The project we are featuring below is implementing Italian precision agriculture technology in Brazil, with the potential to reduce the use of water, fertilisers and pesticides in the field by up to 20%. The initiative is a partnership between Brazilian consultancy Gregori Consulting Group and Italian company Agronica, with support from Clust-ER Agrifood, which promotes innovative solutions in the Emilia Romagna region. Rio Grande do Sul will be the first state to benefit from the technology that allows the use of big data through the collection of environmental data that help to create Decision Support Systems, fundamental for the organization of more efficient processes in agriculture.

Learn more in our interview with Fabrizio Paglierani, director of Agronica, and Roberto Gregori, Chief Executive of Gregori Consulting Group.

1 - Tell us how the partnership with Agronica emerged in the development of the project supported by Low Carbon Brazil that intends to bring an Italian solution of precision agriculture to the Brazilian agricultural sector. (Roberto Gregori)

The partnership emerged at the Low Carbon Business Action in Brazil Matchmaking event held in São Paulo in 2017.

2 - What was Low Carbon Business Action in Brazil's contribution to this process? Mainly, how did phase two contribute from a technical point of view in the commercial aspect of the project? (Roberto Gregori)

Phase two helped to implement the pilot phase in Camaquã (Porto Alegre) and to understand the commercial potential of precision farming equipment, such as monitoring stations.

3 - The description of the project in partnership with Agronica states that it is estimated that the country adopts precision farming practices in about 20% of agricultural areas. How do you view this scenario and the potential of using technologies like Agronica's for Brazilian agriculture? (Roberto Gregori)

20% is an important goal. Today in Italy it is less than 5%, but precision farming practices are increasing. They are important for reducing production costs and for achieving a better environmental impact.

4 - What new features this European technology brings to Brazil? What would be the main obstacles in the use of this type of precision agriculture technology in Brazil? (Roberto Gregori)

The solutions promoted by this project are "integrated" precision farming solutions, with software that can give complete answers to the farmer. This includes technical advice for use of water, fertilisers, treatment against diseases, administrative and economic management, quality standard.

5 - Could you mention, in figures, the main gains the ICT solution developed by Agronica can generate in terms of reducing the use of water, fertilisers and pesticides? How does the less efficient production process impact the operation of farmers who do not adopt this type of technology? (Roberto Gregori)

We estimate a gain of up to 15-20% in the reduction of the use of treatments, fertilisers and water. In addition, even the consumption of gasoline in the machines can be reduced.

6 - How have Brazilian farmers dealt with the topic of environmental responsibility in the field? Do they believe there has been an effort on the part of producers to make systems more intelligent, efficient and with less environmental impact? (Roberto Gregori)

Farmers have paid the utmost attention to reducing costs. When they also have the perception of the least environmental impact, it will be even better.

7 - Where do you intend to implement the project initially? Which Brazilian region would have greater demand for this type of Agronica solution and greater potential to benefit from it? Also, in which other country in Latin America are you already operating or intending to introduce the technology in the upcoming months? (Roberto Gregori)

In Rio Grande do Sul, where the pilot project was installed, then in São Paulo and Campinas. In the future, thanks to contacts with partners there, it would be interesting to implement it in Uruguay.

8 - What are the main needs and challenges of the Brazilian agricultural sector in terms of modernization and production? Do you believe technology can make the whole chain more dynamic? (Roberto Gregori)

Yes, technology will help, by means of precision farming and machinery with sensors. The potential for growth is very high.

9 - Please explain didactically what "precision farming" means in practice and which technologies are the most promising in this area? (Fabrizio Paglierani)

Precision farming is a management concept based on observing, measuring and responding to inter and intra-field variability in crops. In other words, the concept of precision agriculture is based on four pillars – Right place, Right source, Right quantity and Right time. A better name for precision agriculture might be “site-specific agriculture”. Growers are able to take large fields and manage them as if they were a group of small fields. This reduces the misapplication/overapplication of inputs and increases crop and farm efficiency. Precision agriculture practices can be applied to nutrients, water, seed, and other agricultural inputs. There is a lot of technology used to implement precision farming like:  GPS-computer guided tractors and harvesters  Electromagnetic soil mapping and soil sample collection  Crop yield data collection  Aerial imagery (drones or satellite)  Field humidity maps. Each of these geo-referenced data layers help subdivide a large field area into smaller management zones. Using small management zones reduces waste while increasing production potential. Using these zones, geo-referenced prescription maps can be produced to manage site specific fertilisation, irrigation, treatments and so on.

