Pistoia Alliance US Conference 2015 - 1.2.2 Innovation in other industries - Bruce Rasa
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Pistoia Alliance US Conference 2015 - 1.2.2 Innovation in other industries - Bruce Rasa
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Pistoia Alliance US Conference 2015 - 1.2.2 Innovation in other industries - Bruce Rasa
- 1. Mobile voice-capture solutions for efficiency & productivity Bruce Rasa, CEO and Founder, TekWear AGVOICETM
- 2. Ag-enterpriseproblemtoday Criticalworkflow-reportinggap 2 Paper based record-keeping prevalent despite inadequacies Consumer demands for farm-to-fork transparency Retailer demands for sustainable agriculture and traceability
- 3. Eric Jackson Principal Geneticist/Systems Biologist General Mills Crop Bioscience
- 4. Cereal Snacks Baked Goods Meals Dairy Crop Biosciences Grain Fruit Agronomy Sustainability General Mills
- 5. Grower Needs Miller Needs Product Needs Consumer needs Johnson L. 2002. A dozen years of marker assisted sweet corn breeding. Presented at the International Plant and Animal Genome Meeting, San Diego, CA USA, 12 January 2002. Advantaged Finished Product Yield Components (common) Processing components (Proprietary) Hedonic components (Proprietary) Complex Breeding Targets
- 6. Make crosses Inbreed, isolate lines Small-scale trial and selection Large-scale trial and selection Release cultivar Five to seven years Ten to twelve years Product testing and seed increase Four to six years Fourteen to eighteen years Commercialization Classic Breeding to Commercialization Cycle
- 7. The Classic Breeding Cycle is Challenged by The Marketing Cycle The Reality of LifeâŠ
- 9. Make crosses Small-scale trial Large-scale trial Release cultivar Make crosses Advance populations Genotype Small-scale trial/Phenotype Large-scale trial/Phenotype Release cultivar Develop Prediction model/Evaluate Crosses Five to seven years Ten to twelve years Twoyears Fouryears Six to seven years Product testing and seed increase Four to six years = 18 years total Optimized Breeding toCommercialization Cycle One to Two years = 7-9 years total Contract End-Use Prediction Inbreed, isolate lines
- 13. FullyAutomated Workflows r Cross Validation Optimal Population size Model evaluation Predictor Reduction
- 15. Min. -1 ÎŒ 1 Max. SD ï 1 million crosses ï 1 billion progeny Training population 50 crosses 20 lines/cross All pair-wise crosses 1,000 progeny/1,000 progeny The Power of Cross Evaluation
- 16. First round selections p_id m_id _stand_Max _stand_Rang e cases_a_Ma x cases_a_Rang e __recovery_Ma x __recovery_Rang e __broken_Mi n __broken_Rang e _barren_Mi n _barren_Rang e R10Y29006 R10Y29265 44.69219871 1.777431561 518.1309745 14.64071949 0.442564923 0.028086569 0.189667176 -0.008464313 0.374090784 0.01507217 R10Y29246 R10Y29265 43.95027508 1.039387864 522.6514852 -3.449515999 0.444126708 0.009561886 0.177029358 0.000743637 0.359329772 0.013659512 R10Y29246 R10Y29270 43.63446413 1.913630808 517.8734575 3.45800672 0.441117766 0.011358272 0.17205068 0.002952921 0.368395154 0.004147268 R10Y29246 R10Y32023 43.7315396 1.039387864 522.6514852 -4.577192414 0.444126708 0.007951696 0.176221751 0.001551244 0.361536279 0.01542278 R10Y29246 R10Y32025 43.06455186 1.518941218 517.8734575 -8.444397348 0.441117766 0.014329723 0.17460368 0.003318882 0.357566504 0.014975918 R10Y29265 R10Y29265 44.66953028 0.982067264 524.026492 -1.85765549 0.444126708 0.010309384 0.179238642 -0.001615214 0.353312564 