How can we use data for improving food production?

Food security is one of the hottest topics nowadays; with a constantly growing population that is expected to reach (and even exceed) 9 billion by 2020, and the traditional food production systems reaching their limits, new, innovative ways need to be followed in order to ensure that there will be enough food for everyone in the upcoming years. What is strange is that at the same time, huge amounts of food are going to waste on a daily basis; in EU alone, more than 100 million tones of food are going to waste annually.

Image source: http://ecosmartworld.com/new-law-france-forces-grocery-stores-reduce-food-waste/

Intensive and industrial agriculture exhibit higher yields of cultivated crops but the price is high: The (increasingly high) use of pesticides, insecticides, herbicides and fertilizers, among other chemicals, has its toll on the ecosystems, flora and fauna at a small and larger scale. Traditional crop varieties are replaced by hybrids resistant to plant pests and diseases; these hybrids are sterile and may be harmful to useful insects, disrupting the ecosystems. Even domain giants like Sygenta have realized the impact of the excessive inputs in agriculture and introduce initiatives like the Good Growth Plan, which makes use of data for allowing the reduction of inputs thus minimizing their environmental impact. On the other hand, the much safer and environmentally-friendly organic agriculture cannot provide alone the response to the increased demand for food, as yields are usually lower and the effort needed is higher, leading to increased (labor) costs.

Can data help address this issue?

The answer is yes and it seems that data can help in different ways. The use of data can help in making informed decisions and educate stakeholders; for example, the use of appropriate data can help in the identification of the most appropriate crop varieties for a given location, affect the amount of inputs required for pest & weed control, the volume of water for irrigation required etc. Such data can be collected through various means, such as sensors, maps (including soil and climate), related publications, reports, images (e.g. aerial ones) even social media (Twitter has been used for sharing data at a global scale). The example of the Good Growth Plan is a good one as it makes use of various types of data collected over the years in order to help minimize the harmful inputs used for increasing yields. The recently published Discussion Paper of the Global Open Data for Agriculture and Nutrition, titled "How can we improve agriculture, food and nutrition with open data?" also provides a wealth of examples where open data has contributed to a better (and cleaner) agriculture and food production.

A more radical approach comes from the Open Agriculture initiative of MIT's Media Lab, which is working on open source agriculture, by designing and building food computers that ensure the application of optimal environmental and nutritional conditions for plants cultivated in growth chambers; this allows the growth of e.g. vegetables under controlled conditions that have been considered as optional based on "recipes" or values that have been determined based on data aggregated from various sources as well as through testing and experiments. Needless to say that no pesticides, herbicides etc. have any place in this way of growing food.

According to Caleb Harper, Director of the Open Agriculture Initiative, "In the future, even broccoli will have an IP address. Ultra-efficient, sensor-packed urban farms will collect huge quantities of information on every crop they grow and develop data-driven insights into what makes a tomato tastier and a head of broccoli grow faster. That information will be shared, and global agriculture will improve". (You can read the full article here; if you have more time, just watch the video above).

The point is that data can indeed lead to a better and environmentally sound framework of food production; what we need are efficient means for collecting, organizing, analyzing & sharing data, as well as a mean for transforming this data into meaningful (and useful) recommendations that will drive the agricultural practices. This is not science fiction; it is something that already takes place (maybe in an unorganized way so far) so it is up to us to grab it, adapt it and use it.

Why am I telling you all these? I recently got involved in CAPSELLA, one of Agroknow's new projects which aims (among others) to support local communities of farmers and food producers in making informed decisions on their activities by allowing them to access related and high-quality data from various open data sources as well as social media. The project will work on making existing data more easily available to these stakeholders through innovative ICT solutions that will be built on their requirements. And we are referring to food producers that have opted to operate in a way that will benefit the environment and agrobiodiversity, respecting natural resources (so away from industrial agriculture) so they could use all the help they could get from existing data that will allow them to increase their yields and grow higher quality food.

It's all about the data after all, isn't it?