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 | Acceso al texto completo restringido a Biblioteca INIA Treinta y Tres. Por información adicional contacte bibliott@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha : |
19/05/2016 |
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Actualizado : |
11/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
SINCLAIR, K.D.; MOLLE, G.; REVILLA, R.; ROCHE, J.F.; QUINTANS, G.; MORONGIU, L.; SANZ, A.; MACKEY, D.R.; DISKIN, M.G. |
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Afiliación : |
Stottish Agricultural College, Aberdeen.; Instituto Zootecnico e Caseaario per la Sardegna, Olmedo, Sardinia, Italy; Servicio de Investigación Agraria, Unidad de Producicón Animal, Zaragoza, Spain; Faculty Veterinary Medicine, Univerity college Dublin, Ireland.; GRACIELA QUINTANS ILARIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. Scottish Agricultural College, Aberdeen; Instituto Zootecnico e Caseario per la Sardegna, Olmedo, Sardinia, Italy; Servicio de Investigación Agraria, Unidad de Producción Animal, Zaragoza, Spain; Faculty Veterinary Medicine, University College Dublin, Ireland. Teagasc, Athenry, Co. Galway, Ireland.; Teagasc, Athenry, Co. Galway, Ireland. |
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Título : |
Ovulation of the first dominant follicle arising after day 21 post partum in suckling beef cows. |
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Fecha de publicación : |
2002 |
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Fuente / Imprenta : |
Animal Science, 2002, v. 75, p. 115-126. |
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DOI : |
10.1017/S1357729800052899 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 8 December 2001 // Accepted 11 February 2002 // Published online 18 August 2016.
DOI: https://doi.org/10.1017/S1357729800052899 |
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Contenido : |
The effects of body condition score (BCS) of 2·0 or 3·0 units at calving (low v. moderate), post-partum energy intake at 0·6 or 1·0 MJ metabolizable energy (ME) per day per kg M0·75 (low v. high) and unrestricted or restricted (once daily) suckling on the ability of cows to ovulate were studied in a 2 ? 2 ? 2 factorial design with each treatment replicated eight times. Calf isolation and restricted suckling were imposed shortly after selection of the first dominant follicle (DF) to emerge after day 21 post partum. The episodic release of LH (sampled at 15-min intervals for 10 h) was determined 48 h before and 48 h after the day calf isolation and restricted suckling commenced. Additional blood samples were collected weekly for plasma insulin determination. The mean interval from calving to first ovulation was shorter for cows in moderate than low BCS at calving (47·8 v. 57·1 days, s.e.d. = 4·50, P < 0·05), and for cows suckling once daily than for those with unrestricted suckling (42·9 v. 62·0 days, s.e.d. = 4·50, P < 0·001). Post-partum nutrition did not affect this interval. Mean LH pulse frequency prior to the start of restricted suckling was higher for cows of moderate than low BCS at calving (3·2 v. 1·6 pulses per 10 h, s.e.d. = 0·60, P < 0·05). Subsequently, LH pulse frequency was higher for cows suckling once daily than for those with unrestricted suckling (4·0 v. 2·2 pulses per 10 h, s.e.d. = 0·82, P < 0·05). More cows in moderate than low BCS ovulated the first DF to emerge after day 21 post partum (within 4 to 6 days) in response to restricted suckling (69 v. 25%, P < 0·05). LH pulse frequency prior to restricted suckling increased (P < 0·05) with plasma insulin concentration (categorized as low, < 5; moderate, 5 to 8; and high, >8 mIU per l). There were indications of interactions between suckling treatment and BCS (P < 0·08), and suckling treatment and plasma insulin concentration (P < 0·06), on LH pulse frequency, which suggested that calf restriction could alleviate the suppressive effects of under nutrition on episodic LH release. Amongst cows suckling once daily, the non-ovulating animals had fewer LH pulses prior to restricted suckling and smaller, slower growing DF, indicating an inability of the DF to respond to increased LH pulse frequency following calf restriction. Cows of moderate BCS, particularly those with moderate to high levels of plasma insulin (³ 5 mIU per l), responded favourably to restricted suckling. In contrast, excessively thin cows with low plasma insulin concentrations (<5 mIU per l), that had most to gain from restricted suckling, responded poorly. MenosThe effects of body condition score (BCS) of 2·0 or 3·0 units at calving (low v. moderate), post-partum energy intake at 0·6 or 1·0 MJ metabolizable energy (ME) per day per kg M0·75 (low v. high) and unrestricted or restricted (once daily) suckling on the ability of cows to ovulate were studied in a 2 ? 2 ? 