10 - How has Italy's Clust-ER Agrifood helped internationalise innovative technologies for the agricultural sector in other countries and why is Brazil an important market? Which other Latin American countries are Clust-ER Agrifood's target markets? (Fabrizio Paglierani)

Clust-ER Agrifood is a non-profit association composed of 71 members operating in public or private environments: universities, innovation centres, enterprises, both individual and aggregated in associations, and vocational training bodies. The aim of Clust-ER Agrifood is to promote innovation in the agri-food systems, strengthening synergy among its members, and also to enhance international cooperation with key actors. In this respect, an internationalization strategy has been prepared, and Brazil is one of the main target countries, in consideration of the experience of some key actors, and the huge potentiality in terms of growth and sustainable agriculture. Other Latin American countries are in the list of international cooperation, such as Peru with some institutional missions of Clust-ER Agrifood in 2018, and Argentina (particularly with Bologna University, member of Clust-ER Agrifood).

11 - What is the importance of Clusters in promoting an environment of sectoral innovation? (Fabrizio Paglierani)

Clusters play a key role in the promotion of open innovation, allowing members and particularly small enterprises to enter in strategic partnerships, with the possibility for all partners to benefit from the projects’ results, i.e. innovative solutions and tools for a more sustainable agriculture. Precision farming is one of the main priorities, and Clust-ER Agrifood aims to enhance the knowledge among farmers and also the possibility for SMEs to participate in demonstrating actions and to directly perceive the benefits of innovative solutions.

12 - The systems developed by Agronica allow collecting varied production data and environmental conditions. What are the main benefits of Decision Support Systems, one of the solutions that can be created from big data in agriculture? (Fabrizio Paglierani)

In the GIAS Agronica platform, DSSs improve efficiency and speed of decision-making activities. We say Efficiency is improved because decisions are made on the basis of rational parameters, using consolidated knowledge models tested in different conditions. Especially in situations of current climate change, the farmer's experience may not be sufficient to dominate the change and relying on traditional practices can lead to errors that affect the profitability of the production. Speed is also improved because the DSSs of the Agronica platform produce clear and easy-to-read information in a practical way that can be directly used in the farming practice. The results of DSSs are organised in widgets displayed in the main dashboard which provides concise information about what to do in the fields. The widgets provide also access to detailed information reported with tables and charts. The purpose is to smoothen the decision-making process for management, operations, planning, or optimal solution path recommendation. It helps farmers to solve complex issues related to crop production.

For instance, the DSS for precise irrigation provides a real-time irrigation schedule: day-by-day information on how much and when to irrigate farm crops. By means of the web interface, users can fully interact with the system storing plot geolocation, crop, soil and irrigation system information. Users can also register the irrigation gifts and crop start dates to tailor the irrigation schedule. The system is able to integrate local soil moisture and meteorological sensor. On the cloud the user data is integrated with meteorological information, water availability and water table depth, allowing the system to build up the daily irrigation schedule in real time.

DSSs for pest control provide information concerning the main crop adversities, insects and fungi. Pest models serve as basis for decision making because they offer means to predict the exact time of pest phenological development and initiate management actions. Most models are climate driven and the meteorological data are combined with pest models through forecasting algorithms providing the user with real-time pest warnings and recommendations for management actions. DSSs make pest control more sustainable by avoiding unwanted consequences of pesticide applications.

13 - Would you have examples of how the production of several crops, such as rice rotated with corn and wheat works in Europe? How does technology allow this practice to be adopted efficiently? (Fabrizio Paglierani)

Italy is an important rice producer in Europe, in particular in the Piemonte and Lombardia regions, but also with a smaller but important production in Emilia-Romagna. There are some important examples of testing rotation between rice and other crops such as maize, wheat and corn, particularly in Lombardia and Piemonte. The results have been positive, coordinated by Ente Risi Italiano (Italian Rice Association, managed by the Italian Ministry of Agriculture, (https://www.enterisi.it); encouraging results have regarded the benefits in terms of weed control and quantitative and qualitative yield. In addition, these actions are supported by public funding, creating therefore a positive multiplying effect for the development of private investments.

14 - How does Agronica's technology of monitoring, collection, management of meteorological data and forecast, as well as information from field maps and sensors in the soil (humidity, temperature, soil nutrients, etc.) work? Can the solutions be implemented according to the farmers' needs? (Fabrizio Paglierani)

The GIAS main approach is to integrate in a friendly interface all the aspects of farming and post-harvest activities enabling stakeholders of food chains to access all the data they need and sharing the information along the chain. GIAS is a smart agroindustry platform able to support the management of complex processes that typically take place along a food production chain. From the farm, for agronomic operations, to decision support, up to the management of documentary aspects to get to the supply of services of interest to actors downstream of the production component (transformation, marketing).

