Processing companies can now use Hydra to verify in real time the presence of pesticides in the tomatoes
The tomato, in all its varieties and colors, is undoubtedly one of the most consumed fruits in the world, thanks to its versatility and its agro-sugar balance.
According to the Food and Agriculture Organization of the United Nations (FAO), tomato production has increased by 35.76% in the last ten years; in 2017, a total of 182.301 million tons of tomatoes were produced worldwide. The production and demand for organic tomatoes is also growing fastly, which, according to the estimates of the study conducted by the University of Newcastle and published in the British Journal of Nutrition in 2014, are healthier and more pesticide-free compared to conventional tomatoes.
Can processing companies monitor in real time the presence of pesticides in a fresh tomato sample? Starting from today, thanks to Hydra, companies can examine a fresh tomato sample, understand if it is a truly organic tomato and decide whether to process it or discard it.
Hydra + Tomato = ❤
The advantage of monitoring the presence of pesticides in a tomato sample taken from the supplier’s truck is priceless. The transformation process of tomato is very fast: you cannot wait a few days to get the results from the laboratory. On the other hand, there are no valid alternative tools on the market that can detect the presence of pesticides in fresh or processed tomatoes in real time, until today.
Caronte Consulting has designed and built Hydra, an innovative UV-VIS spectrometer, able to examine in real time the spectrum in the finished product, in the semi-finished products and in the transformation wastes of the food chain.
In particular, with tomatoes you can:
- monitor the presence of pesticides;
- determining the product characteristics (eg. sugar, lactic acid, lycopene, beta-carotene, etc.) in the raw material, in the semi-finished product and in the finished product;
- examine the stability of the output product.
Figure 1. Hydra for laboratory.
The principle on which Hydra is based is simple: a sample is analyzed determining differences in its spectrum in relation to an “ideal” sample, recognizing to which parameters the identified differences correspond.
Hydra can communicate with the SCADA system that governs production, in order to keep the production drifts under control and achieve optimal processing (Industry 4.0).
Its software has a smart layer that is customized to correct, autonomously, some parameters of the industrial machines, in order to contain small drifts during processing.
To determine the presence of pesticides we will investigate the UV-VIS spectrum in some specific frequencies  and to have maximum sensitivity to spectral variations we will use the new Hydra for Laboratory.
Nowadays pesticides are widely used in agriculture to protect crops and seeds. Unfortunately, their use has also introduced serious damage to the environment and human health . Pesticides are invisible and cannot be analyzed by visible observation or simple tests; the estimation of pesticides in soil and food requires the intervention of an analysis laboratory, complex techniques and a lot of effort .
Hydra does not replace the analysis laboratory, but helps the operator to identify the batches of raw material that deserve an in-depth analysis (in the laboratory) before being processed.
The food industry very often relies on spectroscopy to monitor food quality and safety . For example, Raman scattering spectroscopy has been applied with extreme success in identifying transgenic cultures (eg in tobacco) .
We have studied the spectral characteristics of pesticide contamination by UV-VIS reflectance spectroscopy.
There are several thousand pesticide molecules to be analyzed   but we cannot test them all! We therefore decided to elect Chlorpyrifos as a representative of organophosphate pesticides, comparing the spectral information obtained from pesticide-free tomatoes and those obtained from contaminated tomatoes, looking for particular traces that could be characteristic of organophosphate pesticide contamination.
Chlorpyrifos is used to kill parasites, insects and worms. It is used on crops, animals and buildings. It was introduced in 1965 by the Dow Chemical Company. It acts on the nervous system of insects by inhibiting acetylcholinesterase.
Chlorpyrifos is considered moderately dangerous for humans by the World Health Organization. Exposure exceeding recommended levels has been linked to adverse effects on neurological systems, persistent developmental disorders and autoimmune disorders. Exposure during pregnancy can damage children’s mental development and in 2001 the domestic use of the substance was banned in the United States .
We performed 2types of analysis:
- on the fresh and blended San Marzano tomatoes;
- on tomato sauce.
In both analyzes we added 0.05 ml of Chlorpyrifos to a sample of 76.35 ml, obtaining 76.4 ml of doped product at 0.065%. We have chosen an high doping to be able to identify with absolute certainty the points of the spectrum to be monitored to identify the presence of Chlorpyrifos.
Fresh tomatoes were washed thoroughly before being blended.