2 factorial design with each treatment replicated eight times. Calf isolation and restricted suckling were imposed shortly after selection of the first dominant follicle (DF) to emerge after day 21 post partum. The episodic release of LH (sampled at 15-min intervals for 10 h) was determined 48 h before and 48 h after the day calf isolation and restricted suckling commenced. Additional blood samples were collected weekly for plasma insulin determination. The mean interval from calving to first ovulation was shorter for cows in moderate than low BCS at calving (47·8 v. 57·1 days, s.e.d. = 4·50, P < 0·05), and for cows suckling once daily than for those with unrestricted suckling (42·9 v. 62·0 days, s.e.d. = 4·50, P < 0·001). Post-partum nutrition did not affect this interval. Mean LH pulse frequency prior to the start of restricted suckling was higher for cows of moderate than low BCS at calving (3·2 v. 1·6 pulses per 10 h, s.e.d. = 0·60, P < 0·05). Subsequently, LH pulse frequency was higher for cows suckling once daily than for those with unrestricted suckling (4·0 v. 2·2 pulses per 10 h, s.e.d. = 0·82, P < 0·05). More cows in moderate than low BCS ovulated the first DF t... Presentar Todo |
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Palabras claves : |
BEEF COWS; HORMONA LUTEINIZANTE; INSULIN; LH; NUTRICION; OVULATION; SUCKLING. |
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Thesagro : |
AMAMANTAMIENTO; BOVINOS DE CARNE; NUTRICION ANIMAL; OVULACION. |
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Asunto categoría : |
-- |
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Marc : |
LEADER 03789naa a2200373 a 4500
001 1054830
005 2019-10-11
008 2002 bl uuuu u00u1 u #d
024 7 $a10.1017/S1357729800052899$2DOI
100 1 $aSINCLAIR, K.D.
245 $aOvulation of the first dominant follicle arising after day 21 post partum in suckling beef cows.$h[electronic resource]
260 $c2002
500 $aArticle history: Received 8 December 2001 // Accepted 11 February 2002 // Published online 18 August 2016. DOI: https://doi.org/10.1017/S1357729800052899
520 $aThe effects of body condition score (BCS) of 2·0 or 3·0 units at calving (low v. moderate), post-partum energy intake at 0·6 or 1·0 MJ metabolizable energy (ME) per day per kg M0·75 (low v. high) and unrestricted or restricted (once daily) suckling on the ability of cows to ovulate were studied in a 2 ? 2 ? 2 factorial design with each treatment replicated eight times. Calf isolation and restricted suckling were imposed shortly after selection of the first dominant follicle (DF) to emerge after day 21 post partum. The episodic release of LH (sampled at 15-min intervals for 10 h) was determined 48 h before and 48 h after the day calf isolation and restricted suckling commenced. Additional blood samples were collected weekly for plasma insulin determination. The mean interval from calving to first ovulation was shorter for cows in moderate than low BCS at calving (47·8 v. 57·1 days, s.e.d. = 4·50, P < 0·05), and for cows suckling once daily than for those with unrestricted suckling (42·9 v. 62·0 days, s.e.d. = 4·50, P < 0·001). Post-partum nutrition did not affect this interval. Mean LH pulse frequency prior to the start of restricted suckling was higher for cows of moderate than low BCS at calving (3·2 v. 1·6 pulses per 10 h, s.e.d. = 0·60, P < 0·05). Subsequently, LH pulse frequency was higher for cows suckling once daily than for those with unrestricted suckling (4·0 v. 2·2 pulses per 10 h, s.e.d. = 0·82, P < 0·05). More cows in moderate than low BCS ovulated the first DF to emerge after day 21 post partum (within 4 to 6 days) in response to restricted suckling (69 v. 25%, P < 0·05). LH pulse frequency prior to restricted suckling increased (P < 0·05) with plasma insulin concentration (categorized as low, < 5; moderate, 5 to 8; and high, >8 mIU per l). There were indications of interactions between suckling treatment and BCS (P < 0·08), and suckling treatment and plasma insulin concentration (P < 0·06), on LH pulse frequency, which suggested that calf restriction could alleviate the suppressive effects of under nutrition on episodic LH release. Amongst cows suckling once daily, the non-ovulating animals had fewer LH pulses prior to restricted suckling and smaller, slower growing DF, indicating an inability of the DF to respond to increased LH pulse frequency following calf restriction. Cows of moderate BCS, particularly those with moderate to high levels of plasma insulin (³ 5 mIU per l), responded favourably to restricted suckling. In contrast, excessively thin cows with low plasma insulin concentrations (<5 mIU per l), that had most to gain from restricted suckling, responded poorly.
650 $aAMAMANTAMIENTO
650 $aBOVINOS DE CARNE
650 $aNUTRICION ANIMAL
650 $aOVULACION
653 $aBEEF COWS
653 $aHORMONA LUTEINIZANTE
653 $aINSULIN
653 $aLH
653 $aNUTRICION
653 $aOVULATION
653 $aSUCKLING
700 1 $aMOLLE, G.
