When I first moved to Spain many years ago, I inadvertently shocked several of my colleagues by wanting to conduct experiments using a randomized design. They were used to planting a continuous list of entries and making decisions based on averages, so instead of responding with “Of course, she wants to randomize her experiment,” they said, “Oh, she wants her experiment to be disorganized.”
I found out the hard way that not everyone makes decisions in the same way. Wheat breeders, for instance, don’t choose between two varieties by going into a field and saying, ‘Wow, this wheat looks beautiful’. Not a chance. But a vegetable breeder very much takes the shape of the fruit or the look of the plant into account. It’s a huge difference between the two types of breeders.
Experimental design and data analysis are critical to everyone engaged in agricultural research regardless of whether someone is working with canola or tomatoes or bananas. It ensures that the decisions being made are based on solid evidence to back what the eyes are seeing or the gut is telling you. Data analysis is often key to determining whether the differences between two varieties are as important as they may at first seem.
I firmly believe that vegetable breeders don’t use statistics nearly enough. Statistical analysis helps us determine whether differences we observe among varieties are truly significant or simply due to chance. It’s what allows us to decide, with confidence, whether it makes more sense to advance the plant with the best disease resistance, the one with superior overall quality, or the one that’s easiest to harvest. Sometimes, the prettiest eggplant or the cucumber that produces the most fruit isn’t what the farmer needs most. The variety that performs more consistently under drought conditions or the one that naturally attracts pollinators without requiring hormonal sprays might ultimately be the better choice.
Even if a breeder ultimately determines that a plant’s aesthetics are vital to a farmer’s success, it’s important that the data collected from well-designed field trials are thoroughly analyzed and stored in a centralized location accessible to every member of the team. This ensures that key decisions about which varieties to advance are made with everyone looking at the same reliable information.
At the end of the day, it doesn’t matter whether you breed vegetables or cereals. Success comes down to the same principle: the better your data, the better your decisions.
