Phenotyping of corn plants with effect of mesotrione herbicide

Authors

  • Christian Ramírez-Rojas Programa de Posgrado en Botánica-Colegio de Postgraduados. Carretera México-Texcoco km 36.5, Montecillo, Texcoco, Estado de México, México. CP. 56230
  • Cecilia Beatriz Peña-Valdivia Programa de Posgrado en Botánica-Colegio de Postgraduados. Carretera México-Texcoco km 36.5, Montecillo, Texcoco, Estado de México, México. CP. 56230
  • Antonio García-Esteva Programa de Posgrado en Botánica-Colegio de Postgraduados. Carretera México-Texcoco km 36.5, Montecillo, Texcoco, Estado de México, México. CP. 56230
  • Daniel Padilla-Chacón Programa de Posgrado en Botánica-CONACYT-Colegio de Postgraduados. Carretera México-Texcoco km 36.5, Montecillo, Texcoco, Estado de México. CP. 56230

DOI:

https://doi.org/10.29312/remexca.v13i8.2886

Keywords:

fluorescence, mesotrione, pigmentation, RGB

Abstract

Mesotrione is an herbicide that is used for the control of a wide spectrum of weeds during pre- and post-emergence in the crop of corn (Z. mays L). The objective of the present study was to evaluate the effects of mesotrione on growth, pigmentation, with images in the visible spectrum (red, green, and blue, RGB) and fluorescence (Fv/Fm) in the corn cultivars Cacahuacintle, HS-2 and Vitamaíz. The plants were grown in greenhouses, in the College of Postgraduates, Montecillo Campus during 2020, they were analyzed in the vegetative stage V3-V4 with a design of randomized complete blocks and with factorial arrangement. The treatments evaluated were controls (water and adjuvant without mesotrione) and mesotrione 1X and 2X. Ten days after application, images of the plants were obtained, which were analyzed with the LemnaGrid program. None of the mesotrione doses altered the growth of the cultivars, although there were effects on the color of the plants. The loss of green color (chlorosis) occurred in more than 50% of the base of the leaf blade and with spots at the apex. The images of chlorophyll fluorescence and the Fv/Fm index in leaf fragments indicated that the highest dose of mesotrione (2X) in the cultivars Cacahuacintle and Vitamaíz maintained values similar to the controls; in contrast, in HS-2 those values decreased. The results of the present study demonstrated the usefulness of non-invasive phenotyping with RGB images, and of the chlorophyll fluorescence to evaluate the effect of herbicides on crops.

Downloads

Download data is not yet available.

References

Acosta, G. L. M.; Liu, S.; Langley, E. X.; Campbell, Z.; Castro, G. N. and Mendoza, C. D. 2016. Moderate to severe water limitation differentially affects the phenome and ionome of Arabidopsis. Funct. Plant Biol. 44(1):94-106.

Aktar, M. W.; Sengupta, D. and Chowdhury, A. 2009. Impact of pesticides use in agriculture: their benefits and hazards. Interdiscip Toxicol. 2(1):1-12.

Bibi, S.; Khan, S.; Taimur, N.; Daud, M. K. and Azizullah, A. 2019. Responses of morphological, physiological, and biochemical characteristics of maize (Zea mays L.) seedlings to atrazine stress. Environ. Monit. Assess. 191:717.

Cayetano, M. M.; Peña, Valdivia, C. B.; García, E. A.; Jiménez, G. J.C.; Galván, E. I. G. and Padilla, C. D. 2021. Humidity restriction, high night temperature and their combination, during post flowering on common bean (Phaseolus vulgaris L.) canopy and pod senescence. Legume Res. Doi: 10.18805/LR-592.

Chivasa, W.; Mutanga, O. and Biradar, C. 2020. UAV-Based multispectral phenotyping for disease resistance to accelerate crop improvement under changing climate conditions. Remote sensing. 12(15):2445.

Creech, J. E.; Monaco, T. A. and Evans, J. O. 2004. Photosynthetic and growth responses of Zea mays L. and four weed species following post-emergence treatments with mesotrione and atrazinet. Pest Manag Sci. 60(11):1079-1084.

Ding, H. D.; Zhang, X. H.; Xu, S. C.; Sun, L. L.; Jiang, M. Y.; Zhang, A. Y. and Jin Y. G. 2009. Induction of protection against paraquat induced oxidative damage by abscisic acid in maize leaves is mediated through mitogen activated protein kinase. J. Integr. Plant Biol. 51(10):961-972.

