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In a field experiment, processing tomato plants inoculated with arbuscular mycorrhizae (AM) and non-inoculated (Control) were supplied with three levels of watering. The AM inoculation significantly increased tomato root colonization regardless of the water supply levels. Under water deficit conditions, AM inoculation significantly increased the biomass production (from 1,189 to 2,062 g plant⁻¹). AM inoculation increased the phosphorus uptake in water deficit supply (from 0.5 to 1.3 g plant⁻¹) and in optimum water supply (from 0.3 to 0.6 g plant⁻¹). Photosynthesis was not affected by irrigation, but mycorrhizal inoculation enhanced the efficiency of photosystem II at all water levels. Inoculated plants accumulated less proline, potassium, and magnesium in shoots in response to water stress. Less organic and inorganic solutes in shoots of inoculated plants were accompanied by higher water use efficiency, better stomatal conductance, and higher leaf water potential. In conclusion, AM inoculation enabled host plants to alleviate moderate water stress, modulating the physiological status of the plants for better water exploitation.
Processing tomato production represents an important part of the total production of processed vegetables in the world. The quality characteristics of processing tomato, important for the food industry, are soluble solids content and antioxidant content (such as lycopene and polyphenols) of the fruit. Analytical quantification of these components is destructive, time and labour consuming. That is why researchers try to develop a non-destructive and rapid method to assess those quality parameters. The present study reports the suitability of a portable handheld visible near infrared spectrometer to predict soluble solids, lycopene and polyphenol content of tomato fruit puree. Spectral ranges of 500-1000 nm were directly acquired on fruit puree of five different tomato varieties using a FieldSpec HandHeld 2™ Portable Spectroradiometer. Immediately after spectral measurement, each fruit sample was analysed to determine soluble solids, lycopene and polyphenol content. Partial least square regressions were carried out to create models of prediction between spectral data and the values obtained from the analytical results. The accuracy of the predictions was analysed according to the coefficient of determination value (R2), the root mean square error of calibration/cross-validation.
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