Rajendra

I write columns on news related to bots, specially in the categories of Artificial Intelligence, bot startup, bot funding.I am also interested in recent developments in the fields of data science, machine learning and natural language processing ...

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I write columns on news related to bots, specially in the categories of Artificial Intelligence, bot startup, bot funding.I am also interested in recent developments in the fields of data science, machine learning and natural language processing

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Artificial intelligence for agricultural pest control in Spain

By Rajendra |Email | Aug 29, 2017 | 6258 Views

Spain's agricultural ministry has this month launched, for the second consecutive year, a pilot experiment using artificial intelligence techniques (AI) to anticipate the evolution of the olive fly pest. EURACTIV's partner EFEAgro reports.

Having access to predictive information on the behavior of pests is a very powerful tool for technicians and farmers with a view to integrated pest management, since it allows for better decision making, knowing the areas and dates of greater risk and impact, and designing control measures in a more efficient and sustainable manner.

To do this, big data collected by the Andalusian Plant Protection and Information Network (RAIF) on this pest and on other crop parameters is analysed and fed into an artificial intelligence model that is able to predict the pests behaviour up to four weeks in advance, through machine-learning techniques.

Data on the fly

The application of Big Data management techniques in agriculture, as well as artificial intelligence, are two fields with enormous potential for improving the efficiency and sustainability of the agricultural sector, according to the Spanish agriculture ministry.

With this project, Andalusia will pioneer the transfer of these technologies to the sector through the RAIF database.

This pilot project benefits the Integrated Olive Production Associations (APIs) working in the regions of Sierra Magina in Jaen and in the Eastern Highlands of Cordoba. The APIs will receive a weekly analysis that includes a prediction of the percentage of olives that will be eaten by the fly, as a parameter to take into account for integrated pest management.

The APIs will provide weekly information on the status of the pest and the crop in their member farms, that will in turn serve to improve the predictive model.

In total there are 12 Integrated Production groups, with 9,000 hectares of olive groves, so this experience will benefit 1,568 farmers in 10 municipalities in the province of Jaen and 9 in the province of Cardoba.

The Andalusian Phytosanitary Alert and Information Network (RAIF) is a project of the Ministry of Agriculture, Fisheries and Rural Development financed by the European Agricultural Fund for Rural Development (EAFRD), which provides updated information on the phytosanitary status of the main crops of Andalusia.

The network relies on the work and collaboration of about 700 field technicians, mainly from the production sector itself, as well as 4,621 control stations distributed in different crop areas, with which they exchange the information and data they collect.

Big data in agriculture

The European Commission hails big data in agriculture as a way to increase productivity, food security and farmer incomes

However, critics say the technology enabling the collection of big data (through sensors, drones, and expensive software) has the effect of expropriating farmers of information, and increasing their dependency on technology companies  as has already happened in the United States.

In a scientific study on precision farming, published in December 2016, the European Parliament recognised the need to regulate the ownership of agricultural data in a way that would benefit farmers.

Making farmers the owners of their data and providing opportunities to control the flow of their data to stakeholders should help build trust with farmers for exchanging data and harvest the fruits of the analysis of big data, it read.

Source: euractiv