Training future plant breeding researchers

With all the complexities facing the world from climate and environment changes to how we feed the world, one thing is clear – we need research in order to plan effectively. And research needs well trained researchers; people who understand agricultural issues and concerns, and who know how to research effectively. GenStat is known as a key research tool for many agricultural and other bioscience researchers, but I was delighted to find GenStat also has an important role to play in the teaching of these areas.

A key user of GenStat is the IAMZ in Zaragoza, Spain, whose main aim is to train people in how to do research. The IAMZ stands (In Spanish) for the Mediterranean Agronomic Institute of Zaragoza, it is one of the 4 sites of the CIHEAM (International Centre for Advanced Mediterranean Agronomic Studies). The main purpose of the CIHEAM is “to develop cooperation between Mediterranean countries through postgraduate training and promotion of cooperative research in the field of agriculture and natural resources.” As a part of this the IMAZ develops Master programmes and advanced courses for professionals designed to update and further the training of researchers in agriculture and its related sciences.

Students come from all over the world to study for the Master programmes, some are straight from their first degree and wish to complete their education, and some are already at work and wish to update their knowledge and understanding of agricultural research. I spoke with Dr Ramzi Belkhodja from the IMAZ, who heads up the Master in plant breeding. The programme covers several areas, one of which being statistics and the use of statistics in plant breeding research. Dr Belkhodja and his colleagues recognised the need for anyone either in plant breeding research or planning on entering the field, to have a good understanding and grounding in statistical methods.

Currently the team teach their statistics course using GenStat. Given GenStat’s history in agricultural research it is perhaps no surprise that it is used as the phraseology and terminology reflects the language used in the biosciences. GenStat contains a huge range of statistical techniques; in fact you would be hard pushed to find a statistical test or routine not included in GenStat. However, it isn’t just GenStat’s inherent statistical strength or its history that makes it so useful to Dr Belkhodja and his colleagues.

GenStat’s straightforward Windows menu system means that the statistics is easy to teach and importantly easy for the students to pick up and understand, indeed Dr Belkhodja told me that the students are up and running with GenStat and statistical techniques within 3 teaching sessions. The self-explanatory menu system means that the statistical methods and concepts are easy to manage and understand. Combined with the speed and ease of importing any data from Excel (for example) into GenStat, and the lecturers at IMAZ can spend less time on the complicated syntax and more time on the analysis itself.

Given the students come from all over the world; GenStat also provides an added advantage for those coming from the developing world. When the students return, they can obtain a free copy of GenStat – as GenStat Discovery, to continue their research. So, in a world where “time is money”, students don’t need to learn a new package in their work environment; they can implement their learning and statistical understanding in a package they already know and trust.

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