poses potential negative environmental or health effects, that the technology would lead to the (further) corporatization of agriculture, and that it is simply unethical to manipulate life in the laboratory. GM crops have been part of the agricultural landscape for more than 15 years and have now been adopted on more than 170 million hectares (ha) in both developed countries (48%) and developing countries (52%).

Genetically engineered (GE) foods apply new molecular technologies to Widely adopted in the United States, Brazil, and Argentina for the p corn, soybeans, and cotton, they are practically banned in Europe and tigh throughout the world. We have found that GE foods have significantly incr of corn, soybean, and cotton, and lowered their prices, thus improving food foods have already contributed to a reduction in the use of pesticides and

The evidence base on agri-food systems is growing exponentially. The CoSAI-commissioned study, Mining the Gaps, applied artificial intelligence to mine more than 1.2 million publications for data, creating a clearer picture of what research has been conducted on small-scale farming and post-production systems from 2000 to the present, and where evidence gaps exist.

A range of approaches and financial instruments have been used to stimulate and support innovation in agriculture and resolve interlocking constraints for uptake at scale. These include innovation platforms, results-based payments, value chain approaches, grants and prizes, incubators, participatory work with farmer networks, and many more.

Innovation for sustainable agricultural intensification (SAI) is challenging. Changing agricultural systems at scale normally means working with partners at different levels to make changes in policies and social institutions, along with technical practices. This study extracts lessons for practitioners and investors in innovation in SAI, based on concrete examples, to guide future investment.

A huge increase in investment in innovation for agricultural systems is critical to meet the Sustainable Development Goals and Paris Climate Agreement. Most of this increase needs to come from reorienting existing funding for innovation. However, understanding whether an investment will fully promote environmentally sustainable and equitable agri-food systems can be difficult.

Finance is a key lever for turning agriculture from a potential source of environmental harm and social inequity to a driver of conservation and social inclusiveness. Private and public sector funding for farmers to combat climate change and protect and restore nature (‘Paying for Nature’) is rapidly increasing. Yet this new funding may not reach its aims without drastically improving farm-level reward mechanisms.