SAMPLE SIZE CALCULATOR FOR PHYTOSANITARY SAMPLING PLANS BASED ON CONSUMER RISK

The international flow of agricultural products is a key factor in the spread of potentially harmful species. Pests and non-native organisms that spread between countries in commercial transport can establish themselves and significantly alter biodiversity, the functioning of agroecosystem services, human health, and the economy. Between 1970 and 2017, the economic cost of biological invasions and control methods represented an estimated global investment of USD 1.288 trillion; in Mexico alone, the cost on the agricultural sector represented an estimated investment of USD 1.01 billion. Because of the volume and diversity of imported products, as well as the economic and environmental damage caused by pest species, sanitary inspection must explicitly incorporate the concepts of producer risk (rejecting a lot with an acceptable sanitary level) and consumer risk (accepting a lot with a minimum sanitary level) to decide whether to accept or reject a lot. This paper introduces the main features of risk-based sampling, defines the acceptable and minimum sanitation levels, discusses how changes in parameters affect the behavior of the characteristic operating curve, and presents the user interface of an interactive web calculator that was programmed in R to automate the development of sampling plans and calculate the risk-based sample size. The estimates obtained compared to other sources indicate that the computation performed with the calculator is accurate and determines sample sizes and acceptance numbers. The inspection should explore sampling methods that explicitly include risk and coin its own concepts that fit its information needs and objectives.

Authors

Publication Details

Journal
Agrociencia
Published
2025-04-04
DOI
https://doi.org/10.47163/agrociencia.v59i3.3239
Primary Topic
Optimal Experimental Design Methods
Type
article
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article

SAMPLE SIZE CALCULATOR FOR PHYTOSANITARY SAMPLING PLANS BASED ON CONSUMER RISK

Juan A. Villanueva-Jiménez, Gustavo Ramírez Valverde, Luis Gabriel Otero-Prevost, Pedro Macías-Canales et al.
Agrociencia
Optimal Experimental Design Methods
article

SAMPLE SIZE CALCULATOR FOR PHYTOSANITARY SAMPLING PLANS BASED ON CONSUMER RISK

Juan A. Villanueva-Jiménez, Gustavo Ramírez Valverde, Luis Gabriel Otero-Prevost, Pedro Macías-Canales, Jorge Luis Leyva-Vázquez
article en

Abstract

The international flow of agricultural products is a key factor in the spread of potentially harmful species. Pests and non-native organisms that spread between countries in commercial transport can establish themselves and significantly alter biodiversity, the functioning of agroecosystem services, human health, and the economy. Between 1970 and 2017, the economic cost of biological invasions and control methods represented an estimated global investment of USD 1.288 trillion; in Mexico alone, the cost on the agricultural sector represented an estimated investment of USD 1.01 billion. Because of the volume and diversity of imported products, as well as the economic and environmental damage caused by pest species, sanitary inspection must explicitly incorporate the concepts of producer risk (rejecting a lot with an acceptable sanitary level) and consumer risk (accepting a lot with a minimum sanitary level) to decide whether to accept or reject a lot. This paper introduces the main features of risk-based sampling, defines the acceptable and minimum sanitation levels, discusses how changes in parameters affect the behavior of the characteristic operating curve, and presents the user interface of an interactive web calculator that was programmed in R to automate the development of sampling plans and calculate the risk-based sample size. The estimates obtained compared to other sources indicate that the computation performed with the calculator is accurate and determines sample sizes and acceptance numbers. The inspection should explore sampling methods that explicitly include risk and coin its own concepts that fit its information needs and objectives.

Agrociencia
Openalex Percentile: Top 93%
Optimal Experimental Design Methods
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