The targets of the platform are the following:  reducing and preventing risk situations for crops deriving from biotic and abiotic attacks  reducing the amount of agronomic inputs for a sustainable farming practice  increasing the profitability of the agricultural activity thanks to greater effectiveness and efficiency of the various operations carried out by the operator  increasing the quality of production through the implementation of tools capable of ensuring a more accurate management of crop needs in the production process  simplifying the administrative and management aspects by integrating them into the IT platforms  providing other subjects external to the food chain with tools to assess farms on their commitment in terms of efficiency of the production process and compliance with the food protocols  implementing food traceability from fields to fork providing the buyers/consumers with all the information on product origin and quality aspects they want.

The wide range of topics GIAS deals with requires a very high degree of customisation according the users’ needs. The tailoring and tuning of solutions are ensured by a huge number of configuration parameters and software drivers to connect automatically with sensors data, operational machines and other farm data.

15 - How would the integration of technological solutions for the improvement of agricultural processes be done? (Fabrizio Paglierani)

Based on our twenty years of experience, it is always preferable to adopt technologies in small steps. The first step is to implement mandatory aspects that are requested by those who acquire the product. For instance, the digital field logbook and the documentation for proving the compliance with the production protocols. The second aspect is to manage farming practices using the DSS for fertilisation, irrigation and pest control. Third is to implement farm business management tools to assess profitability of crops.

All those steps require a fairly rapid training of operators and allows them to have the entire farming process under control. In this stage, the wide use of sensors for site-specific data, which can detect microchanges in field conditions on a zone-by-zone basis, is mediated by the operators who make the decisions and implement them based on the data provided by GIAS.

A stronger level of integration overcomes this approach in which farmers have to interpret the data provided to program farm equipment to act on it, going towards machines that work more autonomously to maximise application effectiveness and minimise the risk of damage. This new approach is still under development, but it is already possible to apply it, for example, by directly interfacing the irrigation or fertigation systems that are started and stopped according to the irrigation models provided by the DSS or the prescription maps sent to the pivot irrigation system or to the tractors for the fertilisation applications.

16 - Could you explain the possibility of creating a georeferenced map, which would allow farmers and technicians to consult the data and information to obtain technical advice for the adoption of more effective and sustainable practices? How could this system be integrated into the chain? (Fabrizio Paglierani)

In the GIAS platform, information is organized into analytical information stored in special database tables (crops, soil, sensor data, fields operations…) and geographic information organized in a Web-GIS module acquired in vector format (field shape, satellite data…) and/or in raster formats. The data is always georeferenced with absolute GPS coordinates. An example of georeferenced maps that can be used by operators are the prescription maps of variable rate distribution plans within the plot of organic fertiliser.

17 - What is needed by producers to implement the precision farming system developed by Agronica? How does it impact the additional cost of this implementation and also, how is the additional investment return obtained? (Fabrizio Paglierani)

Farmers using traditional crop management systems have consistent production costs, representing often a risk for the economic rentability and therefore for their presence in the markets. The systems offered by Agronica are easy to manage, in consideration of their simple structure and the possibility to manage them using smartphones or computers. In addition, Agronica provides a continuous technical assistance to farmers, also with the support of local partners in Brazil.

18 - In general terms, what are the main challenges in implementing innovative solutions in the agricultural sector? What would be the main obstacles? (Fabrizio Paglierani)

The actual growth and proliferation of precision farming has not been as robust as was expected earlier. The sector faces several key challenges/obstacles:  Interoperability of different standards  The learning curve: for the average farmer, setting up the necessary IoT architecture and sensor network for his field(s) can be a big ask.  Connectivity in rural areas  Making sense from big data in agriculture through the use of DSSs  Size of management zones for precision farming depending on available data and characteristics of the operational machines  Lack of scalability and configuration problems: farms can be of different sizes, a single owner can have a large crop-growing land, along with several smaller lands.  The security factor: the presence of malware and data thefts is a risk in practically all types of ‘connected systems’, and smart agriculture is not an exception from that.

The last (and main) obstacle is represented by the benefits of precision farming not immediately apparent. Unfortunately, there is almost no way to guesstimate the benefits of precision farming over the long-run and the benefits do not become apparent from the very outset. For this very reason, many landowners still view the use of advanced technology in agriculture as ‘risky’ and ‘uncertain’, and stay away from adopting it. With greater familiarity with agritech and comprehensive training, such fears should go away.

The concerns listed above have been taken into account in the development of the Agronica GIAS platform which provides practical answers to the challenges in the adoption of digital agriculture.

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