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Moving Toward a Digital Ecosystem
In the 25 years since it became commercial reality, the enabling technologies of precision agriculture have vastly improved processes on the farm. In the busy planting, treatment, and harvest seasons, 24-7 auto-guided operations are now nearly standard practice with most dealers and with a majority of farmers.
Precision agriculture for agronomy, however, seems to lag. Imaging, soil sampling, and the use of sensors for improved decision making still linger at a 20% to 30% adoption rate with the share of variable-rate applications even lower.
Spatial precision has improved from one soil sample per 2½ acres to below-inch pixel size from drone images. But farmers still only have a very small number of temporal observations in the year – a yield map and maybe a few images. They track the weather but don’t track the effects of the weather during germination, emergence, and tasseling since they may not have the tools.
Think Outside the Box
Yet, there are regions increasing the number of observations during the crop season. Following are three examples.
Chile. AgroBolt uses sensors on sprayers and drones to monitor the canopy of tree crops weekly. The technology forecasts yields and crop quality, improves the efficiency of irrigation systems, optimizes fertilizer applications, and detects pests and diseases early to balance efficacy and selectivity of treatments.
Europe. VineScout is testing a multispectral sensor-equipped robot to operate weekly passes in vineyards to track crop vigor and grape quality from early spring until close to harvest. It improves irrigation decisions and disease/pest control in organic crop production of high-value wines. It also tracks the tolerance of different wine varietals to the changing climate.
Japan. A university and companies (e.g., Topcon, Panasonic, and Iseki) have equipped rice transplanters with sensors to track the detailed situation at transplanting and then the growing crop. Next, the technology compares how later variability can be related to earlier observations. Eight observations are currently managed during the growing season.
Ag’s Integration Problem
While these ideas will find their way into big-acre crops like corn, soybeans, and wheat, integration has always been an issue in precision agriculture. Why would competitive seed companies, equipment manufacturers, or distributors allow farmers and dealers to integrate data?
The problem goes deeper than software and data formats. How can data be integrated relating to soil preparation and planting, fertility, seed and traits, plant protection, harvest, and storage? Who can claim the value created and with what rules? Who can charge for the service?
Consolidation allows integration. The big four are consolidating breeding, biotech, chemistry, biologicals, and data science. To what extent will this also lead to integration of precision ag benefits at the farm level?
Competition among the big four may ultimately make it happen.
This goes even further in China. Sinochem (parent company of ChemChina, Syngenta, and Adama) also includes SinoFert, China Seed, and MAP (Modern Agriculture Platform). With 150 local units already operational, Sinochem will build 500 MAP technical centers and 1,500 demonstration farms across China in the next three to five years. They will feature advanced equipment and robots for rent or as part of an application/service package. When will this model be replicated elsewhere and under what brand?
In Brazil, a multibrand database has been created to integrate data generated by equipment and sensors from all manufacturers. The BDCA database will be managed by ABIMAQ (Brazilian Machinery and Equipment Industry Association). Led by seven agribusiness companies, it is expected to be available to farmers in 2020. The hope is that non-Brazilian companies will comply to the common format when operating in the country.
Two recent examples of integration are also worth mentioning. BASF’s Xarvio digital farming solution is collaborating with Nutrien Ag Solutions. Corteva and John Deere are investing in technology solutions to help African farmers improve productivity and meet consumer needs. These positive initiatives, it is hoped, will lead to better outcomes in terms of higher yields, lower production costs, quality of production, and better use of capital and human resources. Ultimately, this should drive a more profitable implementation of precision agriculture for and by farmers.