Hostname: page-component-78c5997874-8bhkd Total loading time: 0 Render date: 2024-11-17T23:26:04.688Z Has data issue: false hasContentIssue false

The agroclimatic analysis at farm scale

Published online by Cambridge University Press:  01 March 2007

Simone Orlandini
Affiliation:
Department of Agronomy and Land Management, University of Florence, Piazzale delle Cascine 18, 50144 Florence, Italy Email: simone.orlandini@unifi.it
Anna Dalla Marta
Affiliation:
Department of Agronomy and Land Management, University of Florence, Piazzale delle Cascine 18, 50144 Florence, Italy Email: simone.orlandini@unifi.it
Marco Mancini
Affiliation:
Department of Agronomy and Land Management, University of Florence, Piazzale delle Cascine 18, 50144 Florence, Italy Email: simone.orlandini@unifi.it
Get access

Abstract

Research was performed in Poggio Casciano Estate (Chianti area, central Italy) with the aim of defining a general approach to analyse the spatial variability of temperature at the microscale. Hourly data were collected from a network of 27 temperature stations covering an area of about 120 ha and determination coefficients r between station pairs on the basis of different geo-topographical factors were calculated. The data were analysed in order to investigate trends describing the spatial distribution of temperature inside the study area. The results pointed out a strong effect of some topographical condition on the distribution of thermal patterns, in particular altitude and the distance from valley bottoms. The results are discussed in order to formulate a general approach for the characterisation of climatic conditions at small scale.

Type
Research Article
Copyright
Royal Meteorological Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aggarwal, P. K. 1993 Agro-ecological zoning using crop simulation models: characterization of wheat environments of India. In: Vries, F. W. T. Penning de, Teng, P. S. & Metselaar, K. (eds.), Systems Approaches for Agricultural Development. Dordrecht, The Netherlands: Kluwer, pp. 97109.Google Scholar
Camargo, M. & Hubbard, K. 1999 Spatial and temporal variability of daily weather variables in sub-humid and semi-arid areas of the united states high plains. Agric. Forest Meteorol. 93: 141148.CrossRefGoogle Scholar
Carlson, R. E., Enz, J. W. & Baker, D. G. 1993 Quality and variability of long term climate data relative to agriculture. Agric. Forest Meteor. 69: 6174.CrossRefGoogle Scholar
Caruso, C. & Quarta, F. 1999. Interpolation methods comparison. Comput. Math. Appl. 35 (12): 109126.CrossRefGoogle Scholar
Chapman, S. C., Edmeadas, G. O. & Crossa, J. 1996 Pattern analysis of gains from selection for drought tolerance in tropical maize populations. In: Cooper, M. & Hammer, G. L. (eds.), Plant Adaptation and Crop Improvement. Wallingford, UK: CAB International, pp. 513528.Google Scholar
Dalla Marta, A., Mancini, M. & Orlandini, S. 2003 Analysis of interpolation methods applied at different spatial scales. In: Proceedings of the Sixth European Conference ‘Applications of Meteorology’, Rome, Italy, 15–19 September 2003 (CD-ROM).Google Scholar
Godwin, R. J., Richards, T. E., Wood, G. A., Welsh, J. P. & Knight, S. M. 2003 An economic analysis of the potential for precision farming in UK cereal production. Biosyst. Eng. 84 (4): 533545.CrossRefGoogle Scholar
Hammer, G. L., Kropff, M. J., Zincalir, T. R. & Porter, J. R. 2002 Future contributions of crop modeling—from heuristics and supporting decision making to understanding genetic regulation and aiding crop improvement. Eur. J. Agron. 18: 1531.CrossRefGoogle Scholar
Harcum, J. B. & Loftis, J. C. 1987 Spatial interpolation of Penman evapotranspiration. Trans. Am. Soc. Agric. Eng. 30 (1): 129136.CrossRefGoogle Scholar
Hoogenboom, G. 2000 Contribution of agrometeorology to the simulation of crop production and its applications. Agric. Forest Meteorol. 103: 137157.CrossRefGoogle Scholar
Hopkins, J. S. 1979 The spatial variability of daily temperature and sunshine over uniform terrain. Meteorol. Mag. 106: 278292.Google Scholar
Hubbard, K. G. 1994 Spatial variability of daily weather variables in the high plains of the USA. Agric. Forest Meteorol. 68: 29–41.CrossRefGoogle Scholar
Maracchi, G. 2003 Meteorologia e climatologia applicate. Florence, Italy: Editrice L’Universo.Google Scholar
Maracchi, G., Dunkel, Z. & Orlandini, S. 2002 European agrometeorological applications. In: Sivakumar, M. V. K. (ed.), Proceedings of the Inter-Regional Workshop ‘Improving Agrometeorological Bulletins’, Bridgetown, Barbados, 15–19 October 2001. Geneva, Switzerland: World Meteorological Organization, pp. 261274.Google Scholar
Meinke, H. & Hammer, G. L. 1995 A peanut simulation model. II: Assessing regional production potential. Agron. J. 87: 10931099.CrossRefGoogle Scholar
Neményi, M., Mesterhàzi, P. A., Pecze, Z. S. & Stepan, Z. 2003 The role of GIS and GPS in precision farming. Comput. Electron. Agric. 40: 4555.CrossRefGoogle Scholar
Orlandini, S., Moriondo, M. & Mancini, M. 2000 Bio-climatic characterisation of hilly area. In: Proceedings of the Third European Conference ‘Applied Climatology’, 16–20 October 2000, Pisa, Italy (CD ROM).Google Scholar
Qiyao, L., Baopu, F. & Jingming, Y. 1987 Methods calculating the spatial distribution of agroclimatic resources in mountainous areas and climatic effects of microtopography. Acta Meteorol. Sin. 2 (3): 380393.Google Scholar
Semenov, M. A. & Porter, J. P. 1995. Climatic variability and the modelling of crop yields. Agric. Forest Meteorol. 73: 265283.CrossRefGoogle Scholar
Shorter, R., Lawn, R. J. & Hammer, G. L. 1991 Improving genotypic adaptation in crops—-a role for breeders, physiologists and modellers. Exp. Agric. 27: 155175.CrossRefGoogle Scholar
Soderstrom, M. & Magnusson, B. 1995. Assesment of local agroclimatological conditions. Agric. Forest Meteorol. 72: 243260.CrossRefGoogle Scholar
Soltani, A., Khooie, F. R., Ghassemi-Golezani, K. & Moghaddam, M. 2000 Thresholds for chickpea leaf expansion and transpiration response to soil water deficit. Field Crops Res. 68: 205210.CrossRefGoogle Scholar
Thornton, P. E., Running, S. W. & White, M. A. 1997 Generating surfaces of daily meteorological variables over large regions of complex terrain. J. Hydrol. 190: 214251.CrossRefGoogle Scholar