Improved grain nutritional quality is an important factor for marketing grain and hence is an important breeding objective for most crop species. However, accurate measurement of the concentration of micro- and macro-nutrients in seeds requires multiple analytical methods, often involving complicated wet chemistry procedures. We proposed to develop a technology platform for reliable low cost and high throughput analysis of pea seed nutritional quality, using X-ray fluorescence (XRF) and Mid-Infra-Red (Mid-IR) absorbance spectroscopy.
The specific objectives of this project were to 1) Select an appropriate calibration set of pea seed samples for developing Mid-IR and XRF based seed nutritional analysis; 2) Develop a high throughput method to homogenize seeds and prepare sample pellets for spectroscopy; 3) Develop an XRF based method for one step prediction of all important mineral nutrients; 4) Develop a Mid-IR based method for one step prediction of all important organic seed nutrients; and 5) Make recommendations for implementing a high throughput seed nutritional analysis platform for breeding programs and grain processing industries.
The objectives 1 and 2 were fully realized. 1) We have defined the criteria and selected optimal sets of calibration and validation sets of pea seeds well suited for developing and the new spectroscopic methods for seed nutritional analysis. 2) We successfully developed and used a new design of grinding tubes and a system for high throughput ball milling of seed samples, that eliminates sample cross contamination. Effective methods for vacuum storage of processed samples and high throughput pellet preparation suitable for XRF and Mid-IR spectroscopy have also been standardized.
Objectives 3 and 4: Accurate prediction of XRF based prediction of multiple mineral concentrations (Fe, Zn and Se) using the same XRF spectrum, has been accomplished in pea seeds, while the prediction of Potassium (K) concentration has been found to be less satisfactory. Excellent prediction of total protein concentrations and moderately accurate prediction of total fiber, total carotenoid and phytic acid using the same Mid-IR absorbance spectra have been accomplished. Prediction of total starch concentrations were found to be less than satisfactory. The deficiency in prediction of potassium concentration appears to be due to the interference of intrinsic seed matrix related factors with X-ray absorption and emission. In contrast, the significant lack of correlation between Mid-IR predictions of total starch concentrations and wet chemistry-based results and lower than ideal accuracy in the Mid-IR based prediction of total fiber, total carotenoids and phytic acid concentrations in pea seeds appear to be related to the high rate of human error observed in wet chemistry assessments rather than the spectroscopy methods themselves. Rectification of these deficiencies should be implemented in the next stage of development of this project based on practically feasible remedies identified in this project.
In fulfillment of objective 5, the design of a high throughput contamination free seed grinding system using grinding tubes designed and fabricated in this project has already benefitted chickpea, lentil and faba bean seed related projects. The protocol for developing standard curves, calibration models and validation of XRF and Mid-IR based prediction of the concentrations of seed nutrients and anti-nutrients (e.g. Phytic acid), are being written up in two manuscripts and will be published in the near future for the benefit of the pulse and other crop breeding groups and grain processing industries. The basic methodology developed in this project can be further broadened and implemented in the future for a wider range of pulse and cereal crops in order to enable routine screening of large sets of seed samples during the breeding cycle at the Crop Development Centre, University of Saskatchewan and other facilities.