Performing Department
(N/A)
Non Technical Summary
Currently flavor forward crop varieties are having a lot of economic success in the U.S. For example, older conventional crop varieties such as Thompson Seedless Grapes and Cascade hops are often sold for far less (i.e. < $1 and < $3-11 a pound, respectively) than new flavor forward crop varieties such as Cotton Candy grapes and Citra® hops which command much higher prices (i.e. ~$3.33-4.99 and ~$15-34 per pound, respectively) (sources: https://tinyurl.com/CCGrapePrice and https://lupulinexchange.com/). Similarly, rice being imported from Thailand and India has a profound impact on the U.S. rice industry, and U.S. rice imports are projected to represent ~32% (or ~1.98 billion USD) of domestic rice use in 2022/23 which is an all-time high.Overall, this is because flavor plays a major role in consumer preference, and consumer demand has grown for Asian aromatic varieties such as Jasmine from Thailand and Basmati from India.To compete effectively with the imported Jasmine rice market, U.S. rice breeders need to develop cultivars with similar but superior and possibly novel flavors. GC-MS/MS along with some other techniques will be used to investigate the variation in the volatile/ nonvolatile profiles across a variety of different rice cultivars from many different U.S. breeding programs (University of Arkansas, Louisiana State University, and the California Cooperative Rice Experiment Station) as well as samples from the USDA-ARS World Rice Collection and subsets of genetically diverse genome-mapped accessions. After analyzing these different varieties multivariate statistics will be used to select a collection (~10-20) of the most diverse samples for sensory analysis. In this way, we will establish a tool so that breeders can better design flavor-forward aromatic rice varieties and set indicators for the key performance of U.S. aromatic rice performance. It is essential to establish infrastructure to facilitate the evaluation of the chemical characteristics in crops which are important for driving unique flavor characteristics in a cost-effective manner and the results of this seed project will help to develop new relationships which will lead to other future proposals which will be submitted to USDA AFRI programs such as A1141 Plant Breeding for Agricultural Production.
Animal Health Component
0%
Research Effort Categories
Basic
25%
Applied
25%
Developmental
50%
Goals / Objectives
The main goal of this project is to generate a better and more comprehensive understanding of rice flavor so that domestic rice varieties remain competitive with imported aromatic varieties such as Thai Jasmine.To achieve this goal there are four main;Develop an understanding of the key volatiles important for different aromas in rice using GC-MS/MS and the nonvolatile starch characteristics using titration and differential scanning calorimetry impacting taste and mouthfeelCharacterize the different aromas/ flavors of rice using descriptive sensory analysisEstablish ranges for these key volatiles in important US varieties as well as across a wide diversity of rice samples using collections such as the USDA world populationGenerate preliminary data to identify the genes underlying the production of various flavor compounds by association mapping with chromosomal location markers
Project Methods
Volatile analysisVolatile detection will be performed on a 1.5 g of paddy/brown/milled rice in a 10 mL amber screw cap vial using a Shimadzu Nexis GC-2030 system equipped with a triple-quadruple mass selective detector. The volatiles in the headspace will be absorbed using an AOC-6000 Autosampler equipped with 1 cm long SPME fiber coated with Divinylbenzene/Carboxen/Polydimethylsiloxane (DVB/CAR/PDMS). A ZB-5MSplus (30 m x 0.25 mm x 0.25 μm) capillary column will be used and a splitless injection will be performed at an inlet temperature of 240 °C, at absorption and desorption times of 10 min and 3 min, respectively. Helium will be used as the carrier gas at a flow rate of 1 mL/min. The inlet pressure will be 47.6 kPa. The initial oven temperature will be set to 35 °C, held for 5 min, then raised to 150 °C at a rate of 5 °C/min, then raised to 280 °C at a rate of 8 °C/min and held for 5 min.11 The MS will be operated in full scan mode (41-400 m/z) and multiple reactions monitoring (MRM) for a total of 0.300 second with an interface and ion source temperatures of 290 and 240 °C, respectively. Unknown compounds will be identified on Shimadzu LabSolution software based on a library search. Linear retention indices will be created using an alkane standard mix solution (C7-C20) to confirm the molecule identifications. Deuterated standards (hexanal-d12, 2-acetyl-pyrroline-d5, β-myrcene-d6, ethyl hexanoate-d11, phenylacetaldehyde-d5, 1-octanol-d17, and linalool-d5) at 20 ng/μL will be added to each vial as internal standards at a fixed volume of 5 μL. For key compounds, MRM optimization will be executed by running product ion scan of each molecule of interest at collision energy increase steps of 3 kV. Then, Shimadzu MRM Optimization Tool will be used to choose the best combination of transitions and collision energies for each molecule for a total of three: one quantitative and two qualitative transitions. A calibration curve will be executed with all molecules of interest ranging from 0.5 ng/μL to 1000 ng/μL, increasing concentration at each point, for a total of 7 calibration points.Nonvolatile analysisFor apparent amylose analysis and gelatinization properties, paddy rice will be dehusked and ground. Apparent amylose will be determined by colorimetric assay as performed by Juliano (1971)12 and measured in a UV-Visible spectrophotometer (Shimadzu) at 620 nm. The gelatinization properties will be measured using a differential scanning calorimeter (DSC, model 4000, Perkin-Elmer, Norwalk, CT) based on Patindol, Jinn, Wang, Siebenmorgen 13 Eight mg of rice flour will be weighed into a stainless-steel pan and added with 16 μL of DI water. The hermetically sealed pan will be equilibrated for one hour at room temperature before scanning from 25 to 125°C at a rate of 5°C/min. The onset temperature (To), peak temperature (Tp), and end temperature (Te) will be obtained by Pyris data analysis software.Sensory analysisMultivariate statistics14 (as described below) will be used to select (10-20 rice varieties to perform sensory analysis on). For sensory analysis~1 kg of these rice varieties will be needed. Therefore, depending on the availability of the samples a seed increase request may be required. Sensory analysis will be performed in collaboration with the Sensory Science Center (Dr. Han-Seok Seo). In general, 11-13 sensory panelists will be recruited and trained (over 5-10 sessions) in advance of data collection on the key characteristics of the selected rice samples for sensory analysis. Over these sessions the panel will blindly and randomly evaluate all the samples to establish, by consensus, the sensory terms, and corresponding reference standards, which best describe the differences between the samples. The samples will then be evaluated over three replications in a randomized and balanced Latin Square order.Data analysisANOVA, three-way ANOVA (including the factors: judge, sample, and replication, as well as corresponding two-way interactions), multiple comparison analysis (Fisher's least significant difference, p < 0.05), Pearson correlation analysis, principal component analysis (PCA), multiple factor analysis (MFA), multiple linear regression, and graphical construction will be carried out using XLSTAT 2021.3.1 (Addinsoft, NY, USA).14 Initially multivariate statistics will be used to determine the most variable samples based on their volatile and nonvolatiele profiles (~10-20) for sensory analysis. These tests and graphs will then also be used to evaluate the significant differences in the aroma, taste, and mouthfeel profiles between the different rice varieties and to assess the associations between the chemical and sensory data. In addition, we will work with our collaborators to generate potential linkages to genomic data for key impact compounds, work to describe the general ranges of targets for key features in aromatic rice, and asses if GxE and/or year effects are having a major influence on the findings. These preliminary findings will then be used for future grant submissions.