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Start Over Author "Cavani, A." Publisher elsevier b.v.
374 results on '"Cavani, A."'

17. Oxidative condensation/esterification of furfural with ethanol using preformed Au colloidal nanoparticles. Impact of stabilizer and heat treatment protocols on catalytic activity and stability

Author

Monti, Eleonora, Ventimiglia, Alessia, Soto, Carolina Alejandra Garcia, Martelli, Francesca, Rodríguez-Aguado, Elena, Cecilia, Juan Antonio, Maireles-Torres, Pedro, Ospitali, Francesca, Tabanelli, Tommaso, Albonetti, Stefania, Cavani, Fabrizio, and Dimitratos, Nikolaos

Published
2022
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25. Genetic relationships between behavioral traits and feed efficiency traits in lactating Holstein cows.

Author

Nascimento, Bárbara M., Cavani, Ligia, Caputo, Malia J., Marinho, Mariana N., Borchers, Matthew R., Wallace, Richard L., Santos, José E.P., White, Heather M., Peñagaricano, Francisco, and Weigel, Kent A.

Subjects
*EFFECT of environment on animals, *ANIMAL herds, *GENETIC correlations, *DAIRY cattle, *STATISTICAL models
Abstract

The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. The evaluation of dairy cow feed efficiency using residual feed intake accounts for known energy sinks. However, behavioral traits may also contribute to the variation in feed efficiency. Our objective was to estimate the heritability and repeatability of behavioral traits and their genetic correlations with feed efficiency and its components in lactating Holstein cows. The first dataset consisted of 36,075 daily rumination and lying time records collected using a SMARTBOW ear-tag accelerometer (Zoetis, Parsippany, NJ) and 6,371 weekly feed efficiency records of 728 cows from the University of Wisconsin–Madison. The second dataset consisted of 59,155 daily activity records, measured as number of steps, recorded by pedometers (AfiAct; SAE Afikim, Kibbutz Afikim, Israel) and 8,626 weekly feed efficiency records of 635 cows from the University of Florida. Feed efficiency and its components included DMI, change in BW, metabolic BW, secreted milk energy, and residual feed intake. The statistical models included the fixed effect of cohort, lactation number, and days in milk, and the random effects of animal and permanent environment. Heritability estimates for behavioral traits using daily records were 0.19 ± 0.06 for rumination and activity, and 0.37 ± 0.07 for lying time. Repeatability estimates for behavioral traits using daily data ranged from 0.56 ± 0.02 for activity to 0.62 ± 0.01 for lying time. Both heritability and repeatability estimates were larger when weekly records instead of daily records were used. Rumination and activity had positive genetic correlations with residual feed intake (0.40 ± 0.19 and 0.31 ± 0.22, respectively) and lying time had a negative genetic correlation with this residual feed intake (−0.27 ± 0.11). These results indicate that more efficient cows tend to spend more time lying and less time active. Additionally, less efficient cows tend to eat more and therefore also tend to ruminate longer. Overall, sensor-based behavioral traits are heritable and genetically correlated with feed efficiency and its components and, therefore, they could be used as indicators to identify feed-efficient cows within the herd. [ABSTRACT FROM AUTHOR]

Published
2024
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27. Inferring phenotypic causal networks for tick infestation, Babesia bovis infection, and weight gain in Hereford and Braford cattle using structural equation models

Author

Cavani, Ligia, Lopes, Fernando Brito, Giglioti, Rodrigo, Bresolin, Tiago, Campos, Gabriel Soares, Okino, Cintia Hiromi, Gulias-Gomes, Claudia Cristina, Caetano, Alexandre Rodrigues, Oliveira, Márcia Cristina de Sena, Cardoso, Fernando Flores, Rosa, Guilherme Jordão de Magalhães, and de Oliveira, Henrique Nunes

Published
2020
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39. Metabolic control and complications in Italian people with diabetes treated with continuous subcutaneous insulin infusion

