Characterize protein levels and composition in Lentil germplasm to inform breeding targets

Objectives
  • Compile genotype-specific information on the protein content, amino acid profile of Lentil seeds.

  • Contrast the protein content and amino acid profile across diverse Lens genotypes in order to detect any genotype-specific variation.

Germplasm
Germplasm Genus
Lens
Germplasm Scientific Name
Lens culinaris
Germplasm Collection
AGILE Lentil Diversity Panel (LDP) subset
Executive Summary

Current data on the protein quality of lentils and lentil protein ingredients are derived from composite samples, and information related to varietal differences, is lacking. The development of protein extraction and processing techniques will only reach limited success if there is an inconsistency with the starting materials. Genotype-specific information on the protein content, amino acid profile, and protein digestibility and functionality, will benefit the lentil breeding program as it begins to focus on improving the nutritional characteristics of lentil. Food scientists will also be able to capitalize on the nutritional baseline information to make use of lentil ingredients in various food applications to meet nutrient content claims.

This study uses near-infrared reflectance spectroscopy (NIRS) measurements calibrated against the official methods to determine the percent composition on a dry matter basis of protein and various amino acids in ground / whole Lentil samples. The NIRS measured Alanine, Arginine, Aspartic Acid, Cysteine, Glutamic Acid, Glycine, Histidine, Isoleucine, Leucine, Lysine, Methionine, Phenylalanine, Proline, Serine, Threonine, Tryptophan, Tyrosine, Valine, as well as, crude protein content. The experiment focused on individual samples from the Lentil Diversity Panel to elucidate varietal differences with each sample being specific to a single variety.

Attribution
Experiments
Experiments
Objectives
  • To evaluate variation of protein and amino acid compositions in cultivated lentils from Canada using the Dumas Combustion method.

  • Compare this reference wet chemistry method to determine protein and amino acid content with NIRS methods done in a related experiment.

Associated Datasets
Dataset

LDP Protein Percent Composition Reference Dataset (XLSX, TSV)

This dataset consists of the total protein percent composition on a dry matter basis and amino acid specific percent composition on a dry matter basis (%) for each of 18 amino acids. The protein compositions were determined using the Dumas Combustion method and this dataset will act as a reference to evaluate the validity of the NIR results in a linked experiment. The seeds used for this analysis are from the AGILE field trial site-years Rosthern2016, Sutherland2016, Rosthern2017, Sutherland2017.

Objectives
  • To develop and evaluate the NIRS models for the prediction of protein and amino acid composition in whole and ground lentils for two types of NIR spectrometers: DA 7250 and FT 9700 (PerkinElmer Health Sciences Canada Inc., Winnipeg, MB, Canada).

  • To analyze the effects of sample status, spectrometers and amino acid correlations to protein on the performance of NIR models.

  • To evaluate variation of protein and amino acid compositions in cultivated lentils from Canada.

  • To detect SNPs significantly associated with protein and 18 amino acids content by using a genome-wide association analysis.

Associated Datasets
Dataset

LDP Protein Percent Composition NIRS Dataset (XLSX, TSV)

This dataset consists of the total protein percent composition on a dry matter basis and amino acid specific percent composition on a dry matter basis (%) for each of 18 amino acids. The protein compositions were determined using near-infrared reflectance spectroscopy (NIRS) models. The seeds used for this analysis are from the AGILE field trial site-years Rosthern2016, Sutherland2016, Rosthern2017, Sutherland2017. These seed samples are the exact same source as the linked reference method experiment.

Grant Activity
Title
EVOLVES: Enhancing the Value of Lentil Variation for Ecosystem Survival
Data Custodian
  • Kirstin E Bett
  • Albert Vandenberg
Research Organization
Funding Range

2019-2023