Books on the topic 'Crop yields – Statistical methods'

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1

Fielder, Lonnie L. Measurement of price, yield, and revenue variability for Louisiana crops. Baton Rouge, La: Dept. of Agricultural Economics and Agribusiness, Louisiana Agricultural Experiment Station, Louisiana State University Agricultural Center, 1985.

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2

Sakamoto, Clarence M. The water satisfaction index for estimating crop yield and harvested/planted area ratio in Botswana. [Gaborone, Botswana]: Republic of Botswana, Dept. of Meteorological Services, Ministry of Works, Transport, and Communications, 1990.

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3

G, Gauch Hugh. Statistical analysis of regional yield trials: AMMI analysis of factorial designs. Amsterdam: Elsevier, 1992.

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4

Manfred, Sievers, ed. Instability in world food production: Statistical analysis, graphical presentation, and interpretation. Kiel, West Germany: Wissenschaftsverlag Vauk Kiel, 1985.

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5

Lakshmi, K. R. Statistical methods for tropical tuber crop research. Thiruvananthapuram: Central Tuber Crops Research Institute, 2003.

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6

Maerz, Ulrich. Methods to simulate distributions of crop yields based on farmer interviews. Aleppo, Syria: International Center for Agricultural Research in the Dry Areas, 1987.

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7

M, Cupello James, and Meadows Becki, eds. Managing Six Sigma: A practical guide to understanding, assessing, and implementing the strategy that yields bottom line success. New York: John Wiley, 2001.

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8

Money and capital markets: Pricing, yields and analysis. 2nd ed. St. Leonards, N.S.W., Australia: Allen & Unwin, 1996.

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9

Maughan, Chris. Field studies on winter milling wheat: Fertiliser nitrogen programmes for yield and quality improvement : evaluation of methods of monitoring crop nitrogen status. Dublin: University College Dublin, 1997.

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10

Harrison, Scott. Productivity differences across New South Wales rice farms: Links to resource quality. Canberra, Australia: ABARE, 1999.

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11

Dillon, John L. The analysis of response in crop and livestock production. 3rd ed. Oxford, England: Pergamon Press, 1990.

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12

Muniyappa, Palaniswamy Kodiveri, ed. Handbook of statistics for teaching and research in plant and crop science. New York: Food Products Press, 2005.

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13

Brunt, Liam. Turning water into wine: New methods of calculating farm output and new insights into rising crop yields during the agricultural revolution. Oxford: University of Oxford, 1996.

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14

Vossen, P. An analysis of agricultural livestock and tradi[ti]onal crop production statistics as a function of total annual and early, mid, and late rainy season rainfall in Botswana. Gaborone: Botswana Meteorological Services, 1987.

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15

Elderen, E. Van. Scheduling farm operations: A simulation model. Wageningen, Netherlands: Pudoc, 1987.

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16

Binns, M. R. Sampling and monitoring in crop protection: The theoretical basis for developing practical decision guides. Wallingford, Oxon, UK: CABI Pub., 2000.

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17

S, Kang Manjit, ed. GGE biplot analysis: A graphical tool for breeders, geneticists, and agronomists. Boca Raton, Fla: CRC Press, 2003.

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18

Bhatti, Aman Ullah. Application of geostatistics and nearest neighbor analysis methods to statistical analysis of field experiments. 1990.

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19

Jones, James W., Daniel Wallach, David Makowski, and Francois Brun. Working with Dynamic Crop Models: Methods, Tools and Examples for Agriculture and Environment. Academic Press, 2018.

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20

Luis, Foguet José, ed. Rendimiento del cultivo de trigo en Tucumán. Tucumán, Argentina: Estación Experimental Agro-Industrial Obispo Colombres, 1991.

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21

Working with Dynamic Crop Models: Methods, Tools and Examples for Agriculture and Environment. Elsevier Science & Technology Books, 2013.

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22

Eurostat. Crop Yield Forecasting Methods: Proceedings of the Seminar (Theme 0--Miscellaneous. Series D, Studies and Research). Statistical Office of European Communities, 1997.

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23

Dillon, John L., and Jamie G. Anderson. Analysis of Response in Crop and Livestock Production. Elsevier Science & Technology Books, 2012.

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24

Pančhaphan, Santiphāp, and KKU-Ford Rural Systems Research Project (Thailand), eds. Rāingān phon kānwičhai rư̄ang nǣothāng sưksā phư̄a kānphœ̄m phonphalit khō̜ng phư̄t sētthakit bāng chanit dōi kānsamrūat phư̄nthī, kānsưksā sathana khō̜ng thāt ʻāhān nai din, læ thēknōlōyī kānsai pui thī Mūbān Hin Lāt, Tambon Bān Khō̜, ʻAmphœ̄ Mư̄ang, Čhangwat Khō̜n Kǣn =: Studies on increasing yield of some economic crops at Hinlat village, Tambon Bankor, Muang District, Khon Kaen, Thailand, using methods of detailed survey, identification of nutrient deficiency and fertilizer technology. [Khon Kaen]: Khrōngkān Wičhai Kānthamfām, Khana Kasēttrasāt, Mahāwitthayālai Khō̜n Kǣn, 1990.

