GEM Presentation GEM Team USDA-ARS NCRPIS GEM - December 8, G ermplasm E nhancement of M aize

Quality Trait Research Susan Duvick Corn Quality Traits Lab Manager

Wet Chemistry Laboratory

Personnel Susan Duvick, Laboratory Manager (NCRPIS) Susan Duvick, Laboratory Manager (NCRPIS) Kaily Chang, Research Associate (CICGRU) Kaily Chang, Research Associate (CICGRU) Oswaldo Taboada-Gaytan, Graduate Student (CICGRU) Oswaldo Taboada-Gaytan, Graduate Student (CICGRU) Joe Van Gorp, Undergraduate Intern (CICGRU) Joe Van Gorp, Undergraduate Intern (CICGRU) Carli Petersen, Undergraduate Intern (NCRPIS) Carli Petersen, Undergraduate Intern (NCRPIS) Cooperating scientists and project members Cooperating scientists and project members

Corn Quality Traits Laboratory Primary Functions Primary Functions Germplasm evaluation for quality traits Germplasm evaluation for quality traits Method development for new quality traits Method development for new quality traits Research leading to high quality corn germplasm Research leading to high quality corn germplasm CRIS Projects CRIS Projects Germplasm enhancement of maize project (GEM) (Mike Blanco) Germplasm enhancement of maize project (GEM) (Mike Blanco) Enhancing corn germplasm for quality traits (Linda Pollak) Enhancing corn germplasm for quality traits (Linda Pollak) Breeding high-quality corn for sustainable, low-input farming systems (Linda Pollak) Breeding high-quality corn for sustainable, low-input farming systems (Linda Pollak) Quantitative genetics and grain quality of corn (Paul Scott and Jode Edwards) Quantitative genetics and grain quality of corn (Paul Scott and Jode Edwards)

Current Analytical Methods Whole grain composition (POS) by NIR using sample sizes from 1 kernel to 1 pound Whole grain composition (POS) by NIR using sample sizes from 1 kernel to 1 pound Specific density by NIR using sample sizes from 1 ear to 1 pound Specific density by NIR using sample sizes from 1 ear to 1 pound Extractable starch by NIR using sample sizes from 1 ear to 1 pound Extractable starch by NIR using sample sizes from 1 ear to 1 pound Starch thermal properties by DSC using sample sizes from 1 kernel to bulk starch samples Starch thermal properties by DSC using sample sizes from 1 kernel to bulk starch samples Starch viscosity properties by RVA using sample sizes of starch from at least 10 grams of corn Starch viscosity properties by RVA using sample sizes of starch from at least 10 grams of corn Fatty acids by GC from single kernels Fatty acids by GC from single kernels Wet milling by both bench top single kernels and 100g using a starch table Wet milling by both bench top single kernels and 100g using a starch table

NIR Whole Grain Composition

NIR Sample Sizes

GEM Results-Composition Protein > 15% Protein > 15% Oil > 4% Oil > 4% Starch > 71% Starch > 71% B73 values: 14% protein, 3.5% oil, 70% starch B73 values: 14% protein, 3.5% oil, 70% starch

Starch Extraction

Bench Top Wet Milling

100g Wet Milling

Starch Thermal Analysis

DSC Curve CH05015:N B-B

GEM Results-Starch Quality ToG < 62 o C ToG < 62 o C TrG < 5 o C TrG < 5 o C %R > 60% %R > 60% Commercial corn starch: ToG, TrG, %R Commercial corn starch: ToG, TrG, %R

Field Day 2004

Recommended GEM Lines for 2004 PedigreeOrigin (race)SETComment BARBGP:N08a B Barbados (Tuson)2004 S4 elevated starch and oil CH05015:N B Chile (Camelia)2004 S4elevated protein CHIS775:S1911b B-B Mexico (Tuxpeno)Set R elevated oil and protein, high TpG, flat-top peak DK212T:N11a B Thailand (comm. DK)2004 S4high starch DKB844:S B-B Mexico (comm. DK)Set E low gel onset temp; low PHI, wide RnG DREP150:N2011d B Domin. Rep. (Mixed)2004 S4elevated protein UR11003:S B Uruguay (Dente Branco) Set H narrow range of gelatinization DKB844:S Mexico (comm. DK)Set E Elevated protein, low gel temp onset, low RnG, high % retro CH05015:N Chile (Camelia)Set H Elevated protein and oil, very high TpG, large complex peak

New Methodology ETOH by bench top laboratory procedure ETOH by bench top laboratory procedure Food applications of oils with altered fatty acids Food applications of oils with altered fatty acids Calculating breeding parameters for quality traits Calculating breeding parameters for quality traits Modeling from our existing data to predict resistant starch Modeling from our existing data to predict resistant starch Thermoelectric conductivity and electroactive transport Thermoelectric conductivity and electroactive transport Plasticizing starches Plasticizing starches

GEM Presentation The End G ermplasm E nhancement of M aize