universita` di firenze

UNIVERSITA’ DI FIRENZE
DIPARTIMENTO DI SCIENZE AGRONOMICHE
E GESTIONE DEL TERRITORIO AGRO – FORESTALE
“ Attività di consulenza nell’ambito del progetto AGRO-SMART”
Bibliografia
“Studio della modellistica agraria: collegamento di modelli
previsionali con quelli fenologici e di stima del rischio per i
principali agenti fitopatologici delle colture individuate.
S. Orlandini, P. Battista, B. Rapi, A. Dalla Marta, M. Petralli, M. Romani
Firenze ottobre 2008
Bibliografia citata
AA.VV., 2003. PATAM: Projet d'Appui Technique à l’Agro Météorologie. Projet d'Appui à la
Direction de la Météorologie Nationale du Maroc, p. 1072 (CD).
AA.VV. (2007). Run Models and Calculate Degree-Days. IPM Program, Agriculture and Natural
Resources, University of California. http://www.ipm.ucdavis.edu/WEATHER/ddretrieve.html
Abdel-Razik, M., 1989. A model of productivity of olive trees under optional water and nutrient
supply in desert conditions. Ecol. Modelling, 45: 179- 204.
Acock, B., and M.C. Acock. 1991. Potential for using long-term field research data to develop and
validate crop simulators. Agron. J. 83:56–61.
Alcalá, A.R. and Barranco, D., 1992. Prediction of flowering time in olive for the Cordoba Olive
Collection. HortScience 27, pp. 1205–1207.
Alilla, R., Severini, M., Pesolillo, S., 2004. Introduzione della temperatura variabile e della
mortalità nei modelli di popolazione a ritardo distribuito. In: Dalla Marta A., Orlandini S.
(Eds.). Atti del Convegno ‘III Giornate di studio: Metodi Numerici, Statistici e Informatici
nella Difesa delle Colture Agrarie e delle Foreste: Ricerca e Applicazioni, Firenze, 114-118.
Allen, R.G., L.S. Pereira, D. Raes, and M. Smith., 1998. Crop evapotranspiration: Guidelines for
computing crop water requirements. Irr. & Drain. Paper 56. UN-FAO, Rome.
Arnold, J. G., and J. R. Williams., 1989. Stochastic generation of internal storm structure at a point.
Trans. of the ASAE, 32:161- 167.
Atkins, T.A. and Morgan, E.R., 1990. Modelling the effects of possible climate change scenarios on
the phenology of New Zealand fruit crops. Acta Hort. 276, pp. 201–208.
Baldacci E., 1947. Epifitie di Plasmopara viticola (1941-1946) nell’Oltrepo Pavese e adozione del
calendario d’incubazione come strumento di lotta. Atti Istituto Botanico, Lab. Crittogamico,
VIII: 45-85.
Barba, N.W. and De Melo-Abreu, J.P., 2002. Validation of rest completion models in peach trees in
two regions of Portugal. Acta Hort. 592, pp. 445–449.
P. Battista, B. Rapi, M. Romani, A. Dalla Marta, M. Mancini, S. Orlandini, 2007. Rilevanza della
densità spaziale dei punti di misura della temperatura dell’aria, per il calcolo delle sommatorie
termiche: principale fattore guida per modelli fenologici e fitosanitari. Quarte Giornate Studio
su Metodi numerici statistici e informatici nella difesa delle colture agrarie e delle foreste.
Ricerca e Applicazioni. Viterbo, 27-29 marzo 2007, p. 55-56.
Benincasa F., G. Maracchi, P. Rossi, 1991. Agrometeorologia. Cap. 7: Difesa dalle gelate e dalla
grandine, Patron Editore, Bologna, pag. 287-294.
Bindi, M., Fibbi, L., Maselli, F., and Miglietta, F., 2000. Modelling climate change impacts on
grapevine in Tuscany in: Climate Change, Climatic Variability and Agriculture in Europe,
edited by Downing, T. E., Harrison, P. A., Butterfield, R. E., and Lonsdale, K. G.,
Environmental Change Unit, University of Oxford.