Author

Mammì, F., Bruzzese, M., Schettino, M., Nuzzo, M.G., Di Blasi, V., Fresa, R., Lambiase, C., Iafusco, D., Zanfardino, A., Confetto, S., Bozzetto, L., Annuzzi, G., Alderisio, A., Riccardi, G., Gentile, S., Marino, G., Guarino, G., Zucchini, S., Maltoni, G., Suprani, T., Graziani, V., Nizzoli, M., Acquati, S., Cavani, R., Romano, S., Michelini, M., Manicardi, E., Bonadonna, R., Dei Cas, A., Dall'aglio, E., Papi, M., Riboni, S., Manicardi, V., Pugni, V., Lasagni, A., Street, M.E., Pagliani, U., Rossi, C., Assaloni, R., Brunato, B., Tortul, C., Zanette, G., Li Volsi, P., Zanatta, M., Tonutti, L., Agus, S., Pellegrini, M.A., Ceccano, P., Pozzilli, G., Anguissola, Beretta, Buzzetti, R., Moretti C, C., Leto, G., Pozzilli, P., Manfrini, S., Maurizi, A.R., Leotta, S., Altomare, M., Abbruzzese, S., Carletti, S., Suraci, C., Filetti, S., Manca Bitti, M.L., Arcano, S., Cavallo, M.G., De Bernardinis, M., Pitocco, D., Caputo, S., Rizzi, A., Manto, A., Schiaffini, R., Cappa, M., Benevento, D., Frontoni, S., Malandrucco, I., Morano, S., Filardi, T., Lauro, D., Marini, M.A., Castaldo, E., Sabato, D., Tuccinardi, F., Forte, E., Viterbori, P., Arnaldi, C., Minuto, N., d'Annunzio, G., Corsi, A., Rota, R., Scaranna, C., Trevisan, R., Valentini, U., Girelli, A., Bonfadini, S., Zarra, E., Plebani, A., Prandi, E., Felappi, B., Rocca, A., Meneghini, E., Galli, P., Ruggeri, P., Carrai, E., Fugazza, L., Baggi, V., Conti, D., Bosi, E., Laurenzi, A., Caretto, A., Molinari, C., Orsi, E., Grancini, V., Resi, V., Bonfanti, R., Favalli, V., Bonura, C., Rigamonti, A., Bonomo, M., Bertuzzi, F., Pintaudi, B., Disoteo, O., Perseghin, G., Perra, S., Chiovato, L., De Cata, P., Zerbini, F., Lovati, E., Laneri, M., Guerraggio, L., Bossi, A.C., De Mori, V., Galetta, M., Meloncelli, I., Aiello A, A., Di Vincenzo, S., Nuzzi, A., Fraticelli, E., Ansaldi, E., Battezzati, M., Lombardi, M., Balbo, M., Lera, R., Secco, A., De Donno, V., Cadario, F., Savastio, S., Ponzani, C., Aimaretti, G., Rabbone, I., Ignaccolo, G., Tinti, D., Cerutti, F., Bari, F., Giorgino, F., Piccinno, E., Zecchino, O., Cignarelli, M., Lamacchia, O., Picca, G., De Cosmo, S., Rauseo, A., Tomaselli, L., Tumminia, A., Egiziano, C., Scarpitta, A.M., Maggio, F., Cardella, F., Roppolo, R., Provenzano, V., Fleres, M., Scorsone, A., Scatena, A., Gregori, G., Lucchesi, S., Gadducci, F., Di Cianni, S., Pancani, S., Del Prato, S., Aragona, M., Crisci, I., Calianno, A., Fattor, B., Crazzolara, D., Reinstadler, P., Longhi, S., Incelli, G., Rauch, S., Romanelli, T., Orrasch, M., Cauvin, V., Franceschi, R., Lalli, C., Pianta, A., Marangoni, A., Aricò, C.N., Marin, N., Nogara, N., Simioni, N., Filippi, A., Gidoni Guarneri, G.L., Contin M.L, M.L., Decata, A.P., Bondesan, L., Confortin, L., Coracina, A., Lombardi, S., Costa Padova, S., Cipponeri, E., Scotton, R., Galasso, S., Boscari, F., Zanon, M.S., Vinci, C., Lisato, G., Gottardo, L., Bonora, E., Trombetta, M., Negri, C., Brangani, C., Maffeis, C., Sabbion, A., Marigliano, M., Lepore, Giuseppe, Bonfanti, Riccardo, Bozzetto, Lutgarda, Di Blasi, Vincenzo, Girelli, Angela, Grassi, Giorgio, Iafusco, Dario, Laviola, Luigi, Rabbone, Ivana, Schiaffini, Riccardo, and Bruttomesso, Daniela

