This work presents a functional clustering procedure applied to meteorological time series. Our proposal combines time series interpolation with smoothing penalized B-spline and the partitioning around medoids clustering algorithm. Our final goal is to obtain homogeneous climate zones of Italy. We compare this approach to standard methods based on a combination of principal component analysis and Cluster Analysis (CA) and we discuss it in relation to other functional clustering approaches based on Fourier analysis and CA. We show that a functional approach is simpler than the standard methods from a methodological and interpretability point of view. Indeed, it becomes natural to find a clear connection between mathematical results and physical variability mechanisms. We discuss how the choice of the basis expansion (splines, Fourier) affects the analysis and propose some comments on their use. The basis for classification is formed by monthly values of temperature and precipitation recorded during the period 1971-2000 over 95 and 94 Italian monitoring stations, respectively. An assessment based on climatic patterns is presented to prove the consistency of the clustering and a comparison of results obtained with different methods is used to judge the functional data approach. © 2012 Springer-Verlag Wien

Diaporthe helianthi is the causal agent of a severe sunflower disease but, in Italy, disease outbreaks are sporadic with no significant losses. The present work investigates the role of meteorological conditions on the potential development of D. helianthi epidemics in Italy, using the French model Asphodel, which simulates the effect of air temperature, relative humidity and rainfall on ascospore maturation and dispersal, infection establishment, disease onset and severity during the period of host susceptibility. Meteorological data measured in eight stations distributed from north to south Italy, over a 5‐year period (1995–99), was used as model input. Results showed that meteorological conditions in Italy are frequently favourable for D. helianthi infections on sunflower, and severe epidemics are possible. Therefore, climatic conditions are not a limiting factor for disease development in the Italian sunflower‐growing areas. The lack of disease epidemics in Italy may be related to differences in the pathogen populations compared with the French ones.

Climate and animal agriculture are interrelated processes and related foods may be threatened through changes in temperature, rainfall and extreme weather events. The present study was aimed to investigate the climate trend over the production area of Grana Padano (GP) cheese. The area is in North of Italy, covers a total land of 46,000 km 2 and it is highly suited for agricultural and livestock productions. Past (1971-2000), recent (2001-2010) and future (2020-2050) climate scenarios were considered and compared. The analysis showed positive anomalies both for minimum and maximum temperatures and a decrease of precipitation for recent and future climate. The Gaussen-Bagnouls classification pointed out a change from humid to semi-humid climate during summer months. These data suggest a warming trend and increasing risk of summer aridity over the production area of GP cheese. The analysis of temperature-humidity index (THI), from past throughout the future scenario, highlighted an increased risk of heat stress for dairy cows. The worst THI condition was predicted for July of the future scenario when milk loss may reach a level of 7 kg/cow/day. The changes in climate may threat the potential to produce GP cheese, indirectly by the negative effect of precipitation deficit on crops yield for cows feeding, directly by the increase of heat stress-related milk loss. These findings may be of help to animate the debate on climate change-related impacts on regional food systems and support policymakers in developing adaptation strategies for the production system of GP cheese. HIGHLIGHTS Climate is changing in the north Italy. Warming and aridity trend may threat the production of Grana Padano cheese. Adaptation measures are required.

The mechanical harvesting of hemp is a key step toward a profitable use of the product. Various fractions (fiber, seeds, residual biomass) may be recovered, and their correct management is fundamental for complying with the requirements of processors/end users. In the light of the renewed interest for its industrial use (panels and insulators), this work proposes the use of modified commercial machines to implement a field separation of the fibrous fraction of stand-retted hemp, a practice that would be profitable if realized with the systems adopted for textile use. The present work was conducted to test the efficiency of harvesting partially macerated plants by using a modified self-propelled forage harvester (SPFH). In Northern Italy, a hemp crop was stand-retted for four months. Then, an SPFH—with rotor knives reduced in number from 24 to 12—was used. Stand-retting made it possible to separate cortical fibers from the inner stem cylinder during harvesting; 53.3% of the material (fibers and shives) was separated automatically by the SPFH together with the chopped bast fiber, while the remaining 46.7% was separated on exiting the launch tube. More than 50% of the fibers were shorter than 5 cm in length, while almost 15% were longer than 10 cm. The SPFH had an effective operating speed of 3.48 km h−1, and no clogging occurred during the test. Therefore, the combination of stand-retting with harvesting using a modified SPFH could be helpful in obtaining an early separation of fibers from shives, thus facilitating the product treatment during its subsequent processing, e.g., by enhancing the defibration.

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