Transgenic crops: trends and dynamics in the world and in Latin America

Abstract

Transgenic crops have been the recipient of strong support as well as vigorously opposed opinions since their appearance. In any case, their growth throughout the world has been remarkable, and the production and commercialization of transgenics in Latin America has been especially significant. The purpose of the present study was to analyze transgenic crop production trends around the world and the relationship between the area allocated to the cultivation of transgenic crops and the profits generated by this activity. Data concerning Latin American countries and their participation in transgenic crop production are addressed specifically. The present study used covariance analysis, Pearson’s correlation coefficient, time series analysis, Dicker–Fuller test, Durbin–Watson statistic, standardization, and different measures of central tendency. Results for the period between 1996 and 2016 show that, despite the significant increase in the area planted with this type of crops, their production presented a deterministic growth behavior, which is explained using a non-stationary model. Current data are insufficient to establish a causal relationship between cultivated hectares and their derived profits. Finally, the present study showed that production increased considerably from 2004 to 2016 in the cases of Brazil, Argentina, Paraguay, and Uruguay, as well as a positive relationship between the global area planted with transgenics and the corresponding area in these selected countries.

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Fig. 1

Source: Created by the authors based on ISAAA (2016)

Fig. 2

Source: Created by the authors based on ISAAA (2016)

Fig. 3

Source: Prepared by the authors based on ISAAA (2016)

Notes

  1. 1.

    This statistic was calculated as follows: \({\text{Cov}}\left({{\text{X}},{\text{Y}}} \right) = \frac{{\mathop \sum \nolimits_{i = 1}^{i = n} \left({X_{i} - \bar{X}} \right)\left({Y_{i} - \bar{Y}} \right)}}{n}\).

  2. 2.

    Weak stationarity is referred to mainly because the probabilistic distribution associated with the series analyzed in the present study is unknown, as well as any combination of observations and all of its moments, which are time-independent.

  3. 3.

    Augmented Dickey-Fuller test validated the null hypothesis H0 = The series contains a unit root (series is non-stationary) over the alternative hypothesis H1 = The series does not contain a unit root (series is stationary).

  4. 4.

    Standardization was carried out using the expression \({\text{Z}}_{\text{i}} = \frac{{X_{i} - \bar{X}}}{{es\left({X_{i}} \right)}}\), a normal probability distribution function with a set mean of 0 and a variance of 1. This makes it possible to modify the variable \(\left| {{\text{Z}}_{\text{i}}} \right|\), which in turn allows for variables of different measurement units to be compared.

  5. 5.

    Average values.

  6. 6.

    The selection of Latin American countries was based on the availability of data. Information is not available for all countries or records are only available for a distinct set of years.

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Acknowledgements

We would like to acknowledge the support provided by the National Polytechnic Institute (Instituto Politécnico Nacional), Secretariat for Research and Postgraduate Studies (Secretaría de Investigación y Posgrado), Grant Numbers 20180919 and 20180205. We also thank to CONACYT for the postdoctoral grant of Dr. Gerardo Reyes Ruiz.

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Correspondence to Alejandro Barragán-Ocaña.

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Barragán-Ocaña, A., Reyes-Ruiz, G., Olmos-Peña, S. et al. Transgenic crops: trends and dynamics in the world and in Latin America. Transgenic Res 28, 391–399 (2019). https://doi.org/10.1007/s11248-019-00123-8

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Keywords

  • Transgenic
  • Crops
  • Production
  • Commercialization
  • World
  • Latin America