MRI and Bidimensional relaxometry sequences for macro and microstructure assessment in food models.

Physico-chemical and organoleptic characteristics of food depend largely on the microscopic level distribution of gases and water, and connectivity and mobility through the pores. Microstructural characterization of food can be accomplished by Magnetic Resonance Imaging (MRI) and Nuclear Magnetic Spectroscopy (NMR) combined with the application of methods of dissemination and multidimensional relaxometry. In this work, funded by the EC Project InsideFood, several artificial food models, based on foams and gels were studied using MRI and 2D relaxometry. Two different kinds of foams were used: a sugarless and a sugar foam. Then, a half of a syringe was filled with the sugarless foam and the other half with the sugar foam. Then, MRI and NMR experiments were performed and the sample evolution was observed along 3 days in order to quantify macrostructural changes through proton density images and microstructural ones using T1T2 maps, using an inversion CPMG sequence. On the proton density images it may be seen that after 16 hours it was possible to differentiate the macrostructural changes, as the apparition of free water due to a syneresis phenomenon. On the interface it can be seen a brighter area after 16 hours, due to the occurrence of free water. Moreover, thanks to the bidimensional relaxometry (T1-T2) it was possible to differentiate among microscopic changes. Differences between the pores size can be observed as well as the microstructure evolution after 30.5 hours, as a consequence differences are shown on free water redistribution through larger pores and capillarity phenomena between both foams.

A multi-criteria optimization and decision-making approach for improvement of food engineering processes.

The objective of this study was to propose a multi-criteria optimization and decision-making technique to solve food engineering problems. This technique was demostrated using experimental data obtained on osmotic dehydratation of carrot cubes in a sodium chloride solution. The Aggregating Functions Approach, the Adaptive Random Search Algorithm, and the Penalty Functions Approach were used in this study to compute the initial set of non-dominated or Pareto-optimal solutions. Multiple non-linear regression analysis was performed on a set of experimental data in order to obtain particular multi-objective functions (responses), namely water loss, solute gain, rehydration ratio, three different colour criteria of rehydrated product, and sensory evaluation (organoleptic quality). Two multi-criteria decision-making approaches, the Analytic Hierarchy Process (AHP) and the Tabular Method (TM), were used simultaneously to choose the best alternative among the set of non-dominated solutions. The multi-criteria optimization and decision-making technique proposed in this study can facilitate the assessment of criteria weights, giving rise to a fairer, more consistent, and adequate final compromised solution or food process. This technique can be useful to food scientists in research and education, as well as to engineers involved in the improvement of a variety of food engineering processes.

Molecular tools to improve chestnut management: El Bierzo as a case study

The European chestnut (Castanea sativa Mill.) is a multipurpose species that has been widely cultivated around the Mediterranean basin since ancient times. New varieties were brought to the Iberian Peninsula during the Roman Empire, which coexist since then with native populations that survived the last glaciation. The relevance of chestnut cultivation has being steadily growing since the Middle Ages, until the rural decline of the past century put a stop to this trend. Forest fires and diseases were also major factors. Chestnut cultivation is gaining momentum again due to its economic (wood, fruits) and ecologic relevance, and represents currently an important asset in many rural areas of Europe. In this Thesis we apply different molecular tools to help improve current management strategies. For this study we have chosen El Bierzo (Castile and Leon, NW Spain), which has a centenary tradition of chestnut cultivation and management, and also presents several unique features from a genetic perspective (next paragraph). Moreover, its nuts are widely appreciated in Spain and abroad for their organoleptic properties. We have focused our experimental work on two major problems faced by breeders and the industry: the lack of a fine-grained genetic characterization and the need for new strategies to control blight disease. To characterize with sufficient detail the genetic diversity and structure of El Bierzo orchards, we analyzed DNA from 169 trees grafted for nut production covering the entire region. We also analyzed 62 nuts from all traditional varieties. El Bierzo constitutes an outstanding scenario to study chestnut genetics and the influence of human management because: (i) it is located at one extreme of the distribution area; (ii) it is a major glacial refuge for the native species; (iii) it has a long tradition of human management (since Roman times, at least); and (iv) its geographical setting ensures an unusual degree of genetic isolation. Thirteen microsatellite markers provided enough informativeness and discrimination power to genotype at the individual level. Together with an unexpected level of genetic variability, we found evidence of genetic structure, with three major gene pools giving rise to the current population. High levels of genetic differentiation between groups supported this organization. Interestingly, genetic structure does not match with spatial boundaries, suggesting that the exchange of material and cultivation practices have strongly influenced natural gene flow. The microsatellite markers selected for this study were also used to classify a set of 62 samples belonging to all traditional varieties. We identified several cases of synonymies and homonymies, evidencing the need to substitute traditional classification systems with new tools for genetic profiling. Management and conservation strategies should also benefit from these tools. The avenue of high-throughput sequencing technologies, combined with the development of bioinformatics tools, have paved the way to study transcriptomes without the need for a reference genome. We took advantage of RNA sequencing and de novo assembly tools to determine the transcriptional landscape of chestnut in response to blight disease. In addition, we have selected a set of candidate genes with high potential for developing resistant varieties via genetic engineering. Our results evidenced a deep transcriptional reprogramming upon fungal infection. The plant hormones ET and JA appear to orchestrate the defensive response. Interestingly, our results also suggest a role for auxins in modulating such response. Many transcription factors were identified in this work that interact with promoters of genes involved in disease resistance. Among these genes, we have conducted a functional characterization of a two major thaumatin-like proteins (TLP) that belongs to the PR5 family. Two genes encoding chestnut cotyledon TLPs have been previously characterized, termed CsTL1 and CsTL2. We substantiate here their protective role against blight disease for the first time, including in silico, in vitro and in vivo evidence. The synergy between TLPs and other antifungal proteins, particularly endo-p-1,3-glucanases, bolsters their interest for future control strategies based on biotechnological approaches.