700 1 $aREVILLA, R.
700 1 $aROCHE, J.F.
700 1 $aQUINTANS, G.
700 1 $aMORONGIU, L.
700 1 $aSANZ, A.
700 1 $aMACKEY, D.R.
700 1 $aDISKIN, M.G.
773 $tAnimal Science, 2002$gv. 75, p. 115-126.
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INIA Treinta y Tres (TT) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
23/02/2024 |
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Actualizado : |
23/02/2024 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
PARUELO, J.; TEXEIRA, M.; TOMASEL, F. |
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Afiliación : |
JOSÉ PARUELO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; IFEVA, Universidad de Buenos Aires, CONICET, Facultad de Agronomía, Buenos Aires, Argentina; IECA, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay; MARCOS TEXEIRA, IFEVA, Universidad de Buenos Aires, CONICET, Facultad de Agronomía, Buenos Aires, Argentina; FERNANDO TOMASEL, Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO, United States. |
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Título : |
Hybrid modeling for grassland productivity prediction: A parametric and machine learning technique for grazing management with applicability to digital twin decision systems. |
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Fecha de publicación : |
2024 |
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Fuente / Imprenta : |
Agricultural Systems. 2024. Volume 214, article 103847. https://doi.org/10.1016/j.agsy.2023.103847 |
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ISSN : |
0308-521X |
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DOI : |
10.1016/j.agsy.2023.103847 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 1 August 2023; Received in revised form 5 December 2023; Accepted 18 December 2023; Available online 28 December 2023. -- Correspondence: Paruelo, J.M.; Instituto Nacional de Investigación Agropecuaria, INIA, La Estanzuela, Ruta 50 km 11, Colonia, Uruguay; email:jparuelo@inia.org.uy -- Funding: This work was supported by grants from ANII (Uruguay. FSDA_1_2018_1_154773 and IA_2021_1_04 and IA_2021_1_1010784), CSIC-Universidad de la República - Uruguay (Programa I + D Grupos 2018-433), Universidad de Buenos Aires (Argentina) and CONICET (2021-2024. PIP-2021. 11220200100956CO01). -- Supplementary data: https://doi.org/10.1016/j.agsy.2023.103847 -- |
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Contenido : |
ABSTRACT.- CONTEXT: Monitoring Aboveground Net Primary Production (ANPP) is critical to assess not only the current ecosystem status but also its long-term dynamics. In rangelands, the seasonal dynamics of ANPP determines forage availability, stock density, and livestock productivity. OBJECTIVE: To develop a hybrid model to be used as a prediction engine for ANPP in the native grasslands of Uruguay. The model combines a parametric component based on the seasonal dynamics of ANPP, and an artificial neural network (ANN) component used to model the remaining non-linearities, which are mainly related to precipitation and temperature variability. The output of hybrid model is proposed as the "virtual entity" of a digital twin support decision system where the "physical entity" is characterized by a collection of bi-weekly (fortnight) ANPP estimates. METHODS: Fortnight ANPP data were calculated from MODIS EVI for the 2001-2020 period. A sigmoidal functional response, having three parameters with an explicit biological interpretation, was fitted to the accumulated ANPP as a function of time. Forecasts were generated by extrapolating the sigmoidal functional response fit up to four fortnights ahead. From these fits, we obtained the fortnight ANPP values by differentiating the accumulated fortnight ANPP. Predictions (up to four fortnights) were generated for each fortnight and year. The residuals from these fits were modeled using a multilayer perceptron trained by backpropagation using climate variables as independent variables. RESULTS AND CONCLUSIONS: The sigmoidal functional response model fit was highly significant for the accumulated ANPP profile. This model also had a high explanatory power for the accumulated ANPP curve. The median of the percentage absolute residuals for forecasts made 1 to 4 fortnights ahead ranged from 17% to 18%. The ANN significantly reduced this unexplained variability in ANPP, showing a median reduction in residuals of 35%, 31%, 30%, and 30% for 1 to 4 fortnights ahead forecasts, respectively, when compared to predictions from the sigmoidal functional response fit. SIGNIFICANCE: By integrating both parametric and machine learning techniques, the hybrid model developed can make accurate predictions in a way that is both efficient and dependable. The hybrid model not only represents an advantage in terms of predictive power, but it also allows for a deeper understanding of the basic ecological processes involved in forage production. © 2023 MenosABSTRACT.- CONTEXT: Monitoring Aboveground Net Primary Production (ANPP) is critical to assess not only the current ecosystem status but also its long-term dynamics. In rangelands, the seasonal dynamics of ANPP determines forage availability, stock density, and livestock productivity. OBJECTIVE: To develop a hybrid model to be used as a prediction engine for ANPP in the native grasslands of Uruguay. The model combines a parametric component based on the seasonal dynamics of ANPP, and an artificial neural network (ANN) component used to model the remaining non-linearities, which are mainly related to precipitation and temperature variability. The output of hybrid model is proposed as the "virtual entity" of a digital twin support decision system where the "physical entity" is characterized by a collection of bi-weekly (fortnight) ANPP estimates. METHODS: Fortnight ANPP data were calculated from MODIS EVI for the 2001-2020 period. A sigmoidal functional response, having three parameters with an explicit biological interpretation, was fitted to the accumulated ANPP as a function of time. Forecasts were generated by extrapolating the sigmoidal functional response fit up to four fortnights ahead. From these fits, we obtained the fortnight ANPP values by differentiating the accumulated fortnight ANPP. Predictions (up to four fortnights) were generated for each fortnight and year. The residuals from these fits were modeled using a multilayer perceptron trained by backpropagation us... Presentar Todo |
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Palabras claves : |
Agroecological transitions; ANPP; Artificial neural networks; Grasslands; Remote sensing; Uruguay. |
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Asunto categoría : |
-- |
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Marc : |
LEADER 04040naa a2200253 a 4500
001 1064472
005 2024-02-23
008 2024 bl uuuu u00u1 u #d
022 $a0308-521X
024 7 $a10.1016/j.agsy.2023.103847$2DOI
100 1 $aPARUELO, J.