Fresh tomato + Chlorpirifos
As shown in Figure 4, a single drop of Chlorpyrifos added to the blended tomato instantly determines a radical change in the color and in the structure of the sample, demonstrating a high reactivity of the pesticide.
Figure 3. Fresh San Marzano tomato.
Figure 4. A drop of Chlorpyrifos in fresh San Marzano tomato.
The analysis performed by Hydra lasts a few seconds and shows 2 very specific spectral areas, in Figure 5 and Figure 6, which explain to the operator the unequivocal presence of pesticide.
Figure 5. CSC curve of fresh tomato doped with pesticide. The peaks correspond to the characteristic frequencies of Chlorpirifos in the tomato.
Figure 6. Comparison of a portion of the spectrum of a fresh tomato and the same one doped with pesticide.
The numerical indexes speak clear: CI and E * clearly show, in Figure 7, a sign inversion in the presence of Chlorpyrifos doping. Starting from these indexes, it is possible to create a customization of the software and generate a traffic light system (green, yellow, red) that helps the operator to assess at a glance the quality of the product or the need to deepen the analysis in a laboratory.
Figure 7. Comparison between numerical indexes CI and E*.
Tomato purée + Chlorpirifos
As can be seen in Figure 8, a single drop of Chlorpyrifos added to the tomato puree determines, in a few seconds, a radical change in the color and in the structure of the sample, demonstrating a high reactivity of the pesticide. The tomato purée was bought in a grocery store.
Figure 8. A drop of Chlorpyrifos in the tomato purée.
The analysis performed with Hydra lasts a few seconds and shows 2 very precise spectral areas, in Figure 9 and Figure 10, which explain to the operator the unequivocal presence of pesticide.
Figure 9. CSC curve of tomato purée doped with pesticide. The peaks correspond to the characteristic frequencies of Chlorpirifos in the tomato purée.
Figure 10. Comparison of a portion of the spectrum of a tomato purée and the same one doped with pesticide.
The numerical indexes talk clear: CI and E* are clearly visible, in Figure 11, a sign inversion in the presence of Chlorpyrifos doping.
Figure 11. Comparison between numerical indexes CI and E*.
Figure 12. The numerical indexes can be summarized in a traffic light code, useful for the operator.
Thanks to Hydra, now we know what frequencies we need to monitor and how the numerical indexes vary: we can identify very small variations that detect the presence of pesticides (Chlorpirifos).
From these indexes, it is possible to create a customization of the software and generate a traffic light system (Figure 12) that helps the operator to assess at a glance the quality of the product or the need to deepen the analysis at a chemical laboratory.
Our experiments and our deductions have drawn particular inspiration from the work of:
Stagno C. “Caratterizzazione dei sottoprodotti della filiera del pomodoro per un potenziale sviluppo industriale“, Università degli Studi di Ferrara, 2010.
 Oumy Diop, Umberto Cerasani, “Light Reflection Spectrum Comparison of Pesticides Free Foods, Organic Foods and Conventional Farming Foods for VIS NIR Filter Creation”, CENTRIC 2016, pp 42-49
 Wen Li, Ming Sun, Minzan Li, “A survey of determination for organophosphorus pesticide residue in agricultural products”, Advance Journal of Food Science and Technology 5(4): 381-386, 2013
 Yankun Peng, Yongyu Li and Jingjing Chen (2012). Optical Technologies for Determination of Pesticide Residue, Infrared Spectroscopy – Materials Science, Engineering and Technology, Prof. Theophanides Theophile (Ed.), ISBN: 978-953-51-0537-4, InTech
 D. Pimentel, “Environmental and economic costs of the application of pesticides primarily in the United States”, Environment, development and sustainability, vol. 7, pp. 229-252, 2005.
 D. Yang and Y. Ying, “Applications of Raman spectroscopy in agricultural products and food analysis: a review”, Applied Spectroscopy Reviews, vol. 46, pp. 539-560, 2011.
 L. R. Goldman, “Managing pesticide chronic health risks: US policies”, Journal of agromedicine, vol. 12, pp. 67-75, 2007.
 C. f. D. C. a. Prevention. (2013). CDC – Pesticide Illness & Injury Surveillance – NIOSH Workplace Safety and Health Topic.
 Mughal BB, Fini JB, Demeneix BA, “Thyroid-disrupting chemicals and brain development: an update”, Endocr Connect 2018 Apr; 7(4):R160-R186. doi: 10.1530/EC-18-0029.