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25

Jones, James W., Daniel Wallach, David Makowski, and Francois Brun. Working with Dynamic Crop Models: Methods, Tools and Examples for Agriculture and Environment. Elsevier Science & Technology Books, 2018.

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26

Jones, James W., Daniel Wallach, David Makowski, and Francois Brun. Working with Dynamic Crop Models: Methods, Tools and Examples for Agriculture and Environment. Elsevier Science & Technology Books, 2013.

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27

Clewer, Alan G., and David H. Scarisbrick. Practical Statistics and Experimental Design for Plant and Crop Science. Wiley & Sons, Incorporated, John, 2013.

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28

Clewer, Alan G., and David H. Scarisbrick. Practical Statistics and Experimental Design for Plant and Crop Science. Wiley & Sons, Incorporated, John, 2013.

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29

Clewer, Alan G., and David H. Scarisbrick. Practical Statistics and Experimental Design for Plant and Crop Science. Wiley, 2001.

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30

Breyfogle, Forrest W. III, James M. Cupello, and Becki Meadows. Managing Six Sigma: A Practical Guide to Understanding, Assessing, and Implementing the Strategy That Yields Bottom-Line Success. Wiley-Interscience, 2000.

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31

van, Keulen H., and Wolf J, eds. Modelling of agricultural production: Weather, soils, and crops. Wageningen [Netherlands]: Pudoc, 1986.

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32

Binns, M. R., J. P. Nyrop, and W. van der Werf. Sampling and Monitoring in Crop Protection: The Theoretical Basis for Designing Practical Decision Guides (Cabi Publishing). CABI, 2000.

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33

Yan, Weikai, and Manjit S. Kang. GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists, and Agronomists. Taylor & Francis Group, 2002.

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34

Yan, Weikai, and Manjit S. Kang. Gge Biplot Analysis: A Graphical Tool for Breeders, Geneticists, and Agronomists. Taylor & Francis Group, 2010.

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35

Yan, Weikai, and Manjit S. Kang. GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists, and Agronomists. CRC, 2002.

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36

Yan, Weikai, and Manjit S. Kang. Gge Biplot Analysis. Taylor & Francis Group, 2019.

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37

Yan, Weikai, and Manjit S. Kang. GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists, and Agronomists. Taylor & Francis Group, 2002.

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38

Yan, Weikai, and Manjit S. Kang. GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists, and Agronomists. Taylor & Francis Group, 2002.

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39

Yan, Weikai, and Manjit S. Kang. GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists, and Agronomists. Taylor & Francis Group, 2002.

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40

Waller, John. Heredity: A Very Short Introduction. Oxford University Press, 2017. http://dx.doi.org/10.1093/actrade/9780198790457.001.0001.

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The idea of heredity—that qualities of body and mind are somehow inherited from one’s parents—has profoundly shaped many aspects of the human experience: from our attempts to understand variation in personality and intelligence, to popular attitudes about gender, race, and social hierarchy, to the methods employed to increase crop yields and the value of horses and cattle. Heredity: A Very Short Introduction traces both the technical study of biological inheritance and the ideological use of the concept of heredity from antiquity into a modern age of molecular biology in which a brave new prospect is emerging: the capacity to manipulate the human genome itself.
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41

Boken, Vijendra K., Arthur P. Cracknell, and Ronald L. Heathcote. Monitoring and Predicting Agricultural Drought. Oxford University Press, 2005. http://dx.doi.org/10.1093/oso/9780195162349.001.0001.

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Agricultural droughts affect whole societies, leading to higher food costs, threatened economies, and even famine. In order to mitigate such effects, researchers must first be able to monitor them, and then predict them; however no book currently focuses on accurate monitoring or prediction of these devastating kinds of droughts. To fill this void, the editors of Monitoring and Predicting Agricultural Drought have assembled a team of expert contributors from all continents to make a global study, describing biometeorological models and monitoring methods for agricultural droughts. These models and methods note the relationships between precipitation, soil moisture, and crop yields, using data gathered from conventional and remote sensing techniques. The coverage of the book includes probabilistic models and techniques used in America, Europe and the former USSR, Africa, Asia, and Australia, and it concludes with coverage of climate change and resultant shifts in agricultural productivity, drought early warning systems, and famine mitigation. This will be an essential collection for those who must advise governments or international organizations on the current scope, likelihood, and impact of agricultural droughts. Sponsored by the World Meterological Organization
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