245 $aHybrid modeling for grassland productivity prediction$bA parametric and machine learning technique for grazing management with applicability to digital twin decision systems.$h[electronic resource]
260 $c2024
500 $aArticle history: Received 1 August 2023; Received in revised form 5 December 2023; Accepted 18 December 2023; Available online 28 December 2023. -- Correspondence: Paruelo, J.M.; Instituto Nacional de Investigación Agropecuaria, INIA, La Estanzuela, Ruta 50 km 11, Colonia, Uruguay; email:jparuelo@inia.org.uy -- Funding: This work was supported by grants from ANII (Uruguay. FSDA_1_2018_1_154773 and IA_2021_1_04 and IA_2021_1_1010784), CSIC-Universidad de la República - Uruguay (Programa I + D Grupos 2018-433), Universidad de Buenos Aires (Argentina) and CONICET (2021-2024. PIP-2021. 11220200100956CO01). -- Supplementary data: https://doi.org/10.1016/j.agsy.2023.103847 --
520 $aABSTRACT.- CONTEXT: Monitoring Aboveground Net Primary Production (ANPP) is critical to assess not only the current ecosystem status but also its long-term dynamics. In rangelands, the seasonal dynamics of ANPP determines forage availability, stock density, and livestock productivity. OBJECTIVE: To develop a hybrid model to be used as a prediction engine for ANPP in the native grasslands of Uruguay. The model combines a parametric component based on the seasonal dynamics of ANPP, and an artificial neural network (ANN) component used to model the remaining non-linearities, which are mainly related to precipitation and temperature variability. The output of hybrid model is proposed as the "virtual entity" of a digital twin support decision system where the "physical entity" is characterized by a collection of bi-weekly (fortnight) ANPP estimates. METHODS: Fortnight ANPP data were calculated from MODIS EVI for the 2001-2020 period. A sigmoidal functional response, having three parameters with an explicit biological interpretation, was fitted to the accumulated ANPP as a function of time. Forecasts were generated by extrapolating the sigmoidal functional response fit up to four fortnights ahead. From these fits, we obtained the fortnight ANPP values by differentiating the accumulated fortnight ANPP. Predictions (up to four fortnights) were generated for each fortnight and year. The residuals from these fits were modeled using a multilayer perceptron trained by backpropagation using climate variables as independent variables. RESULTS AND CONCLUSIONS: The sigmoidal functional response model fit was highly significant for the accumulated ANPP profile. This model also had a high explanatory power for the accumulated ANPP curve. The median of the percentage absolute residuals for forecasts made 1 to 4 fortnights ahead ranged from 17% to 18%. The ANN significantly reduced this unexplained variability in ANPP, showing a median reduction in residuals of 35%, 31%, 30%, and 30% for 1 to 4 fortnights ahead forecasts, respectively, when compared to predictions from the sigmoidal functional response fit. SIGNIFICANCE: By integrating both parametric and machine learning techniques, the hybrid model developed can make accurate predictions in a way that is both efficient and dependable. The hybrid model not only represents an advantage in terms of predictive power, but it also allows for a deeper understanding of the basic ecological processes involved in forage production. © 2023
653 $aAgroecological transitions
653 $aANPP
653 $aArtificial neural networks
653 $aGrasslands
653 $aRemote sensing
653 $aUruguay
700 1 $aTEXEIRA, M.
700 1 $aTOMASEL, F.
773 $tAgricultural Systems. 2024. Volume 214, article 103847. https://doi.org/10.1016/j.agsy.2023.103847
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