Bindi, M., Miglietta, F., Gozzini, B, Orlandini, S., Seghi, L., 1997a. A simple model for simulation
of growth and development in grapevine (Vitis Vinifera L.). I. Model description. Vitis 36: 6771.
Bindi, M., Miglietta, F., Gozzini, B, Orlandini, S., Seghi, L., 1997b. A simple model for simulation
of growth and development in grapevine (*Vitis vinifera* L.). II. Model validation, Vitis;
Germany, 1997, 36 (2) 73-76.
Blaeser M., 1978. Untersuchungen zur epidemiologie des falschen mehltaus an weinreben
Plasmopara viticola (Berk. et Curt.) Berl. Et de Toni. Diss. Univ. Bonn.
Bonati, A.P., 1999. Essential knowledge of rain structure for radio applications based on available
data and models. Proc. Radio Africa '99 workshop, October 25-29, Gaborone, Botswana, 1-11.
Borgo M., 1990. Influenza delle temperature su inoculazioni ed incubazioni di Plasmopara viticola
(B. et C.) Berl. Et De Toni.
Brisson N., Gary C., Justes E., Roche R., Mary B., Ripoche D., Zimmer D., Sierra J., Bertuzzi P.,
Burger P., Bussière F., Cabidoche Y.M., Cellier P., Debaeke P., Gaudillère J.P., Hénault C.,
Maraux F., Seguin B. e H. Sinoquet, 2003. An overview of the crop model STICS. Eur. J. Agr.,
18:309-332.
Calvi Parisetti C., 1983. A Bayesian approach in the estimation of the abundance of an insect
population. Proc. EC Expert's Meeting, Parma: 58-61
Campbell G., 1985. Transport models for soil-plant systems. Elsevier, Amsterdam.
Chow, V.T., 1964. Handbook of applied hydrology. McGraw-Hill, New York, NY, USA.
Chuine I., Rehfeldt G.E. and Aitken S.N., 1996. Height growth determinants and adaptation to
temperature in pines: a case study of Pinus contorta and Pinus monticola, Can. J. For. Res. 36,
pp. 1059–1066.
Collins F.C. and Bolstad P.V., 1996. A Comparison of Spatial Interpolation Techniques in
Temperature Estimation. Proceedings of the Third International Conference/Workshop on
Integrating GIS and Environmental Modelling. Santa Fe.
Conese C., Rapi B., Romani M., Bonora L., Dambra C., 2005. New tools for wineyard
management. In A. Quintanilla e S. Montesinos “Methodological approach for vineyard
inventory and management”, Univ. of Castilla La Mancha. Spain. p. 127-143; 195- 200.
Connolly, R.D., J. Schirmer, and P.K. Dunn., 1998. A daily rainfall disaggregation model. Agric.
Forest Meteorol., 92:105-117.
Cossu A., Cresto P. C., Delrio G., Locci L., Mannoni M., 1996. Development of a simulation
model for olive fly population management. Proc. XX Int. Congr. Entomology, Firenze, 25-31
Agosto: 709.
Crovetti A. Quaglia F., Loi G., Rossi E., Malfatti P., Chesi F., Conti B., Belcari A., Raspi A.,
Paparatti B., 1982. Influenza di temperatura e umidità sullo sviluppo degli stadi preimmaginali
di Dacus oleae (Gmelin). Frustula Entomologica N.S. V: 133-166.
Danuso F., Bigot L., Budoi G. e D. Franz, 1999. CSS: a modular software for cropping system
simulation. Proc. Int. Symp.”Modelling cropping systems”, ESA, Lleida, 21-23 June 1999,
Catalonia, Spain, pp. 287-288.
Danuso, F., 2002. Climak: a stochastic model for weather data generation. Ital. J. Agron., 6:57-71.
De Melo-Abreu, J.P. and Campbell, G.S., 1996. Simulation of weather variables. Inst. Sup. Agron.
(Lisbon) 45, pp. 45 163–189.
De Wit, C.T., Goudriaan, J., Van Laar, H.H., 1978. Simulation of Assimilation, Respiration and
Transpiration of Crops. Pudoc, Wageningen, The Netherlands.
