We are land
keepers; fruit is
our profession.

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We need to capture more data for an efficient future in agriculture

In my last article, The future of agriculture and the involvement of young people, I pointed out the importance of applying new technologies and innovation within agriculture to attract young talent, which are integrated as strategic pillars for the sector’s sustainability.

The future of agriculture and youth involvement

According to data published by the FAO, minor (aging) farmers in developing countries produce most of the world’s food. They tend to have little resilience to adopt new technologies to increase the productivity of fields sustainably. On the other hand, the involvement of young people in agricultural activities has been a matter of interest in the international development plan due to the growing concern that new generations do not feel a connection and interest in agriculture.

IIn recent centuries, physical human labor and pack animals were the primary energy sources for agricultural work. Now, humanity has achieved technological innovations to support efficiency in the field, potentially improving the diagnosis and decision-making of agricultural producers. When machines are incorporated, farming operations can be performed with greater precision, leading to further improvements in efficiency and productivity.

The billions of dollars lost within the value chain

We are land keepers; fruit is our profession. Discover more information about our work. The billions of dollars lost within the value chain Enough food is produced worldwide to feed the entire population, yet nearly a billion people suffer from chronic hunger. This problem has different origins depending on the geographical area to which we refer; however, huge amounts of food are wasted within the value chain. According to an estimate by the FAO, a third of the food produced for human consumption is lost or wasted each year, worth 1.2 trillion dollars. On the other hand, nearly 14% of

The lack of data is always a limitation to analyzing the trends in the adoption of machinery; however, with efforts made by The Food and Agriculture Organization of the United Nations (FAO), we can classify the use of machinery into two groups:


  1. Engine-based machinery, such as tractors, water pumps, and harvesters
  2. Auxiliary machinery without a motor but combined with a motor-based machine (for example, tractor implements such as plows, seeders, and irrigation systems).

The adoption of motor technologies began in the United States (EEUU), reaching its peak from 1910 to 1960; This technological revolution within agriculture displaced approximately 24 million pack animals. Twenty years later, the use of motors began to explode in the United Kingdom and Northern Ireland in 1930, followed by Japan, Denmark, France, Germany, Spain, and the former Yugoslavia. At a later stage, many Asian and Latin American countries witnessed considerable progress in adopting powered machinery.

The most recent databases published by the FAO, subject to the warning made by the same institution where it recognizes that they are irregular and obsolete, the following graph shows the progress of mechanization in the regions of the world between 1961 and 2009. The indicator (number of tractors in use per 1,000 ha of arable land) does not consider the tractor’s size or other equipment types. However, using an indicator as a proxy for machinery may be justified partly by the need for more availability of additional data and the fact that tractors are currently the primary energy source for many agricultural operations, such as land preparation, planting, fertilization, and chemical fumigation. In addition to transportation, tractors can also provide power to pump water for irrigation.

The future of the mechanization of agriculture is subject to the ability to obtain data that we have within the industry. Fortunately, more and more companies are pioneering data collection and technology manufacturing for innovation and waste prevention. A great example is a technology proposed by Experience Fruit Quality, an intelligent data platform to integrate data and improve yield monitoring.




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