Saffron, obtained from the flower stigmas of Crocus sativus L., is one of the most expensive food spices. The introduction of saffron in alpine areas could help to broaden and diversify the activities of mountain mult...Saffron, obtained from the flower stigmas of Crocus sativus L., is one of the most expensive food spices. The introduction of saffron in alpine areas could help to broaden and diversify the activities of mountain multifunctional farms, with a positive impact on economy and land management. According to ISO 3632(2010/2011), saffron can be classified into three categories of quality(I, II, III) depending on the concentration of the three main metabolites responsible for its characteristic colour, flavor and aroma: Crocin, Picrocrocin and Safranal. This study represents the first investigation of the quality of saffron produced in the Italian Alps evaluated with spectrophotometry, HPLC, solid-phase microextraction(SPME), and gas chromatographic analysis combined with mass spectrometry(GC/MS). The experiments used Crocus sativus stigmas produced in 2012-2013 in different areas of the Central Italian Alps were located at an altitude between 720 and 1200 m a.s.l.. Results obtained were compared to commercial saffron. The analyses confirmed that all samples can be classified in the first quality category according to the ISO classification. This high quality is also confirmed by HPLC analysis. Moreover, the SPME-GC/MS analysis identified some differences in the aromatic profile of saffron samples, in particular regarding safranal concentration. A preliminary assessment of the economic viability of high quality saffron production for local markets was also performed. Our study provides valid information regarding the quality and economic sustainability of saffron production in the alpine area confirming this crop as a good candidate for a new source of income for multifunctional farms in mountain areas.展开更多
To estimate atmospheric predictability for multivariable system, based on information theory in nonlinear error growth dynamics, a quantitative method is introduced in this paper using multivariable joint predictabili...To estimate atmospheric predictability for multivariable system, based on information theory in nonlinear error growth dynamics, a quantitative method is introduced in this paper using multivariable joint predictability limit(MJPL) and corresponding single variable predictability limit(SVPL). The predictability limit, obtained from the evolutions of nonlinear error entropy and climatological state entropy, is not only used to measure the predictability of dynamical system with the constant climatological state entropy, but also appropriate to the case of climatological state entropy changed with time. With the help of daily NCEP-NCAR reanalysis data, by using a method of local dynamical analog, the nonlinear error entropy, climatological state entropy, and predictability limit are obtained, and the SVPLs and MJPL of the winter 500-hPa temperature field, zonal wind field and meridional wind field are also investigated. The results show that atmospheric predictability is well associated with the analytical variable. For single variable predictability, there exists a big difference for the three variables, with the higher predictability found for the temperature field and zonal wind field and the lower predictability for the meridional wind field. As seen from their spatial distributions, the SVPLs of the three variables appear to have a property of zonal distribution, especially for the meridional wind field, which has three zonal belts with low predictability and four zonal belts with high predictability. For multivariable joint predictability, the MJPL of multivariable system with the three variables is not a simple mean or linear combination of its SVPLs. It presents an obvious regional difference characteristic. Different regions have different results. In some regions, the MJPL is among its SVPLs. However, in other regions, the MJPL is less than its all SVPLs.展开更多
基金partly supported by "Accordo di Programma, affermazione in Edolo del Centro di Eccellenza Università della Montagna" MIURUniversità degli Studi di Milano, prot. no. 386 1293-05/08/2011 and by Fondazione della Comunità Bresciana- Onlus
文摘Saffron, obtained from the flower stigmas of Crocus sativus L., is one of the most expensive food spices. The introduction of saffron in alpine areas could help to broaden and diversify the activities of mountain multifunctional farms, with a positive impact on economy and land management. According to ISO 3632(2010/2011), saffron can be classified into three categories of quality(I, II, III) depending on the concentration of the three main metabolites responsible for its characteristic colour, flavor and aroma: Crocin, Picrocrocin and Safranal. This study represents the first investigation of the quality of saffron produced in the Italian Alps evaluated with spectrophotometry, HPLC, solid-phase microextraction(SPME), and gas chromatographic analysis combined with mass spectrometry(GC/MS). The experiments used Crocus sativus stigmas produced in 2012-2013 in different areas of the Central Italian Alps were located at an altitude between 720 and 1200 m a.s.l.. Results obtained were compared to commercial saffron. The analyses confirmed that all samples can be classified in the first quality category according to the ISO classification. This high quality is also confirmed by HPLC analysis. Moreover, the SPME-GC/MS analysis identified some differences in the aromatic profile of saffron samples, in particular regarding safranal concentration. A preliminary assessment of the economic viability of high quality saffron production for local markets was also performed. Our study provides valid information regarding the quality and economic sustainability of saffron production in the alpine area confirming this crop as a good candidate for a new source of income for multifunctional farms in mountain areas.
基金supported by the National Natural Science Foundation of China (Grant No. 41375063)
文摘To estimate atmospheric predictability for multivariable system, based on information theory in nonlinear error growth dynamics, a quantitative method is introduced in this paper using multivariable joint predictability limit(MJPL) and corresponding single variable predictability limit(SVPL). The predictability limit, obtained from the evolutions of nonlinear error entropy and climatological state entropy, is not only used to measure the predictability of dynamical system with the constant climatological state entropy, but also appropriate to the case of climatological state entropy changed with time. With the help of daily NCEP-NCAR reanalysis data, by using a method of local dynamical analog, the nonlinear error entropy, climatological state entropy, and predictability limit are obtained, and the SVPLs and MJPL of the winter 500-hPa temperature field, zonal wind field and meridional wind field are also investigated. The results show that atmospheric predictability is well associated with the analytical variable. For single variable predictability, there exists a big difference for the three variables, with the higher predictability found for the temperature field and zonal wind field and the lower predictability for the meridional wind field. As seen from their spatial distributions, the SVPLs of the three variables appear to have a property of zonal distribution, especially for the meridional wind field, which has three zonal belts with low predictability and four zonal belts with high predictability. For multivariable joint predictability, the MJPL of multivariable system with the three variables is not a simple mean or linear combination of its SVPLs. It presents an obvious regional difference characteristic. Different regions have different results. In some regions, the MJPL is among its SVPLs. However, in other regions, the MJPL is less than its all SVPLs.
