APPLICATION OF MATHS IN AGRICULTURE.pptx

application of math's in agriculture

1. Application Of Maths In Agriculture Presented By, Karthikeyan.G M.Sc.Mathematics Mannar Thirumalai Naicker College, Pasumalai,Madurai-04

2. Introduction Agriculture the cultivation and breeding farm , produce , raise, grow-cultivate by growing , often involving improvements by means of agriculture techniques. Agriculture the science occupation with cultivating land , raising crops. Agriculture cultivation of animals , plants ,fiber ,biofuel , medicinal plants and products used to sustain and human life.

3. Mathematics & Agriculture Mathematics is directly applied in Measuring many aspects in agriculture, like. Measurement of land. Average investment and average return. Production per unit area and cost . Time and work. Seed rate and manure rate.

4. AGRICULTURE IN GENRATION

5. Mathematics in agriculture strong industrial need Precision farming: “precision farming is a farming management concept based on observing ,measuring and responding to inter and inter-field variability in crops”. Crop variability typically has both a spatial and temporal component statistical/computational treatments quite involved .

6. GROWTH

7. Growth increase

8. Plant growth modelling Bioclimatology soil sciences Botany plant architecture Agronomy:Ecophysiolgy Applied Mathematics stochastic processes dynamical systems optimization,control Plant growth simulation Computer sciences simulation visuallization

9. A model combining two approaches Morphological models=>simulation of 3D development Process-based models => yield prediction as a function of environmental conditions Biomass water Nutriments CO 2 Organogenesis + empirical Geometry=plant Architecture Biomass acquisition ( photosynthesis, root nutriment uptake)+ biomass partitioning Functional-structural models

10. Growth cycle Development of new architectural units : Continuous : agronomic plants or tropical tress. Rhythmic : trees in temperate regions. Organogenesis cycle=Growth cycle ,time for the model. For continuous growth , the number of phytomers depends linearly on the sum of daily temperatures.

11. Growth Graph

12. A generic equation to describe sources –sinks dynamics along plant growth Environment No stress W. stress Energetic efficiency Development Sinks function

13. Example Plants = Dynamic system State variables Xn = vector of biomass production Input variables Un = environment ( light,tempreature , soil water content) Parameter P Observation Y = G( Xn,P ) Trace back organogenesis dynamics form static data collected on plant architecture (numbers of organs produced, modelling of bud functioning) Trace back source sink dynamics (biomass production and allocation) from static data on organ masses.

14. Agriculture in India backbone. Agriculture in India has a significant history. Today India ranks second world wide in farm output. Agriculture and alied sectors like forestry and fisheries accounted for of the work force. Conclusion

15. Agriculture to economic contribution of agriculture to India . Declining with the country’s broad based economic growth. Still agriculture is demographically the broadest economic. Sector and plays a significant role .

16. References M. Ellis, B. Williams, H. Sadid , K.W. Bosworth, and L. Stout, "Math usage by practicing engineers: What does it mean to curriculum planners" Proceedings of the Annual ASEE Conference, 20 pages, 2004. Y. Shibberu , "What is the Role of Mathematical Modeling in Core Mathematics Courses for Engineering Students" Retrieved from: http://www.ing.unp.edu.ar/asignaturas/algebra/shibberu.pdf . D. Wedelin , "Mathematical Modelling for Software Engineering Students," Pedagogical Papers Series, Spring, 2009, ISBN/ISSN 1654-3009, www.cs.chalmers.se/~dag/docs/matmodReport6.pdf .

17. 4. C . Huang, "Investigating engineering students' mathematical modelling competency," World Transactions on Engineering and Technology Education, 10, 2, 99-104, 2012 . 5. M.E . Cardella , " Mathematical Modeling in Engineering Design Projects," Modeling Students' Mathematical Modeling Competencies, part 3, 87-98, 2010 . 6. G . Kaiser, M. Blomhøj , B. Sriraman , "Towards a didactical theory for mathematical modelling ," Zentralblatt für Didaktik der Mathematik , 38, 2, 82-85, April, 2006 . 7. K . Maaß , "What are modelling competencies" Zentralblatt für Didaktik der Mathematik , 38, 2, 113-142, April, 2006 . 8.M . Niss , "Mathematical competencies and the learning of mathematics: The Danish KOM project," 3rd Mediterranean Conference on Mathematics Education, Athens, Greece: Hellenic Mathematical Society and Cyprus Mathematical Society, 115-124, 2003.

18. 9. OECD , Programme for International Student Assessment (PISA) Assessment Framework-Key competencies in reading, mathematics and science, 2009. Retrieved from: www.oecd.org/dataoecd/11/40/44455820.pdf . 10. M . Niss , "The Danish KOM project and possible consequences for teacher education," Journal of research and training in mathematics education No9: Curriculum, assessment, teacher training, skills, ISSN: 1659-2573.( Cuadernos de Investigación y Formación en Educación Matemática . Año 6. Número 9.), 13-24, Costa Rica, 2011.

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