Proteins from plant based biomass: effects op post-harvest conditions on protein retention and quality : Part III (Sugar beet leaf harvest 2020)

This report is the follow-up of the exploration study concerning the potential impact of post-harvest technology on protein supply chains with special focus on the effects of post-harvest conditions on protein retention in sugar beet leaves. The research was performed independently by researchers from Wageningen Food & Biobased Research and funded by the Ministry of Agriculture, Nature and Food Safety through DFI- R&D budget, within the strategic WUR-KB theme of Healthy and Safe Food. The study has been divided into two main experiments: in a first part the effects of temperature and storage time on protein retention and on RuBisCo stability in sugar beet leaves were investigated. In asecond experiment, the effect of big volume storage on temperature and RuBisCo retention was examined.In the first experiment, sugar beet leaves were stored at 1, 20, 30 and 45 °C and sampled after 0, 6, 24, 30, 48, 72 and 168 h. The protein content, measured absolutely with both BCA method and relatively on protein gel, was stable during the first part of the storage, i.e. the latent phase. Depending to storage temperature, a decline in total protein content and in RuBisCo stability was observed. Based on these results, it was concluded that sugar beet leave can be stored up to168 hours at 1 °C without major effects in RuBisCo degradation. When sugar beet leaves were stored at 20 °C, loss of RuBisCo was initiated after 72 h of storage, 48 h at 30 °C and between 24 and 30 h when leaves were subjected to a temperature of 45 °C.In the second experiment, the effects of storing whole sugar beet leaf material in a big box at two temperature conditions was investigated. Sugar beet leaves were piled up in a big box to a height of 120 cm and left for 68 hours at 5 °C for the first box and at outside temperature for 24 hours followed by 44 hours at 20 °C for the second box. Each box was divided in 5 layers. Within each layer,temperature and gas contents were monitored over the complete storage period. At the end of this period and based on the temperature recordings, sugar beet leaves located at layers 30 and 120 cm at5 °C and 0 cm, 30, 60, 90 and 120 cm at 20 °C were sampled for protein analysis. Protein extraction was done directly on both leaf material and juice extracted from 1 kg of raw leaf material. The first extraction method allowed comparison of protein content results to the first experiment and the second extraction method was comparable to standard extraction methods applied at industrial level.After 68 hours of storage (44 hours at 20 °C), a mild rise in temperature was observed at the centre of the box stored at 20 °C. The temperature recordings showed that the warmest spot was located at 60 cm depth (centre of the pile) and reached a maximum temperature of 31.9 °C for a short period oftime (5.5 hours above 30 °C). Concerning the total protein content and RuBisCo stability analysis on samples extracted from the sugar beet leaf material, no significant difference between the two storage conditions (5 °C and 20 °C) and the different layers in the boxes was found. These results were consistent with the first experiment; the storage duration and the temperature rise observed in the boxes matched with the latent phase identified in the first experiment. Based on the results, it is possible to conclude that sugar beet leaves can be stored for a period of 68 hours without major effects on the RuBisCo stability. Storage in a big box in a cold room set up at5 °C helped to avoid the rise in temperature. RuBisCo was stable when the temperature inside the box remained under 30 °C for the majority of the storage period (62.5 hours). Finally, predictive models based on dry matter and on non-destructive sensing technologies were investigated. The correlation between dry matter and protein content was judged poor and indicated that it is not possible to extrapolate the protein content of the sugar beet leaves on basis of their drymatter content. A model based on NIR-measurements was also built to non-destructively predict dry matter and total protein content of sugar beet leaves. A relatively good performance was achieved for the prediction of dry matter on basis of a 13-wavelength measurement. Unfortunately, the predictionof protein content was less sensitive when using a NIR measurement of 10 wavelengths. Further measurements are required to optimise this model improve its prediction score