Zobrazeno 1 - 10
of 71
pro vyhledávání: '"AMBREEN HAMADANI"'
Autor:
Ambreen Hamadani, Nazir Ahmad Ganai
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)
Abstract In a rapidly transforming world, farm data is growing exponentially. Realizing the importance of this data, researchers are looking for new solutions to analyse this data and make farming predictions. Artificial Intelligence, with its capaci
Externí odkaz:
https://doaj.org/article/8381754b0bb6423d830863c3912414ae
Publikováno v:
Bulletin of the National Research Centre, Vol 47, Iss 1, Pp 1-8 (2023)
Abstract Background With the advancement in technology the amount of data generated, in almost every sphere of life, is increasing exponentially. This enormous amount of data needs new powerful tools for analysis and inference drawing. One such proce
Externí odkaz:
https://doaj.org/article/512ace5aa1f14dc5a3b13f0be6e48763
Publikováno v:
Indian Journal of Animal Sciences, Vol 93, Iss 10 (2023)
The realignment of the production profile to respond to demanding market signals is one of the most important challenges that an animal breeders face today. Animal fibre being a significant contributor to the agricultural economy needs special attent
Externí odkaz:
https://doaj.org/article/88f0c0ab35a84b9994da41c8db2f85bc
Autor:
Ambreen Hamadani, Nazir A. Ganai
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-13 (2022)
Abstract As the challenges of food insecurity and population explosion become more pressing, there is a dire need to revamp the existing breeding and animal management systems. This can be achieved by the introduction of technology for efficiency and
Externí odkaz:
https://doaj.org/article/5dfe25de08554b769b288292e91ffad8
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-12 (2022)
Abstract As the amount of data on farms grows, it is important to evaluate the potential of artificial intelligence for making farming predictions. Considering all this, this study was undertaken to evaluate various machine learning (ML) algorithms u
Externí odkaz:
https://doaj.org/article/00ada80ac62c4f528e689929c471a35d
Autor:
SAFEER ALAM, MUBASHIR ALI RATHER, NUSRAT NABI, GURJEET KAUR, S SHANAZ, NAZIR AHMAD, TAVSIEF AHMAD, MIR SHABIR AHMAD, AMBREEN HAMADANI
Publikováno v:
Indian Journal of Animal Sciences, Vol 93, Iss 1 (2023)
A study on the socio-economic, phenotypic, and technical features of Purgi goats in Kargil was undertaken. A total of 215 Purgi goat breeders from 8 villages were interviewed and 215 kids born between 2016 and 2018 were studied. The study revealed th
Externí odkaz:
https://doaj.org/article/e14470761fba46daa4a2a21b363adb50
Autor:
AMBREEN HAMADANI, NAZIR A GANAI, MUBASHIR A RATHER, SYED SHANAZ, AADIL AYAZ, SHEIKH MANSOOR, SABA NAZIR
Publikováno v:
Indian Journal of Animal Sciences, Vol 92, Iss 4 (2022)
Externí odkaz:
https://doaj.org/article/560755904b73410eabd41e63b21cfc58
Autor:
RUKSANA SHAH, N A GANAI, S SHANAZ, F D SHEIKH, H M KHAN, NUSRAT N KHAN, AMBREEN HAMADANI, SAFEER ALAM
Publikováno v:
Indian Journal of Animal Sciences, Vol 91, Iss 10 (2021)
Genetic information is necessary to devise strategic plans aimed to improve the genetic merit of dairy cattle. Exploration of quantitative, qualitative, and molecular genetics is important to improve dairy cattle performance. The aim of the study was
Externí odkaz:
https://doaj.org/article/3b541beb706d4396a46105dd0baf53f5
Autor:
NUSRAT N KHAN, AMBREEN HAMADANI, MUBASHIR ALI RATHER, MIR SHABIR AHMAD, SYED SABA BUKHARI, AADIL AYAZ, HENNA JALAL, NAJIMAANA WANI
Publikováno v:
Indian Journal of Animal Sciences, Vol 91, Iss 3 (2021)
Data and pedigree information obtained from 4,186 birth records of Rambouillet Sheep collected from the Government Sheep Breeding and Research Farm, Reasi, Jammu and Kashmir were analyzed. The objective was to evaluate the performance and to estimate
Externí odkaz:
https://doaj.org/article/9c211cc4d84d4f969241931673e0a125
Autor:
TAVSIEF AHMAD, ANKIT MAGOTRA, A K GUPTA, SHAKTI KANT DASH, MIR MOHSIN, MIR SHABIR, AMBREEN HAMADANI, B R YADAV
Publikováno v:
Indian Journal of Animal Sciences, Vol 91, Iss 2 (2021)
The current study was undertaken with the objective of sire evaluation as well as studying the effect of genetic and non-genetic factors on growth performance in males of Tharparkar and Karan Fries Cattle. Data on body weights of Tharparkar and Karan
Externí odkaz:
https://doaj.org/article/70ea81ef509741d3ba3ad671e13a94bb