0.019024488 R10Y29265 R10Y29270 44.35371934 1.856310208 519.2484643 5.049867229 0.441117766 0.01210577 0.174259964 0.00059407 0.362377946 0.009512244 R10Y29265 R10Y32023 44.4507948 0.982067264 524.026492 -2.985331905 0.444126708 0.008699194 0.178431035 -0.000807607 0.355519071 0.020787756 R10Y29265 R10Y32025 43.78380706 1.461620618 519.2484643 -6.852536839 0.441117766 0.015077221 0.176812964 0.000960031 0.351549296 0.020340894 R10Y29270 R10Y32023 44.13498386 1.856310208 519.2484643 3.922190814 0.441117766 0.01049558 0.173452357 0.001401677 0.364584453 0.011275512 R10Y32023 R10Y32023 44.23205932 0.982067264 524.026492 -4.11300832 0.444126708 0.007089004 0.177623428 0 0.357725578 0.022551024 Average: 44.06344764 1.400838376 520.8187026 -0.473532188 0.442617027 0.012278572 0.177217367 5.7757E-05 0.360544309 0.01516087 Recurrent Selections Round 1 p_id m_id _stand_Score cases_a_Score __recovery_Score __broken_Score _barren_Score R10Y29265 R10Y32023 43.89548048 530.3234663 0.444126708 0.177623428 0.36262474 R10Y32023 R10Y32023 43.49333887 530.3234663 0.444126708 0.177623428 0.364055556 R10Y32023 R10Y32023 43.51027699 530.3234663 0.444126708 0.177623428 0.364415257 R10Y32023 R10Y32023 43.51027699 530.3234663 0.444126708 0.177623428 0.364415257 R10Y29265 R10Y29265 44.59265149 522.5657156 0.440906328 0.179238642 0.369762986 R10Y29265 R10Y29265 44.51577269 525.877358 0.442516518 0.178431035 0.364815218 R10Y29265 R10Y29265 44.34930467 523.693392 0.438972016 0.178431035 0.3597373 R10Y29265 R10Y32023 44.11363108 525.877358 0.435427514 0.178431035 0.365279814 R10Y29265 R10Y32023 44.2138032 525.9130514 0.444126708 0.177623428 0.364482766 R10Y32023 R10Y32023 43.84755303 526.4802844 0.440582206 0.177623428 0.364965058 Average: 44.00420895 527.1701025 0.441903812 0.178027231 0.364455395 Recurrent Selection Round 2 p_id m_id _stand_Max _stand_Range cases_a_Max cases_a_Rang e __recovery_Max __recovery_Rang e __broken_Min __broken_Rang e _barren_Min _barren_Range R10Y29265 R10Y32023 202 R10Y29265 R10Y32023 202 44.37450089 0.958040811 530.3234663 0 0.444126708 0 0.177623428 0 0.352931506 0.019386468 R10Y29265 R10Y32023 202 R10Y32023 R10Y32023 206 44.0725314 0.739305331 530.3234663 0 0.444126708 0 0.177623428 0 0.356294762 0.014450473 R10Y29265 R10Y32023 202 R10Y32023 R10Y32023 31 44.05559329 0.722367219 530.3234663 0 0.444126708 0 0.177623428 0 0.355328542 0.016023212 R10Y29265 R10Y32023 202 R10Y32023 R10Y32023 426 44.0725314 0.739305331 530.3234663 0 0.444126708 0 0.177623428 0 0.356294762 0.014450473 R10Y32023 R10Y32023 206 R10Y32023 R10Y32023 206 43.77056191 0.520569852 530.3234663 0 0.444126708 0 0.177623428 0 0.359658018 0.009514478 R10Y32023 R10Y32023 206 R10Y32023 R10Y32023 31 43.7536238 0.50363174 530.3234663 0 0.444126708 0 0.177623428 0 0.358691798 0.011087217 R10Y32023 R10Y32023 206 R10Y32023 R10Y32023 426 43.77056191 0.520569852 530.3234663 0 0.444126708 0 0.177623428 0 0.359658018 0.009514478 R10Y32023 R10Y32023 31 R10Y32023 R10Y32023 31 43.73668569 0.486693628 530.3234663 0 0.444126708 0 0.177623428 0 0.357725578 0.012659956 R10Y32023 R10Y32023 31 R10Y32023 R10Y32023 426 43.7536238 0.50363174 530.3234663 0 0.444126708 0 0.177623428 0 0.358691798 0.011087217 R10Y32023 R10Y32023 426 R10Y32023 R10Y32023 426 43.77056191 0.520569852 530.3234663 0 0.444126708 0 0.177623428 0 0.359658018 0.009514478 R10Y29265 R10Y32023 160 R10Y29265 R10Y32023 160 44.51577269 0.804283219 527.0050344 2.25535283 0.437037704 0.00322038 0.179238642 -0.001615214 0.361500568 0.007558492 Year1Year2Year3 âŠOver Virtual YearsâŠPower to Know
