AGRE-0048 To Increase the Use of Pisum and Other Grain Legumes by Improving the Composition and Nutritional Value of the Seed by Genetic and by Processing Techniques

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ECLAIR Cluster VII - Proteins : Plant Genetics : Protein/Amino Acid

Pea nutrition

SUMMARY

This project has resulted in the production of several databases which provide detailed information on the composition and feed (nutritional) value of a wide range of pea varieties. This information can be of value in breeding improved varieties.

INRODUCTION

The aim of this project was to increase knowledge of the composition and the nutritional value in monogastric animals of pea (Pisum sativum, L.) and other grain legume species, and to understand the determinants of this value. It was anticipated that this information could be used to improve the use of these species through a combination of plant genetics and processing techniques.

OBJECTIVES

The main objective was to create a coherent body of results, from both the standard proximate analysis used in industry and from detailed characterisation of some components, and link these to nutritional studies. The information was gathered within a database based on the same samples used in all the participating laboratories for the various aspects under investigation.

ACTIVITIES

Approximately 300 lines of pea were used in the project, including 3 types of material: varieties of commercial nature (developed or in development); exotic germplasm (including wild ecotypes); and isogenic material (pairs of lines differing in one genetic character). About 60 of these lines were multiplied over several years until they reached a sufficient amount to be used in nutrition trials (200-500 kg). Near infrared spectroscopy was used for rapid non-destructive analyses. On the 60 large batches, several other measurements were performed in addition to the classical ones, in order to quantify and characterise the various chemical compounds of the seeds. The same 60 large batches were used for digestibility trials performed on rats (as an animal model with particular emphasis on proteins), on poultry (adults cockerels) and on pigs. Amongst the batches tested on poultry as meal, some were also tested after a pelleting process, which is the form most commonly used in industry.

RESULTS

General conclusions have been obtained from comparing differences between 3 groups of pea distinguished in the database: round white-flowered peas, round coloured-flowered peas, wrinkled peas. The mean composition within these groups identified is very different. Within the groups, the variability observed in most of the components is also quite high. In parallel to chemical analyses, the seeds were also analysed by near infrared spectroscopy. The spectra obtained were used to build calibrations for prediction of chemical composition. The accuracy of the models developed is very good for some variables (mainly the proximate analysis measurements) and some promising results were obtained on other measurements (anti-nutritional factors). Predictions were satisfactory on whole seeds as well as on ground samples, whilst reflectance spectroscopy (NIRS) produced better results than transmittance (NITS). Prediction of composition of individual seed was done where reference methods could be performed on such samples: this was the case for phenolics, and for lipid composition. The nutritional results have enabled the characteristics of the various groups of peas to be reliably established. The first factor of variation identified in the metabolisable energy (ME) value in poultry is the fibre content, with a correlation of about Rē=0,5 in round peas. Fibre content was assessed by several measurements: crude fibre, ADF, NDF, cell walls, cotyledon cell walls, percentage of integument. All were shown to have some correlation with ME, but the most remarkable fact is that no single factor could be recognised to account for all the effects of fibres. This leads to 2 possible conclusions: first the negative effect of fibres can in fact have different causes, for instance a dilution of the useful nutrients by non-digestible compounds as well as a problem of accessibility of the nutrients; secondly from a practical point of view, there is no method amongst those used that is sufficient for nutritionists.

CONCLUSION

A major product of this work is a unique databases based on samples with a very homogeneous origin from a wide collection of peas. Infrared calibrations appeared to be a very promising tool to valorise this information and to help in future work on composition and genetics. The nutritional part of the programme provided references on the mean nutritional value in the various categories of pea. Within these categories, some data was provided on the relative contribution to the nutritional value of both nutritional and anti-nutritional compounds. Feasibility studies also showed that inclusion of peas can be made in fish diets. The investigation of technological treatments confirmed the importance of these tools in reducing the differences between lines of different initial value, and more generally indicated ways to improve the value of feed peas.

EXPLOITATION

The main conclusion of this work is that all the characters studied present some variability. The collection of this information into a large database on pea composition can be used to select parents for longer-term genetic studies, used to understand the inheritance of specified seed characters. This information will be made available to plant breeders. If lines could be produced which differ only for a specified component, this material would also be valuable to nutritionists to substantiate the role of specific components in animal nutrition. A second database concerning the 60 lines that were analysed for their detailed chemical composition and their nutritional value is also available.

PARTICIPANTS

John Innes Centre, Norwich (UK). The two partners were linked to 17 laboratories specialising in determining the chemical composition of seeds or nutritional value in animals: CCPA Osny (F), CNR Portici (I), CRA Libramont (B), FSA Gembloux (B), GSP Mons (F), IFR Norwich (GB-UK), INA PG Paris (F), INIA Madrid (ES), INRA Dijon-Jouy-Nantes-Nouzilly-Rennes-Versailles (F), IRTA Reus (ES) JCL Valladolid (ES), KVL Frederiksberg (DK), NIAS Tjele (DK), PROVITAL Warcoing (B), PSW Plymouth (UK), SANDERS Athis-Mons (F), TNO Zeist (NL), UCAAB Chateau-Thierry (F) and UCB Lyon (F).