Delrio G., 1989. Mass trapping experiments to control the olive fruits fly in Sardinia.Proceedings of
the CEC/IOBC International Symposium "Fruit Flies of Economic Importance 87", Rome,
Italy, 7-10/04/1987, pp. 419-425.
Delrio G., 1995. Controllo integrato dei fitofagi dell'olivo. Inf. Fitopatol., 12: 9-15.
Delrio G., Luciano P. and Prota R., 1987. Researches on Grape-Wine moths in Sardinia. In:
Cavalloro R. (ed). Integrated pest control in Viticulture. A.A. Balkena, Rotterdam, Netherlands:
57-67;
Delrio G., Luciano P., Prota R., 1979. Dix ans d'observations sur l'entomofaune nuisible au chéneliège en Sardaigne, pour la protection de la forét. Boll. Soc. Sarda Sci. Nat. 18: 71-97.;
Donatelli M., M. Acutis, M. Balderacchi, S. Barbieri, L.m Bechini, G. Bellocchi, R. Bonera,
L.Carlini, F. Danuso, D.Degli Esposti, D. Ditto, G. Fila, F. Fontana, , A. Gentile, F.Mazzetto,
P. A. Nasuelli, P. Sacco, M. Speroni, M.Trevisan, V. Vetrano, M. Zuliani, 2006. Progetto
SIPEAA, CRA-ISCI Bologna.
Doorembos J. e A.H. Kassam, 1979. Yield response to water. FAO Irrigation and Drainage Paper n.
33, Rome.
Dumortier, D. 2002. Prediction of air temperatures from solar radiation. SoDA deliverable D-5-2-4.
Internal document.
Ephrath, J.E., J. Goudriaan, and A. Marani, 1996. Modelling diurnal patterns of air temperatures,
radiation, wind speed and relative humidity by equations for daily characteristics. Agr. Sys.,
51:377-393.
Fletcher B. S., Comins H., 1985. The development and use of a computer simulation model to study
the population dynamics of Dacus oleae and other fruit flies. Atti XIV Congr. Naz. Ital.
Entomol., Palermo: 561-575.
Fornaciari, M., Pieroni, L., Ciuchi, P. and Romano, B., 1998. A regression model for the start of the
pollen season in Olea europaea. Grana 37, pp. 110–113.
Gabel, B. 1981. Volatile halogenated compounds (VOCHal) in drinking waters of the FRG. Sci.
Total Environ. 18, 363-366.
Galán, C., García-Mozo, H., Cariñanos, P., Alcázar, P. and Domínguez-Vilches, E., 2001. The role
of temperature in the onset of the Olea europaea L. Pollen season in southwestern Spain. Int. J.
Biometeorol. 45, pp. 8–12.
Garcia-Mozo, H., Orlandi, F., Galan, C., Fornaciari, M., Romano, B., Ruiz, L., Diaz de la Guardia,
C., Trigo, M. M., Chuine, I., 2007. Olive flowering phenology variation between different
cultivars in Spain and Italy: modeling analysis (www.springerlink.com/content/101580/...)
Geng, S., F.W. Penning de Vries, and I. Supit, 1986. A simple method for generating daily rainfall
data. Agric. For. Hydrol., 36:363-376. Gibbs e Maher (1967).
Gilbert, N., A. P. Gutierrez, B. D. Frazer and R. E. Jones, 1976. Ecological Relationships. W. H.
Freeman & Co. Ltd., San Francisco, CA.
Gilreath, P.R. and Buchanan, D.W., 1981. Rest prediction model for low-chilling sungold nectarine.
J. Am. Soc. Hort. Sci. 106, pp. 426–429.
Girolami V., 1979. Studi biologici e demoecologici sul Dacus oleae (Gmelin). Influenza dei fattori
ambientali abiotici sull’adulto e sugli stadi preimmaginali. Redia 62: 147-91.
Goudriaan, J., and H.H. Van Laar, 1994. Modelling potential crop growth processes. Kluwer
Academic Publishers, London, United Kingdom.
