9 феврал 2026
5RAQAMLI STATISTIKA – FERMER XO‘JALIKLARI FAOLIYATINI SAMARALI BOSHQARISH OMILI SIFATIDA
6989c1b3965d3.pdf
MAQOLA ANNOTATSIYASI
MUALIFLAR
A.Ayubjonov
Toshkent Davlat iqtisodiyot universiteti
F.Rateyev
Kadrlar malakasini oshirish va statistik tadqiqotlar instituti
Teglar
Maqolani baholang
0
Maqola idintifikatorlari
DOI:
Mavjud emas
Foydalanilgan adabiyotlar
https://www.coherentmarketinsights.com/industry-reports/digitalagriculture-market
Smith, J. (2020). Optimizing small and medium farms efficiency using statistical monitoring in the USA (p. 112). New York: Springer.
Müller, A. (2021). Digital agriculture and resource optimization in Germany (p. 67). Berlin: Springer Nature.
Silva, C. (2022). Regression analysis for yield prediction in Brazilian farms (p. 89). São Paulo: Elsevier
Li, W. (2023). Artificial intelligence applications for farm management in China (p. 55). Beijing: Tsinghua University Press.
Petrova, O. (2021). Integrating statistical and economic indicators in farming in Russia and Central Asia (p. 101). Moscow: Nauka.
Qo‘chqorov, A. (2022). Improving economic efficiency of farms in Uzbekistan using statistical methods (p. 74). Tashkent: Fan va Texnologiyalar Universiteti
Rasulova, G. (2023). Digital monitoring and cost reduction in Uzbek farms (p. 68). Tashkent: Agroinform
Roberts, J. (2022). Statistical methods for improving agricultural efficiency in the UK (p. 120). London: Routledge.
Gonzales, M. (2021). Digital technologies and resource optimization in Mexican farming (p. 75). Mexico City: Universidad Nacional Autónoma de México
World Bank & O‘zbekiston Respublikasi Milliy Statistika qo‘mitasi. (2025). Agricultural productivity and digital technologies: Global trends and national approaches (p. 45). Washington, DC & Tashkent: World Bank & Statistika qo‘mitasi
https://www.coherentmarketinsights.com/industry-reports/digitalagriculture-market
Smith, J. (2020). Optimizing small and medium farms efficiency using statistical monitoring in the USA (p. 112). New York: Springer.
Müller, A. (2021). Digital agriculture and resource optimization in Germany (p. 67). Berlin: Springer Nature.
Silva, C. (2022). Regression analysis for yield prediction in Brazilian farms (p. 89). São Paulo: Elsevier
Li, W. (2023). Artificial intelligence applications for farm management in China (p. 55). Beijing: Tsinghua University Press.
Petrova, O. (2021). Integrating statistical and economic indicators in farming in Russia and Central Asia (p. 101). Moscow: Nauka.
Qo‘chqorov, A. (2022). Improving economic efficiency of farms in Uzbekistan using statistical methods (p. 74). Tashkent: Fan va Texnologiyalar Universiteti
Rasulova, G. (2023). Digital monitoring and cost reduction in Uzbek farms (p. 68). Tashkent: Agroinform
Roberts, J. (2022). Statistical methods for improving agricultural efficiency in the UK (p. 120). London: Routledge.
Gonzales, M. (2021). Digital technologies and resource optimization in Mexican farming (p. 75). Mexico City: Universidad Nacional Autónoma de México
World Bank & O‘zbekiston Respublikasi Milliy Statistika qo‘mitasi. (2025). Agricultural productivity and digital technologies: Global trends and national approaches (p. 45). Washington, DC & Tashkent: World Bank & Statistika qo‘mitasi