Sexual behavior and seminal characteristics of Brahman bulls in the Colombian tropical flooded savanna: effects of reproductive management systems and climatic periods

Jaramillo, Liliana Chacón; Navarro, Oscar; Ladino, Cesar; Martins, Jorge André Matias; Osorio, Jair Pérez; Silva, Ariosto Ardila

doi:10.1007/s11250-022-03087-w

Cited by 4 publications

(5 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The 170 farmers that followed the advice and skipped the planting season saved a significant amount of money on planting when the drought struck. Other use cases include using an AI approach to optimize food delivery networks in areas affected by natural disasters, or integrating data from various alternative sources, including geospatial data, social media data, telecommunications data, internet search data, and vaccine data, to better forecast patterns of virus and disease transmission [20].…”

Section: Resultsmentioning

confidence: 99%

The nexus between Artificial Intelligence and Sustainable Development Goals: A review

Mahadew

2024

Sustain. Econ.

View full text Add to dashboard Cite

This article focuses on the link between Artificial Intelligence and Sustainable Development Goals and, more precisely, how the former can be applied to achieve the latter. The solution to SDG-related issues may be one goal of AI applicability. There have been suggestions that the current status of artificial intelligence (AI) might serve hundreds of millions of people in both rich and developing countries by helping to resolve problems related to all 17 UN Sustainable Development Goals. Examples include helping those who are blind or visually handicapped navigate their environment, detecting victims of sexual exploitation online, supporting relief operations in the event of a disaster, helping to detect diabetes early, and using image scanning to diagnose skin cancer. These are but a few examples of how AI works and how AI innovation can be advantageous. It also reviews how Artificial Intelligence can be applied to protect the environment, food production, the energy industry, and healthcare development.

show abstract

Section: Resultsmentioning

confidence: 99%

The nexus between Artificial Intelligence and Sustainable Development Goals: A review

Mahadew

2024

Sustain. Econ.

View full text Add to dashboard Cite

show abstract

“…According to literary sources [28], [29], [30], [31], [32], the increase in the service period causes an increase in the total amount of milk during lactation. It causes a deterioration in the reproductive capacity of cows.…”

Section: Resultsmentioning

confidence: 99%

The prolonged effect of GLUTAM 1M biologically active preparation on dairy productivity and milk quality of cows

Трохименко

Kovalchuk

Биденко

et al. 2022

Potr. S. J. F. Sci.

View full text Add to dashboard Cite

We have studied the effect of biologically active preparation of metabolic-neurotropic action “Glutam 1M” on milk productivity of cows and quality indicators of raw milk. This preparation was used for dry cows in the last trimester of pregnancy. Studies were performed in the private agricultural enterprise “Savertsi” of Popilnyansky district of Zhytomyr region on cows of Holstein breed. The biologically active preparation “Glutam 1M” has been administered to the cows of the experimental groups under the skin behind the shoulder blade in an amount of 20 ml, starting from 270 and 265 days of gestation, once a day for three consecutive days. Cows of control groups were injected with saline in the same dose. Using the biologically active preparation “Glutam 1M”, a milk yield decreased slightly by 2% (91.9 kg). The milk yield increased by 2.9% (141.5 kg) in the control group. 305-days milk yield in the control group of cows was almost the same as in the previous lactation period. During the experiment, the experimental group of cows – has decreased by 2.9% (136.5 kg). A similar situation has been observed during the biologically active preparation “Glutam 1M” on the 270 – 272th days of pregnancy. Milk yield in the experimental group of animals for the previous lactation and after the use of preparation remained almost at the same level in the control group – decreased by 4.7% (207.1 kg). 305-days milk yield in the control group of cows for the previous and post-lactation experiment period was almost the same. In the experimental group of animals, there was an increase in this indicator by 2.7% (128.7 kg). The use of the “Glutam 1M” preparation did not affect milk quality, namely the mass fraction of fat and protein; fluctuations of the above indicators stayed within the error.

show abstract

“…En la evaluación morfológica se determinaron el porcentaje y el tipo de anormalidades. Según Chacón et al (2022), se acepta un máximo de 30 % de espermatozoides anormales. Las anormalidades se clasifican en tres grupos: primarias (aquellas que afectan la cabeza y el acrosoma del espermatozoide), secundarias (las que afectan la pieza o tracto intermedio) y terciarias (las que causan daño de la cola).…”

Section: Características Seminalesunclassified

Análisis de la correlación entre las características fenotípicas y seminales en toros reproductores Bos indicus

Bulla-Arias,

Montoya-Andrade,

Munevar-Romero

et al. 2023

Cien. Agri.

View full text Add to dashboard Cite

En el contexto ganadero de Casanare, donde el acceso a tecnologías para evaluar la calidad seminal es limitado, anticipar las características seminales de los toros basándose en sus atributos físicos sin recurrir a metodologías específicas y costosas sería beneficioso. Esto podría mejorar la eficiencia reproductiva del hato, aumentando los índices de preñez y la producción anual de crías. En un estudio experimental con 238 toros se midieron diversas características físicas y seminales, y se utilizó el coeficiente de correlación de Spearman para analizar las relaciones entre ellas. Se observó que el 57,1 % de los toros fueron clasificados como muy buenos, mientras que el 7,6 % fueron considerados de baja calidad. La edad promedio de los toros fue de 5,5 años, con una motilidad y vitalidad seminal promedio del 76 % para cada una. La concentración espermática promedio fue de 610 millones. Se encontraron correlaciones negativas fuertes entre la libido, erección, protrusión, eyaculación y el tipo de eyaculación con características seminales como volumen, grumos, motilidad, vitalidad y concentración espermática. Además, la concentración de espermatozoides mostró una correlación moderada positiva con la circunferencia escrotal (CE), lo que indica que un incremento en la CE tiende a aumentar la concentración espermática. Estas correlaciones proporcionan información valiosa para la selección de reproductores y la mejora de programas reproductivos en explotaciones pecuarias en Colombia, especialmente para aquellos productores con limitado acceso a tecnologías reproductivas.

show abstract

Sexual behavior and seminal characteristics of Brahman bulls in the Colombian tropical flooded savanna: effects of reproductive management systems and climatic periods

Cited by 4 publications

References 54 publications

The nexus between Artificial Intelligence and Sustainable Development Goals: A review

The nexus between Artificial Intelligence and Sustainable Development Goals: A review

The prolonged effect of GLUTAM 1M biologically active preparation on dairy productivity and milk quality of cows

Análisis de la correlación entre las características fenotípicas y seminales en toros reproductores Bos indicus

Contact Info

Product

Resources

About