Hartkamp A. D., De Beurs K., Stein A. and White J.W., 1999. Interpolation Techniques for Climate
Variables. NRG - Natural Resources Group. Sub-department Soil Science and Geology,
Department of Environmental Sciences, Wageningen Agricultural University, PO Box 37, 6700
AA Wageningen, The Netherlands;
Hodges T., 1991. Predicting crop phenology, CRC Press, Boston;
Hutchinson, M.F., and Corbett J.D., 1995. Spatial interpolation of climate data using thin plate
smoothing splines. In: Coordination and harmonization of databases and software for
agroclimatic applications. Agroclimatology Working paper Series, no. 13. Rome, FAO.
Iñaki Garcia De Cortazar Atauri, 2006. Adaptation du modele stics a la vigne (vitis vinifera
l.).utilisation dans le cadre d'une etude d'impact du changement climatique a l'echelle de la
France. Docteur De L'ecole Nationale Superieure Agronomique De Montpellier
Janssen, P.H.M. and Heuberger, P.S.C., 1995. Calibration of process-oriented models. Ecol. Model.
83, pp. 55–66.
Jato V., Rodriguez-Rajo F.J., Mendez J., Aira m.J., 2002. Phenological behaviour of Quercus in
Ourense (NW Spain) and its relationships with the atmospheric pollen season. Int. J.
Biometeorol. 46:176-184.
Jones, G. V., White, M. A., and Cooper, O. R., 2004, Climate change and global wine quality.
Journal Climatic Change, Volume 73, Number 3 / December, 2005, pp. 319-343
Kidd N. A. C., Gazziano S., 1992. Development of population models for olive pest management.
BCPC MONO. 52: 41-46.
Kumral N.A., Kovanci B. and Akbudak B., 2005. Pheromone trap catches of the olive moth, Prays
oleae (Bern.) (Lep.: Plutellidae) in relation to olive phenology and degree-day models, J. Appl.
Entomol. 129: pp. 375–381.
Kumral N.A., Kovanci B. and Akbudak B., 2007. Using degree-day accumulations and host
phenology for predicting larval emergence patterns of the olive psyllid, Euphyllura phillyreae.
J. Pest. Sci. (29ì008), 81:63-69.
Lane, L.J., and M.A. Nearing, 1989. Water Erosion Prediction Project: hillslope profile model
documentation. NSERL report no. 2, USDA-ARS National Soil Erosion Research Laboratory,
West Lafayette, IN, USA.
Loague, K. and Green, R.E., 1991. Statistical and graphical methods for evaluating solute transport
models: overview and application. J. Contam. Hydrol. 7, pp. 51–73.
Logan J. A., Wollkind D. J., Hoyt S. C., Tanigoshi L. K., 1976. An analytical model for description
of temperature dependent rate phenomena in arthropods. Env. Entomol. 5: 1133-1140.
Mancini M., 1999. Caratterizzazione microclimatica di un’area viticola. Tesi di dottorato,
Università degli Studi di Firenze, Facoltà di Agraria, Corso di Laurea in Scienze Agrarie
Dipartimento di Scienze Agronomiche e Gestione del Territorio Agro-forestale, pp. 40.
G. Maracchi and M.V.K. Sivakumar (Eds.), 2000. Handbook of G.I.S. Application in
Agrometeorology, World Meteorological Organization (WMO), Geneva, Switzerland - Roving
Seminar on Geographical Information Systems and Agroecological Zoning (Kuala Lumpur,
Malaysia, May 2000).
Maracchi, G., Matta, A., 1999. La modellistica in viticoltura: applicazioni. Collana TecnicoScientifica INAPA- CNR, Quaderno n° 5, Marzo 1999, Firenze, p. 111.
McIntyre, G.N.,. Lider, L.A, Ferrari, N.L., 1982. The chronological classification of grapevine
phenology. American Journal of Enological Viticulture, 33: 80-85.
Meteotest. 2003. The global meteorological database for engineers, planners and education.
Software and data on CD-ROM. James and James, London, United Kingdom.
Miglietta F. and Ranieri R., 2008. Previsioni di resa e di qualità del grano duro in preraccolto.
Filiera grano duro news, n.5, Febbraio 2008.
Moleas T., 1995. Lotta alle tignole della vite da tavola nell'Italia meridionale. Informatore
Fitopatologico n. 5: 8-11.
