Technical report: Optimization of the harvest stage for reducing cooking banana postharvest losses: a multi-criteria approach targeting matooke end-product.

This report presents results of RTB-ENDURE sub-output 1.3; ‘Determining appropriate harvest time for the cooking bananas with intrinsic long shelf-life using physical, chemical and sensory attributes’ of the cooking banana business case’s Output 1, entitled “Increased access of farmers to cooking banana varieties with preferred quality attributes and intrinsic long shelf life traits”. The worked aimed at reducing postharvest losses for cooking banana while modulating harvest stage for green life extension. The originality of this investigation was to evaluate the putative impact of fruit stage of harvest onto its potential storage life and eating quality. The optimal harvest stage was evaluated by coupling three antagonist parameters, namely fruit diameter, green life, and eating quality, to optimize harvest stage of the variety Kibuzi in specific edapho-climatic conditions of Rakai and Isingiro districts in southwestern Uganda. A temperature record was considered in both sites between flowering and harvest. The interval between flowering and harvest (IFH) of Kibuzi banana variety was used as a quantitative explanatory variable, and the site location (Rakai at 1270 masl vs Isingiro at 1440 masl) was used as a qualitative one. Since the sites were at different altitudes, two Tynitag temperature data loggers were installed to record temperatures. Fruits size, dry matter, fruit firmness, total soluble solids, titratable acidity and sensory attributes were recorded at four harvest stages: 112, 126, 138, 152 days and 111, 125, 137, 151 days after flowering. The evolution of three parameters; diameter of fruit, green life and overall acceptability of the end-product - Matooke - were simulated for 110 to 155 days range, leading to the identification of a range of optimal harvest ages for variety Kibuzi in Rakai at between 133 to 142 days and 133 to 150 days for Isingiro. The prediction of the optimal harvest stage will remain only valid for the two locations without taking into account thermal sum for establishing a strong relationship between fruit age in degree.days and green life. Given the respective altitudes at Rakai and Isingiro, it implies that the two edapho-climatic conditions were not so different in terms of on field temperature. With some more diverse thermal conditions in the experimental sites (lowland vs highland with at least 3°C needed between sites), the thermal sum concept will be even more precise for the prediction of the optimal harvest stage for bananas, regardless the location site (lowland, highland, with hot or cool local conditions). Such original multi-criteria approach (agro-morphological, physiological traits, and end-product sensory attributes) was relevant for the prediction of the optimal harvest stage, in order to reduce banana postharvest losses during transport and until Matooke preparation by end-users. Such innovative methodology can be applied to some other banana culinary recipes and end-uses

Modeling the vacuolar storage of malate shed lights on pre- and post-harvest fruit acidity

Background: Malate is one of the most important organic acids in many fruits and its concentration plays a critical role in organoleptic properties. Several studies suggest that malate accumulation in fruit cells is controlled at the level of vacuolar storage. However, the regulation of vacuolar malate storage throughout fruit development, and the origins of the phenotypic variability of the malate concentration within fruit species remain to be clarified. In the present study, we adapted the mechanistic model of vacuolar storage proposed by Lobit et al. in order to study the accumulation of malate in pre and postharvest fruits. The main adaptation concerned the variation of the free energy of ATP hydrolysis during fruit development. Banana fruit was taken as a reference because it has the particularity of having separate growth and post-harvest ripening stages, during which malate concentration undergoes substantial changes. Moreover, the concentration of malate in banana pulp varies greatly among cultivars which make possible to use the model as a tool to analyze the genotypic variability. The model was calibrated and validated using data sets from three cultivars with contrasting malate accumulation, grown under different fruit loads and potassium supplies, and harvested at different stages. Results: The model predicted the pre and post-harvest dynamics of malate concentration with fairly good accuracy for the three cultivars (mean RRMSE = 0.25-0.42). The sensitivity of the model to parameters and input variables was analyzed. According to the model, vacuolar composition, in particular potassium and organic acid concentrations, had an important effect on malate accumulation. The model suggested that rising temperatures depressed malate accumulation. The model also helped distinguish differences in malate concentration among the three cultivars and between the pre and post-harvest stages by highlighting the probable importance of proton pump activity and particularly of the free energy of ATP hydrolysis and vacuolar pH. Conclusions: This model appears to be an interesting tool to study malate accumulation in pre and postharvest fruits and to get insights into the ecophysiological determinants of fruit acidity, and thus may be useful for fruit quality improvement. (Résumé d'auteur

