2011 Annual Report
1a.Objectives (from AD-416)
1) Evaluate NIR spectra in diffuse reflectance, transmittance, and scattering modes for determination of potato density/specific gravity.
2) Evaluate NIR spectra in diffuse reflectance, transmittance, and scattering modes for determination of specific sugars levels in potatoes.
3) Determine optimal sensing configuration (mode and wavelengths) for moving toward development of a prototype device for potential real-time field-based measurement.
1b.Approach (from AD-416)
Potatoes covering a range of density and sugar levels will be obtained from the potato industry. Samples will be collected and evaluated at multiple intervals over the length of the storage season. Each cleaned and intact potato tuber will be measured with the laboratory instrumentation set-up under the following three modes: diffuse reflectance over the visible and NIR region from 500-1700 nm; transmittance over the range of 500-1300 nm; and scattering over the range of 500-1300 nm. The transmittance and scattering ranges do not extend as far into the NIR range due to absorption. Following whole (intact) tuber measurement, a tissue sample will be cut from the same tuber and the same spectroscopic measurements will be obtained on this controlled and uniform sized sample. Additionally, each potato will be measured for density and specific sugars using conventional hydrometer and wet chemistry techniques to provide a baseline to which the spectroscopic measurements will be compared and correlated. A local company, Techmark Inc., specializes in potato handling and analysis and is supportive and willing to assist with conventional analysis (as a no cost collaborator). While the goal is to successfully measure whole/intact tubers, additionally evaluating samples of tissue will provide the opportunity to compare the results of this study against published results and also tissue versus whole tuber measurement. Several potato varieties will be included in the study to determine robustness or specificity of findings.
Data analysis will involve determining portions of the spectra and the mode, or combinations of spectra and modes, capable of best predicting density and sugars levels.
The progression of the research would include the first year of broad spectral measurement of whole tubers and tissue samples and critical analysis of data. A second year would be important (similar budget) to validate first year findings and, in parallel, focus on a particular sensing configuration based on what we learned from year 1. This sensing configuration would be a step toward a prototype device incorporating dedicated electronics for real-time in-field measurements.
The first year of this project resulted in some promising preliminary results that led to an effort in the following season to improve the uniformity and range of sugars of the potato sample set. This was done to confirm and strengthen the results and prediction models. The attempt to enhance the data set through varying vine kill dates, harvest dates, storage temperatures, and storage durations was moderately successful. The analysis of the data from the wet chemistry and the electronic (visible and NIR) reflectance, interactance, and hyperspectral imaging measurements of whole tubers and slices was not directly confirming of the first year. During this past year, effort was extended to evaluating the data under multiple statistical modeling approaches to determine if improved results could be obtained. Multivariate data analysis methods were studied along with many transformation processing methods to reach the best models for obtaining correlations for glucose and sucrose for both Frito Lay and Russet Burbank varieties. Multi-linear regression, principle components regressions, and partial least squares were implemented to model glucose and sucrose, in addition to using the radial basis functions artificial neural network (RBF-NN) as a non-linear regression. Partial least squares results showed that the glucose can be modeled for Frito Lay and Russet Burbank for the sliced tubers and also whole tubers at levels as high as R= 0.95. More powerful results were obtained using the RBF-NN which yielded slightly better models for glucose for both varieties and significantly improved models for sucrose for Russet Burbank in terms of the correlation coefficients and the standard error of prediction (R=0.96, SEP=0.0103). Models were run on individual modes/sources of data as well as fused data sets combining reflectance, interactance, and hyperspectral imaging with the highest correlations for each sugar under each potato variety coming from different models and data sources. The highest R value achieved for Frito Lay sucrose was R=0.51. Further studies in the treatments and the data analysis are needed to improve the sucrose models for Frito Lay. In addition, to improve variation in the distribution of both glucose and sucrose data sets and for confirming of models, more storage temperatures and studying spatial variation of both constituents may be considered under further collection and analysis of new samples. The goal remains to develop a low cost dedicated field level instrument for rapid evaluation of potato constituents and status for assisting harvest, storage, and marketing decisions. Project progress was monitored via meetings, emails, and joint sessions on planning, execution, and analysis of research with the collaborating researchers.