Monteith, J.L., 1977. Climate and the efficiency of crop production in Britain. Phil. Trans. R. Soc.
(London) 281, pp. 277–294.
Moriondo M., Orlandini S., Zipoli G., 1999. Modelli di simulazione della fenologia della Vite.
Quaderno n.5 della Collana tecnico-scientifica CNR- INAPA.
Müller K, Sleumer H., 1934. Biologische Untersuchungen über die Peronosporakrankheit des
Weinstocks mit besonderer Berücksichtigung ihrer Bekämpfung nach Inkubationsmethode. Z
Wiss Landwirtsch 79:509-576.
Ndlovu, L. 1994. Weather data generation and its use in estimating evapotranspiration. Ph.D
dissertation. College of Engineering, Washington State University, Pullman WA, USA.
Nelder, J.A. and Mead, R., 1965. A simplex method for function minimization. Comput. J. 7, pp.
308–313.
Nemani, R.R., White, M.A., Cayan, D.R., Jones, G.V., Running, S.W., Coughlan, J.C., Peterson,
D.L., 2001. Asymmetric climatic warming improves California vintages, Clim. Res., 19, 25-34.
Nicks e Harp, 1980.
Nicks, A.D., C.W. Richardson, and J.R. Williams, 1990. Evaluation of the EPIC model weather
generator. In Sharpley A.N., Williams J.R. eds., EPIC-Erosion/Productivity Impact Calculator,
1. Model 56. Documentation, USDA Technical Bullettin No. 1768, 105-124.
Olsson, J., 1998. Evaluation of a cascade model for temporal rainfall disaggregation. Hydrol. Earth
System Sci, 2:19-30.
Orlandi, F., Fornaciari, M. and Romano, B., 2002. The use of phenological data to calculate chilling
units in Olea europaea L. in relation to the onset of reproduction. Int. J. Biomet. 46, pp.2–8.
Orlandini S., Mancini M., 1998. Studio preliminare sulla microzonazione bioclimatica condotto in
un’area viticola collinare: In: atti del simposio Territorio e Vine. Siena, 20-24 maggio 1998,
417-429.
Orlandini S., Mancini M., Maracchi G. and Moribondo M. , 2003. Le gelate primaverili: metodo di
valutazione del rischio per il vigneto, Vignevini n.3: 3-7.
Palese A.M., Sofo A. Celano G. and Xiloyannis C., 2004. Stoccaggio della CO2 ambientale in
giovani piante di olivo. Atti Convegno Europeo “Il futuro dei sistemi olivicoli in aree
marginali: aspetti socio-economici, gestione delle risorse naturali e produzioni di qualità” Matera, 12-13 ottobre 2004.
Palmer, W. C., 1965. Meteorological Drought. Research Paper No. 45, U.S. Department of
Commerce Weather Bureau, Washington, D.C.
Pe´rez-Lo´pez, D., Ribas F. , Moriana A., Olmedilla N. And. De Juan A., 2007. The effect of
irrigation schedules on the water relations and growth of a young olive (Olea europaea L.)
orchard, Agric. Water Manage. 2409, doi:10.1016/j.agwat.2007.01.015.
Pesolillo, S., Severini, M., Alilla, R., 2004. Il modello simulatore di ritardo ‘Delay Simulator’
versione 2.0. Un modello di simulazione su foglio di calcolo elettronico della demografia e
della fenologia delle popolazioni naturali. In: Dalla Marta A., Orlandini S. (Eds.). Atti III
Giornate Studio Metodi Numerici.
Phillips, D.L, Dolph J., and Marks D., 1992. A comparison of geostatistical procedures for spatial
analysis of precipitation in mountainous terrain. Agricultural and Forest Meterology 58:119141.
Pinnola I.M., 1998. Utilizzazione degli indici climatici e bioclimatici per l'agricoltura. Bollettino
Geofisico VI (Agrimeteo), Perugia, pp. 83-106.
Porter, C.H., N.B. Pickering, J.W. Jones, and G. Hoogenboom, 2000. Weather module in DSSAT v.
4.0 documentation and source code listing. Agricultural and Biological Engineering.
Department Research Report No. 2000-1203. University of Florida, Gainesville, FL, USA.
