A macronutrient optimization platform for micropropagation and acclimatization: using turmeric (Curcuma longa L.) as a model plant

Abstract

Tissue culture medium is often overlooked as a factor in plant biotechnology. Most work uses Murashige and Skoog (MS; Physiol Plant in 15:473–497, 1962) inorganic medium formulation, which is not likely optimal for many of the plant systems where it is used. This current study of macronutrient factors simultaneously altered media volume and amount of tissue (plants per vessel), sucrose, nitrogen (as NO ⁻₃ and NH ⁺₄ ions), and K⁺ in a d-optimal design space with only 55 experimental units (including five true replicates). Meso- and micro-nutrient concentrations were lowered (5% of MS) to determine which elements were most critical to plantlet quality. Plantlet quality was quantified by multiplication in the laboratory and survival and growth in the greenhouse. Plantlets grown at the lowest plant density, the lowest macronutrient concentration (20 mM), and equi-molar proportions of NH ⁺₄ /K⁺ resulted in the best multiplication ratio and 100% greenhouse survival. Multiplication ratio in vitro and survival in the greenhouse were well correlated with one another. Laboratory dry mass, media use, sucrose use, and the uptake of the macronutrients NO ⁻₃ , NH ⁺₄ , and K⁺ were not well correlated with plantlet quality. Plantlets with the greatest uptake of P, Ca, Mg, and Mn had the best multiplication in the laboratory and on subsequent transfer, acclimatized and grew fastest in the greenhouse. Phosphorus was shown to be most depleted in media. This work demonstrates a platform to simultaneously optimize several nutritive components of tissue culture media to produce plantlets that perform well in both laboratory and greenhouse environments. Plant quality was related with factors outside the macronutrient design, and this platform indicated where to expand the experimental space. Fixed, flat-screen presentations revealed less of the response surface than interactive profiles driven by the reader.

Appendices

Appendix I

Shockwave file showing multiplication ratio prediction profiler, as shown in static Fig. 2A , B , and C . The reader may explore the response surface model by sliding the x-coordinates and viewing the dynamic adjustment of response values.

Appendix II

Shockwave file showing uptake of P, Ca, and Mg compared with optimization of multiplication ratio and greenhouse survival as shown in static Fig. 5A and B . The reader may simultaneously explore several response surface models by sliding the x-coordinates and viewing the dynamic adjustment of response values. The ranges of response values may be adjusted by sliding the y-axis coordinates along the vertical axes.