- 17. Time Gain Standard Plant Breeding (Linear) End-Use Genomic Selection (Exponential)
- 18. Sweet Crispiness Hardness Yield Color Xanthamonas Sulfur Bitter 25.0 kgs/ha 5.0 deep green 5.8 scale 4.4 scale 4.7 scale 0.21 scale 5.3 scale 5.5 scale 4.0 17.0 4.2 5.6 5.3 0.6 4.2 4.6 11.0 3.8 4.6 5.1 0.58 3.7 4.7 The Power of End-Use Projection
- 19. DNA Proteins Traits Metabolites LOGICAL UNDERPINNING CURATED KNOWLEDGE YOU LUCKY of for Smart data collection = Information & Learning Data Workflows = Neurological Net
- 20. Mobile voice-capture solutions for efficiency & productivity. AGVOICETM Solution:
- 21. Data & Reports Compliance Work instructions Sustainability data Client invoices Daily, weekly reports Voice Recognition Regional accents Technical terms Brand names Work Flow/Checklists Agricultural database Weather history Fertilizer Water usage Imagery Retrieve Generate Voice notes Photos Geo-coordinates Sensor measurements Time stamps TekWear Copyright
- 22. Voice-Assist Design Enterprise Workflow Work Orders Universal Access Partner API Walkie-Talkie Mode Spring 16â 2H 16â 2H 17â+ Critical Alerts Offline Mode Voice Search Spanish English Big Data Analytics Pro-Active Assistant AGVOICE- Roadmap TekWear Copyright 8 Under Development Phase 2 Phase 3 Phase 4 IP 22 Claims Filed: April, 2015 U.S. & International
- 23. Anexperiencedteam: CEO Bruce Rasa 20+ yrs (IBM, NCR & AGCO) Strategic Mkt & Product Mgmt. Chief Revenue Officer Aaron Gobin 10+ yrs Enterprise Sales Expert Experience Engineer John Swansey 25+ yrs Design & UX Innovation 35 Patents & 40 Design Awards CTO Erick Kobres 25+ yrs Software Innovation Start-up experience , 20+ Patents Key advisors: Phil Ventimiglia Chief Innovation Officer Georgia State University 23 Kip Pendleton Serial Ag-Tech Entrepreneur & Advisor Voice experts including developers of: Amazon ECHO SIRI (Apple) Dragon NaturallySpeaking Google Glass
- 24. GlobalMarketOpportunity $4.3 Billion annually Mobile-to-cloud solution allows global scale Animal Health: 24 Crop Health: Veterinarians Inspectors Producers Ag Professionals Machinery Repair Auditors / Insurance
- 25. Information, data, and drawings embodied in this presentation are strictly confidential and supplied on the understanding that they will be held confidentially and not disclosed without the prior written or electronic consent of TekWear, or itâs members AGVOICETM www.TekWearAg.com Thank You Thank You www.AgVoiceGlobal.com AGVOICETM
Hinweis der Redaktion
- 30 seconds: (Prior 3 attempts were 15, 32, 34 secs) Hi, I am Bruce Rasa and itâs good to be back in my home state⊠Iâm a farm kid from Western MO and an Agriculture Economics Grad from Mizzou.. My father and brother currently farm 3,500 acres of livestock, corn, beans and wheat.. Iâm honored to have them here in the audience today along with my mom. (Point them out. Then wave)
- 60 seconds: (Prior 3 attempts were 51, 53, 1:09 secs) From my familyâs experience and that of the many AgProfessionals we talk to, weâve learned that capturing information and insights when in the field is increasingly vital âŠ. Iâll share some news with you from a top 3 meat producer in the US two weeks ago⊠one of the largest retailers on the planet, announced that they will be placing demands for traceability and sustainable agriculture starting in 2016⊠This is in response to growing concerns about food safety, and consumer desire for âfarm to tableâ transparency. Whether itâs the birthing records of a calf, or growth stage of corn, or pests spotted⊠accurate data capture is key, but cannot be done reliably outdoors with pen and paper, and tap-tapping on an tablet or laptop is not very useful either. Sunlight glare, dust, and the need to use both hands makes it difficult. At the exact time and place when data capture would be most useful, there is no good digital tool to do itâŠ. until now.