Pucci, C., Forcina, A. & Bagnoli, B., 1985. Estimating stage recruitment and mortality rates of
Saissetia oleae (Oliv.). Proceedings of the CEC/FAO/IOBC International Joint Meeting on
'Integrated Pest Control in Olive-Groves', Pisa, 3–6 April 1984. pp. 169–174. AA Balkema,
The Netherlands.
Pugliesi A., Bartolini G., Orlandini S., 2007. La variabilità climatica in Toscana: tecniche di
omogeneizzazione dei dati climatici e analisi degli impatti su vite e olivo.
http://www.agrometeorologia.it/documenti/atti_2008/riassunti/06PUGLISI.pdf
Rapagnani M. R., Caffarelli V., Barlattini M., 1988. Lobesia botrana (Den. et Schiff.): studio in
laboratorio del ciclo di sviluppo in funzione della temperatura. Atti XV Congr. Naz. Ital.
Entomol., L'Aquila: 973-980.
Rapi B., Romani M., Bonora L., Dainelli N., Dambra C., Conese C., 2004. Technical Note on
Spatial analysis operation, E.U. Pr. Bacchus D17 - EVG1-CT-2002-00075, pp. 40.
Rapi B., Romani M., Conese C., 2005. VISAVES: un sistema per la Valutazione della
Vocazionalità Territoriale e della Variabilità dei Vigneti”, Manuale informativo, p. 28.
Rattigan, K. and Hill, S.J., 1986. Relationship between temperature and flowering in almond. Aust.
J. Exp. Agric. 26, pp. 399–404.
Remund, J., and J. Page. 2002. Chain of algorithms: short- and longwave radiation with associated
temperature prediction resources. SoDa Deliverable D5-2-2/3. Internal document.
Reuter D.J., Robinson J.B., Peverill K.I. e G.H. Price, 1986. Guidelines for collecting, handling and
analyzing plant materials. In: Reuter D.J. e J.B. Robinson (eds.), Plant analysis an interpretation
manual. Inkata Press, Melbourne, Australia, pp. 20-35.
Richardson, C.W., 1981. Stochastic simulation of daily precipitation, temperature, and solar
radiation. Water Resour. Res., 17:182-190.
Richardson, E.A., Seeley, S.D. and Walker, D.R., 1974. A model for estimating the completion of
rest for Redhaven and Elberta peach trees. HortScience 9, pp. 331–332.
Ritchie J.T. e S. Otter, 1984. Description and performance of CERES Wheat a user-oriented wheat
model. USDA-ARS-SR Grassland Soil and Water research Laboratory Temple.
Romani M., Rapi B., Bonora L., Dambra C., Conese C., 2004. Spatial Analysis Operation for land
and vine management, E.U. Pr. Bacchus D16 - EVG1-CT-2002-00075, pp. 176.
Salsón, S., and R. Garcia-Bartual., 2003. A space-time rainfall generator for highly convective
Mediterranean rainstorms. Nat. Hazards Earth Syst. Sci., 3:103-104. Eyring, 1935.
Scienza A., 1999. Lo studio dell'ecosistema viticolo al servizio di naturalità e origine. L'Informatore
agrario, supplemento al n° 16, pp. 7-9.
Severini M., Alilla R., Pesolillo S., Baumgärtner J., 2005. Fenologia della vite e della lobelia
botrana (Lep. Tortricidae) nella zona dei Castelli Romani. Rivista Italiana di Agrometeorologia
34-39 (3).
Severini M., Gilioli G., 2002. Storia e filosofia dei modelli di simulazione nella difesa delle colture
agrarie. Notiz. Protez. Piante, 15, 9- 29.
Shaltout, A.D. and Unrath, C.R., 1983. Rest completion prediction model for Starkrimson delicious
apples. J. Am. Soc. Hort. Sci. 108, pp. 957–961.
Sharpe P. J. H., DeMichele D. W., 1977. Reaction kinetics of poikilotherm development. J. Theor.
Biol. 64: 649-670.
