Laboratory of Plant Pathology, Department of Crop Science, School of Plant Sciences, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece.
Department of Sustainable Crop Production (DI.PRO.VE.S.), Universita Cattolica del Sacro Cuore, Via Emilia Parmense 84, 29122 Piacenza, Italy.
Toxins (Basel). 2020 Jul 10;12(7):445. doi: 10.3390/toxins12070445.
In recent years, very many incidences of contamination with aflatoxin B (AFB) in pistachio nuts have been reported as a major global problem for the crop. In Europe, legislation is in force and 12 μg/kg of AFB is the maximum limit set for pistachios to be subjected to physical treatment before human consumption. The goal of the current study was to develop a mechanistic, weather-driven model to predict growth and the AFB contamination of pistachios on a daily basis from nut setting until harvest. The planned steps were to: (i) build a phenology model to predict the pistachio growth stages, (ii) develop a prototype model named AFLA-pistachio (model transfer from AFLA-maize), (iii) collect the meteorological and AFB contamination data from pistachio orchards, (iv) run the model and elaborate a probability function to estimate the likelihood of overcoming the legal limit, and (v) manage a preliminary validation. The internal validation of AFLA-pistachio indicated that 75% of the predictions were correct. In the external validation with an independent three-year dataset, 95.6% of the samples were correctly predicted. According to the results, AFLA-pistachio seems to be a reliable tool to follow the dynamic of AFB contamination risk throughout the pistachio growing season.
近年来,由于开心果中存在黄曲霉毒素 B(AFB)污染的情况非常普遍,这已成为该作物在全球范围内面临的主要问题。在欧洲,现行立法规定,用于人类消费的开心果在进行物理处理前,其 AFB 的最大限量为 12μg/kg。本研究的目的是开发一种基于力学和天气驱动的模型,以便从坐果到收获的每一天,预测开心果的生长和 AFB 污染情况。计划步骤包括:(i)建立预测开心果生长阶段的物候模型;(ii)开发一个名为 AFLA-pistachio 的原型模型(从 AFLA-maize 模型转移);(iii)从开心果果园收集气象和 AFB 污染数据;(iv)运行模型并详细说明概率函数以估计超过法定限量的可能性;(v)进行初步验证。AFLA-pistachio 的内部验证表明,75%的预测是正确的。在使用独立的三年数据集进行的外部验证中,95.6%的样本被正确预测。根据结果,AFLA-pistachio 似乎是一种可靠的工具,可以在整个开心果生长季节跟踪 AFB 污染风险的动态。