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Effectively conserving biodiversity with limited resources requires scientifically informed and efficient strategies. Guidance is particularly needed on how many living plants are necessary to conserve a threshold level of genetic diversity in ex situ collections. We investigated this question for 11 taxa across five genera. In this first study analysing and optimizing ex situ genetic diversity across multiple genera, we found that the percentage of extant genetic diversity currently conserved varies among taxa from 40% to 95%. Most taxa are well below genetic conservation targets. Resampling datasets showed that ideal collection sizes vary widely even within a genus: one taxon typically required at least 50% more individuals than another (though Quercus was an exception). Still, across taxa, the minimum collection size to achieve genetic conservation goals is within one order of magnitude. Current collections are also suboptimal: they could remain the same size yet capture twice the genetic diversity with an improved sampling design. We term this deficiency the ‘genetic conservation gap’. Lastly, we show that minimum collection sizes are influenced by collection priorities regarding the genetic diversity target. In summary, current collections are insufficient (not reaching targets) and suboptimal (not efficiently designed), and we show how improvements can be made.

Quantifying fruit shape is challenging, particularly when measurements are made on segregating populations of plants. Objective manual measurements can be performed on small samples of fruit, but this method is difficult and very time-consuming when dealing with larger samples or when shapes are complex or shape variations are slight. Subjective rating scales can also be used, but their effectiveness is questionable when done by multiple raters resulting from varying descriptive standards among individuals. Therefore, a method was developed to analyze digital images containing multiple fruits to characterize fruit shapes. Each segregant of a population of table grapes (Vitis spp.) with parents of wide shape variation was photographed and analyzed for shape using SigmaScan® software. The program discriminately selected image pixels representing the fruit and determined the area and perimeter of a grape berry, which were subsequently used to calculate the major:minor axis ratio, shape factor, and compactness values. Computer findings were compared with data from human raters using a simple correlation. When compared with the human ratings, results showed strong correlations of r = 0.941 for major:minor axis ratio, r = –0.804 for shape factor, and r = 0.744 for compactness. This analysis method was a reasonably quick and simple way to quantify grape berry shape, yielding valuable phenotypic data in numerical form. This technology should be useful for shape characterizations in other fruits as well.

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