Shehata W.A., Abou-Elkhair S.S., Stefanos S.S., Youssef A.A., and Nasr F.N., 2003. Biological
studies on the olive leaf moth, Palpita unionalis Hübner (Lepid., Pyralidae) and the olive moth,
Prays oleae Bernard (Lepid., Yponomeutidae). J Pest Sci 76: 155-158.
Sigwalt B., 1977. La nonienclature alaire de Co~nstock-Needham dans l'étude des Braconides :
distinction des genres Pharierofoma et Phanerotomella (Hym. Braconidae, Cheloninae). Annls
Soe. ent. Fr. (N.S.), 13 (3) : 525-534.
Srikanthan, R., and F. Chiew. 2003. Stochastic models for generating annual, monthly and daily
rainfall and climate data at a site. Cooperative Research Centre for Catchment Hydrology,
Report 03/16, Victoria, Australia.
Stöckle C.O., Nelson R.L., Donatelli M., Castellvì F., 2001. ClimGen: a flexible weather generation
program. In Proc. 2nd Int. Symp. Modelling Cropping Systems, 16-18 July, Florence, Italy,
229-230.
Stöckle, C.O., 2002. Atmosphere: derived climate variables and time interpolation. BSysE 562
lecture. Pullman, WA, USA.
Supit L., Hooijer A.A. e C.A. Van Diepen (eds.), 1994. System description of the WOFOST 6.0
crop simulation model implemented in CGMS, vol.1. JRC, European Commission.
Tosi L., 2008. I microsensori guidano le irrigazioni nel vigneto a controllo informatico. Terra e Vita
74, Tecnica e tecnologia, n. 2/2008
Tremblay E., 1990. Entomologia applicata. Vol. I. Liguori, Napoli.
Tsitsipis J. A., 1977. Effect of costant temperatures on the eggs of the olive fruit fly, Dacus oleae
(Diptera, Tephritidae). Ann. Zool. Ecol. Anim. 9: 133-139.
Van Keulen, h. and Sligmen, N.G 1987. in simulation of water use, nitrogen nutrition and growth of
spring crop. Pudoc Wageningen pp 1-310.
Vanclay, J.K. and Skovsgaard, J.P., 1997. Evaluating forest growth models. Ecol.Mod.98,pp.1–12;.
Vercesi A., 1994. Strumenti innovativi per la gestione della difesa contro la peronospora della vite.
Informatore patologico 5/1995.
Villalobos, F.J., F. Orgaz, L. Testi, and E. Fereres., 2000. Measurement and modelling of
evapotranspiration of olive (Olea europaea L.) orchards. Eur. J. Agron. 13:155–163.
Villalobos, F.J., L. Testi, J. Hidalgo, M. Pastor and F. Orgaz, 2005. Modelling potential growth and
yield of olive (Olea europaea L.) canopies. European Journal of Agronomy 24: 296-303.
Conese C., Rapi B., Romani M., Bonora L., Dambra C., 2005. New tools for wineyard
management. In A. Quintanilla e S. Montesinos “Methodological approach for vineyard
inventory and management”, Univ. of Castilla la Mancha. Spain. p. 127-143; 195- 200.
Weinberger, J.H., 1950. Chilling requirements of peach varieties. Proc. Am. Soc. Hort. Sci. 56, pp.
122–128.
Wilks, D.S. and Wilby, R.L., 1999. The weather generation game: a review of stochastic weather
models. Progress in Physical Geography, 23, 329-357.
Williams, J.R., C.A. Jones, J.R. Kiniry, and D.A. Spanel, 1989. The EPIC crop growth model.
Trans. ASAE, 32(2):497-511.
Woolhiser, D.A., and G.G.S. Pegram, 1979. Maximum likelihood estimation of Fourier coefficients
to describe seasonal variations of parameters in stochastic daily precipitation models. J. Appl.
Meteor., 18:34-42.
Young, E. and Werner, D.J., 1985. Chill unit and growing degree hour requirements for vegetative
bud break in six apple rootstocks. J. Am. Soc. Hort. Sci. 110, pp. 411–413.
Zalom, F., Goodell, P.B., Wilson, L.T. , Barnett, W.,. Bentley W. J.,1983. Degree-Days: The
calculation and use of Heat Units in Pest Management. Division of Agriculture and Natural
Resources, University of California.