An enzymatic assay method in 96-well microplates (MP method) is proposed for non-structural carbohydrates (NSC) in ligneous plants. Soluble sugars were extracted from 50 mg of finely ground plant powder, in the presence of water, methanol and chloroform. The glucose, fructose and sucrose contents were successively determined in each well, although sorbitol could not be assayed under these conditions. Whatever the sugar, the precision (reproducibility), linearity (addition of specific amounts of sugars) and accuracy (comparison with method using high-performance liquid chromatography (HPLC)) were excellent. This method was more specific than with HPLC, so that the recovery rate of sugars was improved. In the absence of a significant matrix effect, purification of the extract was unnecessary, thus simplifying the procedure and contributing to its robustness. A micro-method is thus proposed which can be applied to 5 mg of plant powder. This miniaturization affects neither the precision of the MP method nor sugar concentrations. The results of starch assays further demonstrated that this micro-method was appropriate to the analysis of NSC in small samples of woody plant tissues. Reliable, rapid and simple to perform, this micro-method is less expensive than HPLC or other classic enzymatic methods.

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Understanding how the fruit microclimate affects ascorbate (AsA) biosynthesis, oxidation and recycling is a great challenge in improving fruit nutritional quality. For this purpose, tomatoes at breaker stage were harvested and placed in controlled environment conditions at different temperatures (12, 17, 23, 27 and 31°C) and irradiance regimes (darkness or 150 µmol m-2 s-1). Fruit pericarp tissue was used to assay ascorbate, glutathione, enzymes related to oxidative stress and the AsA/glutathione cycle and follow the expression of genes coding for 5 enzymes of the AsA biosynthesis pathway (GME, VTC2, GPP, L-GalDH, GLDH). The AsA pool size in pericarp tissue was significantly higher under light at temperatures below 27°C. In addition, light promoted glutathione accumulation at low and high temperatures. At 12°C, increased AsA content was correlated with the enhanced expression of all genes of the biosynthesis pathway studied, combined with higher DHAR and MDHAR activities and increased enzymatic activities related to oxidative stress (CAT and APX). In contrast, at 31°C, MDHAR and GR activities were significantly reduced under light indicating that enzymes of the AsA/glutathione cycle may limit AsA recycling and pool size in fruit pericarp, despite enhanced expression of genes coding for AsA biosynthesis enzymes. In conclusion, this study confirms the important role of fruit microclimate in the regulation of fruit pericarp AsA content, as under oxidative conditions (12°C, light) total fruit pericarp AsA content increased up to 71%. Moreover, it reveals that light and temperature interact to regulate both AsA biosynthesis gene expression in tomato fruits and AsA oxidation and recycling.

The prediction of internal quality properties, such as sweetness and acidity, in peach fruit by mid infrared spectroscopy is of interest for rapid determination. Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) was tested here on two populations of peach fruits issued from contrasting genitors providing a large phenotypic variability. Over two successive years, 284 samples in 2006 and 483 samples in 2007 were characterized for soluble solids content (SSC), titratable acidity (TA), glucose, fructose, sucrose, malic acid, and citric acid contents. Sugar and organic acid composition were determined by three methods: colorimetric enzymatic measurements (ENZ), high-performance liquid chromatography (HPLC), or proton NMR spectroscopy ((1)H NMR), depending on the samples. For all samples, fruit homogenates were analyzed in ATR-FTIR using the same methodology and the same spectrometer. The objective here was to evaluate the effect of reference methods on the prediction performance. The best results were generally observed for SSC and TA, the percentage of the root-mean-square error of cross validation (RMSECV%) ranging respectively between 5.8% and 8.7% and between 5.9% and 8.0%, depending on the samples. For individual sugars and organic acids, the best correlations were obtained between ATR-FTIR data and ENZ reference data followed by HPLC and (1)H NMR ones.

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