- 10 seconds: (Prior 3 attempts were 15, 5, 7 secs) AGVOICE is the solution that these Agri-businesses have been looking for⊠hereâs how it works
- 30 seconds: This is the workflow management missing link where we connect to the Enterprises existing backend that no one else does today for any Agri-business⊠automatically and 100% digital and structured to aid on time decision-making
- 60 seconds: Weâve got a roadmap for AgVoice starting with our essential first release, and adding innovative features in subsequent phases. To clarify, we started building our roadmap pieces 11 months ago when our customer discovery began, and each stage represents the functionality listing that our Enterprise customers have prioritized and are willing to pay for. The features listed in Phase 1 as an example are all the building block within our two statements of work currently being negotiated with Enterprise partners. Phase 1 will be delivered in Spring 2016 â it will include the AGVOICE advanced voice capture, data processing & workflow smart checklist core functionality Phase 2 expands the solution by incorporating offline mode, Voice search, Critical alert triage, Spanish to English translation Phase 3 & Phase 4 is where integration of supplier data, as well as data analytics and processing moves towards allowing our Enterprise customers the ability to move beyond current reactive decision making to a pro-active level
- 45 seconds (prior 3 attempts were 45, 47 & 54 secs) My favorite slide here summarizes the everyday passion that drives our startup forward: Iâve worked with my 3 co-founders in different corporate roles over the past 20 years, and they are the best of the best in their respective disciplines, together we have more than 55 patents filed and 40 international design awards for user experience. Two of our co-founders also have prior startup experience. - Our Advisors complement our expertise from a business, research and successful startup and Agriculture focus â as an example, we won a USDA grant and work with two university systems from a research and execution standpoint. We also leverage key advisors that have worked on the Amazon Echo, Appleâs SIRI, Dragon Voice reco software utilized in the medical industry and with Google voice and natural language processing experts
- 20 seconds: AGVOICE extends to multiple areas of the Food & Ag supply chain, and the common theme we have heard during the past year of customer discovery is that AGVOICE is the missing link to an enterprise workflow problem that is prevalent across the livestock, crop and machinery landscape within global Ag. All together this is a multi-billion $ annual market.
- 20 seconds: AGVOICE is first mover innovation in the industry to solve an everyday problem for Ag-Enterprises. We have an Enterprise development and customer focused team to execute against this vision Thank you. Myself and Aaron Gobin, one of my co-founders, will be here after the event to talk with you, and address any individual questions or interest in partnering with AGVOICE