Published
2018
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46. Consistency of dry matter intake in Holstein cows: Heritability estimates and associations with feed efficiency.

Author

Cavani, Ligia, Parker Gaddis, Kristen L., Baldwin, Ransom L., Santos, José E.P., Koltes, James E., Tempelman, Robert J., VandeHaar, Michael J., White, Heather M., Peñagaricano, Francisco, and Weigel, Kent A.

Subjects
*MILK yield, *COWS, *GENETIC correlations, *HERITABILITY, *QUANTILE regression, *FIXED effects model, *DAIRY cattle, *BODY weight
Abstract

Resilience can be defined as the capacity to maintain performance or bounce back to normal functioning after a perturbation, and studying fluctuations in daily feed intake may be an effective way to identify resilient dairy cows. Our goal was to develop new phenotypes based on daily dry matter intake (DMI) consistency in Holstein cows, estimate genetic parameters and genetic correlations with feed efficiency and milk yield consistency, and evaluate their relationships with production, longevity, health, and reproduction traits. Data consisted of 397,334 daily DMI records of 6,238 lactating Holstein cows collected from 2007 to 2022 at 6 research stations across the United States. Consistency phenotypes were calculated based on the deviations from expected daily DMI for individual cows during their respective feeding trials, which ranged from 27 to 151 d in duration. Expected values were derived from different models, including simple average, quadratic and cubic quantile regression with a 0.5 quantile, and locally estimated scatterplot smoothing (LOESS) regression with span parameters 0.5 and 0.7. We then calculated the log of variance (log-Var-DMI) of daily deviations for each model as the consistency phenotype. Consistency of milk yield was also calculated, as a reference, using the same methods (log-Var-Milk). Genetic parameters were estimated using an animal model, including lactation, days in milk and cohort as fixed effects, and animal as random effect. Relationships between log-Var-DMI and traits currently considered in the US national genetic evaluation were evaluated using Spearman's rank correlations between sires' breeding values. Heritability estimates for log-Var-DMI ranged from 0.11 ± 0.02 to 0.14 ± 0.02 across models. Different methods (simple average, quantile regressions, and LOESS regressions) used to calculate log-Var-DMI yielded very similar results, with genetic correlations ranging from 0.94 to 0.99. Estimated genetic correlations between log-Var-DMI and log-Var-Milk ranged from 0.51 to 0.62. Estimated genetic correlations between log-Var-DMI and feed efficiency ranged from 0.55 to 0.60 with secreted milk energy, from 0.59 to 0.63 with metabolic body weight, and from 0.26 to 0.31 with residual feed intake (RFI). Relationships between log-Var-DMI and the traits in the national genetic evaluation were moderate and positive correlations with milk yield (0.20 to 0.21), moderate and negative correlations with female fertility (−0.07 to −0.20), no significant correlations with health and longevity, and favorable correlations with feed efficiency (−0.23 to −0.25 with feed saved and 0.21 to 0.26 with RFI). We concluded that DMI consistency is heritable and may be an indicator of resilience. Cows with lower variation in the difference between actual and expected daily DMI (more consistency) may be more effective in maintaining performance in the face of challenges or perturbations, whereas cows with greater variation in observed versus expected daily DMI (less consistency) are less feed efficient and may be less resilient. [ABSTRACT FROM AUTHOR]

Published
2024
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