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Replication Data for "A conditional linear Gaussian network to assess the impact of several agronomic settings on the quality of Tuscan Sangiovese grapes"
Oct 4, 2021 - A conditional linear Gaussian network - Sangiovese grapes
Stefanini, Federico M.; Alessandro Magrini; Stefano Di Blasi, 2021, "Replication Data for "A conditional linear Gaussian network to assess the impact of several agronomic settings on the quality of Tuscan Sangiovese grapes"", https://doi.org/10.13130/RD_UNIMI/BMCJ8L, UNIMI Dataverse, V1, UNF:6:zl6bIXUg5THPPd+pQwFMWw== [fileUNF]
In this paper, a Conditional Linear Gaussian Network (CLGN) model is built for a two- year experiment on Tuscan Sangiovese grapes involving canopy management techniques (number of buds, defoliation and bunch thinning) and harvest time (technological and late harvest). We found th...
A conditional linear Gaussian network - Sangiovese grapes(University of Milan)
Oct 4, 2021Federico M. Stefanini
Federico M. Stefanini(Università degli Studi di Milano)
Oct 4, 2021Dipartimento di scienze e politiche ambientali
Dipartimento di scienze e politiche ambientali(Università degli Studi di Milano)
Oct 4, 2021
Bacterial-assisted Adsorption Technology for Arsenic removal from water
Jul 28, 2021Dipartimento di Scienze per gli Alimenti, la Nutrizione e l'Ambiente
The toxicological effects of arsenic are related to its chemical form and oxidation state: As(III) is about 100 times more toxic and mobile than arsenate As(V). Methyl Arsenic may present comparable toxicity or higher than inorganic species, As(III) or As(V). Hence, it is necessa...
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