Analyzing food production risk with Monte Carlo simulation

Trias Mahmudiono, Ghulam Yasin, Saade Abdalkareem Jasim, Tawfeeq Abdulameer Hashim Alghazali, Mustafa Mohammed Kadhim, Acim Heri Iswanto, Mohammed Sabeeh Majeed, Sandhir Sharma, Zaid Shaker Al-Mawlawi, Nadia Masaya Panduro-Tenazoa

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The agricultural sector in the country has a high and growing status and importance, but the growth and development of this sector are not possible without proper and effective risk management. In the current study, using the Monte Carlo simulation method as one of the powerful tools in risk analysis, the production risk due to the effects of climate change on the dominant agricultural products of Plovdiv, Bulgaria in the period 1990-2017, is predicted and measured. The results showed that Lentils has the highest risk (Product risk index was-0.25%) and bean has the lowest risk (Product risk index was 0.17%). Overall, the research results indicate the significant effect of performance risk in this region. Therefore, farmers should pay special attention to the risk of crop performance in determining their cultivation pattern in addition to other factors and criteria such as price, profitability, self-consumption, etc. Meanwhile, it is suggested that products with higher risk should not be grown alone and should be placed next to the other products with less risk as much as possible to increase food security.

Original languageEnglish
Article numbere03522
JournalFood Science and Technology
Volume42
DOIs
Publication statusPublished - 2022

Keywords

  • Monte Carlo simulation
  • agricultural products
  • food production risk
  • risk management

Fingerprint

Dive into the research topics of 'Analyzing food production risk with Monte Carlo simulation'. Together they form a unique fingerprint.

Cite this