UNBIASED ESTIMATION OF NORWAY SPRUCE (PICEA ABIES L. KARST.) CHLOROPLAST STRUCTURE: HETEROGENEITY WITHIN NEEDLE MESOPHYLL UNDER DIFFERENT IRRADIANCE AND [CO2]

Author:

Kubínová Zuzana,Glanc Natália,Radochová Barbora,Lhotáková Zuzana,Janáček Jiří,Kubínová Lucie,Albrechtova JanaORCID

Abstract

The main objective of this study was to find out whether the selected chloroplast characteristics measured in the mesophyll layer nearest to the needle surface (i.e., the first mesophyll layer) could be representative for the whole needle cross section. Two chloroplast sampling approaches were applied on Norway spruce needles during the investigation of the effects of different levels of air CO2 concentration and irradiance: (i) sampling only from the first mesophyll layer, and (ii) systematic uniform random (SUR) sampling. The selected characteristics were: (i) chloroplast area, (ii) starch grain area, and (iii) starch areal density on median chloroplast cross sections, and (iv) chloroplast number per unit of needle volume. It was shown that the first mesophyll layer was not representative for estimating all evaluated characteristics except the chloroplast area. Sampling only there caused obtaining slightly biased results, while SUR sampling gave unbiased estimations at the cost of longer measuring time. The major effect of studied factors was in starch areal density and starch grain area, which were larger in sun needles in elevated CO2 concentration in comparison with sun needles in ambient CO2 concentration. In conclusion, it was demonstrated that the first layer of mesophyll is not always representative for the needle cross section. If technically feasible, SUR is recommended for analysis of chloroplast ultrastructure. The simplified sampling design can be applied, e.g., for comparisons of many different treatments. However, it should be combined with other approaches to characterize the chloroplast function and the results carefully considered and interpreted.

Publisher

Slovenian Society for Stereology and Quantitative Image Analysis

Subject

Computer Vision and Pattern Recognition,Acoustics and Ultrasonics,Radiology, Nuclear Medicine and imaging,Instrumentation,Materials Science (miscellaneous),General Mathematics,Signal Processing,Biotechnology

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