Sensory characterization of the perceived quality of East African highland cooking bananas (matooke)

Open Access ArticleBACKGROUND It has recently become increasingly evident that banana projects in Uganda need to consider consumer preferences as part of the breeding process to increase the acceptability of new cultivars. A trained panel used quantitative descriptive analysis (QDA) as a tool to assess the sensory characteristics of 32 cooking bananas (matooke). The aim was to investigate which sensory characteristics best describe matooke. RESULTS Fourteen descriptors were generated. The preferred attributes of matooke were high-intensity yellow color, homogeneous distribution of yellow color, good matooke aroma, highly moldable by touch, moist and smooth in the mouth. Analysis of variance revealed significant differences in the yellowness, homogeneity of color, firmness, moistness, smoothness, matooke aroma, hardness, and moldability across the genotypes (P < 0.05). Principal component analysis (PCA) showed strong positive correlations between yellowness and homogeneity of the color (R = 0.92). Smoothness in the mouth and moldability by touch were strongly and positively correlated (R = 0.88). Firmness in the mouth was well predicted by hardness to touch (R2 = 0.85). The matooke samples were ranked into two sensory clusters by agglomerative hierarchical clustering (AHC). CONCLUSION The study showed attribute terms that could be used to describe matooke and also revealed that QDA may be used as a tool during the assessment and selection of new cooking banana hybrids to identify relevant sensory attributes because of its ability to discriminate among the banana hybrids

CREAPULS : Création de variétés de légumes secs innovantes répondant aux défis technologiques et sociétaux actuels

Les légumes secs sont reconnus pour leurs avantages environnementaux et nutritionnels. Cependant leur développement est entravé par des problèmes variés. Du côté des producteurs, les rendements sont variables en raison des conditions pédoclimatiques et de la sensibilité aux maladies et aux ravageurs. Du côté des transformateurs, la complexité de la transformation, notamment la mouture et l'appertisation, pose des défis. Enfin, du côté des consommateurs, les temps de préparation longs, la faible diversité et des caractéristiques organoleptiques déplaisantes entravent l'adoption de ces produits. C'est dans l'objectif de répondre à ces enjeux que s'inscrit le projet CREAPULS. Plus précisément, son objectif est de dynamiser et accélérer le processus de sélection variétale des légumineuses (lentilles, haricots et pois chiche), en fonction des caractéristiques technologiques et sensorielles souhaitées par le marché, mais également des conditions culturales visées (types de sols, augmentation des rendements, etc.). Pour ce faire, en parallèle i) du développement d'une nouvelle méthode de sélection basée sur la génération de lignées doubles haploïdes, deux études seront menées : ii) la caractérisation de la diversité mondiale en haricots, pois-chiches et lentilles des critères technologiques dans l'objectif de réaliser un phénotypage précoce (peu ou pas destructif) et de sélectionner des variétés répondant aux exigences des transformateurs ; iii) la caractérisation sensorielles et physico-chimiques des marqueurs de goût des différentes variétés dans l'objectif de sélectionner des variétés répondant aux exigences des consommateurs. Grâce à ces nouvelles méthodes, et sur la base des résultats obtenus, de nouvelles variétés répondant spécifiquement à la demande pourront rapidement être créées et commercialisées (en moins de 6 ans), quand les méthodes actuelles nécessitent plus de 10 ans d'études. La force du projet CREAPULS réside notamment dans son consortium constitué d'acteurs clés composant l'ensemble de la chaine de valeur tels que les semenciers, les transformateurs de légumes secs, l'interprofession et le centre technique de la filière des oléoprotéagineux permettant d'assurer la communication et la promotion des résultats à l'ensemble de la filière. Le consortium dispose également de compétences de pointes en termes de recherche en agronomie génétique et amélioration des plantes, notamment grâce à l'implication de l'Institut de GENECH et du CIRAD. Ainsi CREAPULS dispose de tous les atouts pour assurer le développement et la structuration de la filière des légumes secs en France, et pour répondre à l'ensemble des enjeux nationaux précités

Influence de la nature des pâturages sur les caractéristiques de texture et de flaveur des fromages

*INRA, Documentation, 17 rue Sully, BP 86510, 21065 Dijon cedex Diffusion du document : INRA, Documentation, 17 rue Sully, BP 86510, 21065 Dijon cedex Diplôme : Dr. Ing