Image dataset: Optimizing growth of nonembryogenic citrus tissue cultures using response surface methodology

Abstract

The data are images of Valencia sweet orange nonembryogenic tissue grown on different culture media that varied in the composition of the mineral nutrients from three experiments. Experiment 1 was a 5-factor d-optimal response surface design of five groupings of the component salts that make up Murashige and Skoog (MS) basal salt medium. Experiment 2 was a 3-factor d-optimal response surface design of extended ranges of factors 1, 2, and 3 from Experiment 1. Experiment 3 was thirteen formulations that were predicted using the prediction model generated from the 5-factor RSM from Experiment 1. The predictions were for two types of growth. One, points were predicted where growth was equal to MS medium (the standard), and two, points predicted with growth greater than MS medium by a minimum of 25%. An image representative of each formulation in each of the experiments makes up the dataset. The data will be useful for 1) visualizing the effects of the diverse mineral nutrient compositions, effects that may not be fully captured with single measure metrics; 2) development of image analysis applications via computer vision and segmentation algorithms for additional insight or for more rapid and possibly accurate assessment of tissue growth and quality; and 3) as an educational resource to learn how to use multifactor experimental designs to assess in vitro growth.