Durmuş, N. and Kadioğlu, A. 2005. Reduction of paraquat toxicity in maize leaves by benzyladenine. Acta Biol Hung. 56(1-2):97-107.

EcheverrÌa, S. S.; Mena, F.; Pinnock, M.; Ruepert, C.; Solano, K.; Cruz, E.; Campos, J.; Sánchez, A. B.; Lacorte, S. and Barata, C. 2012. Environmental hazards of pesticides from pineapple crop production in the Río Jiménez watershed (Caribbean Coast, Costa Rica). Sci. Total Environ. 440:106-114.

FAO. 1993. Organización de las Naciones Unidad para la Alimentación y la Agricultura. El maíz en la nutrición humana. Colección FAO: Alimentación y nutrición Nº 25. Roma Italia. http://www.fao.org/3/t0395s/T0395S02.htm#Tipos%20de%20maiz.

Feng, X.; Yu, C.; Chen, Y.; Peng, J.; Ye, L.; Shen, T. 2018. Non-destructive determination of shikimic acid concentration in transgenic maize exhibiting glyphosate tolerance using chlorophyll fluorescence and hyperspectral imaging. Front. Plant Sci. 9(468):1-16.

Gehan, M. A.; Fahlgren, N.; Abbasi, A.; Berry, J. C.; Callen, S. T.; Chavez, L.; Doust, A. N.; Feldman, M. J.; Gilbert, K. B.; Hodge. J. G.; Hoyer, J. S.; Lin, S.; Liu, S.; Lizárraga, C.; Lorence, A.; Miller, M.; Platon, E.; Tessman, M. and Sax, T. 2017. PlantCV v2: Image analysis software for high-throughput plant phenotyping. Peer J. Dec 1;5:e4088

Goltsev, V.; Zaharieva, I.; Chernev, P. and Strasser, R. J. 2009. Delayed fluorescence in photosynthesis. Photosyn. Res. 101(2-3):217-232.

Halpering, O.; Gebremedhin, A.; Wallach, R. and Moshelion, M. 2017. High-throughput physiological phenotyping and screening system for the characterization of plant environment interactions. The Plant J. 89(4):839-850.

Haselimashhadi, H.; Mason, J. C.; Mallon, A. M.; Smedley, D.; Meehan, T. F. and Parkinson, H. 2020. OpenStats: A robust and scalable software package for reproducible analysis of high-throughput phenotypic data. PLoS One, 15(12):0242933.

Herrero, H. E.; Rodríguez, C. M. S.; Pose, J. E.; Sánchez, G. S.; Andrades, M. S. and Sánchez, M. M. J. 2017. Seasonal distribution of herbicide and insecticide residues in the water resources of the vineyard region of la rioja (Spain). Sci. Total Environ. 609:161-171.

Jansen, M.; Gilmer, F.; Biskup, B.; Nagel, K. A.; Rascher, U.; Fischbach, A.; Briem, S.; Dreissen, G.; Tittmann, S.; Braun, S.; Jaeger, I.; Metzlaff, M.; Schurr, U.; Scharr, H. and Walter. A. 2009. Simultaneous phenotyping of leaf growth and chlorophyll fluorescence via growscreen fluoro allows detection of stress tolerance in Arabidopsis thaliana and other rosette plants. Funct. Plant Biol. 36(11):902-914.

Kuklas, C.; Chen, D. and Pape, J. M. 2014. Integrated analysis platform: an open-source information system for high-throughput plant phenotyping. Plant Physiol. 165(2):506-518.

Lopez, B.; Ollivier, P.; Togola, A.; Baran, N. and Ghestem, J. P. 2015. Screening of french groundwater for regulated and emerging contaminants. Sci. Total Environ. 15(518-519):562-573.

Minervini, M.; Giuffrida, M. V.; Perata, P. and Tsaftaris, S. A. 2017. Phenotiki: an open software and hardware platform for affordable and easy image-based phenotyping of rosette-shaped plants. Plant J. 90(1):204-216.

Mitchell, G.; Bartlett, D. W.; Fraser, T. E. M.; Hawkes, T. R.; Holt, D. C.; Townson, J. K. and Wichert, R. A. 2001. Mesotrione: a new selective herbicide for use in maize. Pest Manag. Sci. 57(2):120-128.

Neilson, E. H.; Edwards, A. M.; Blomstedt, C. K.; Berger, B.; Møller, B. L. and Gleadow, R. M. 2015. Utilization of a high throughput shoot imaging system to examine the dynamic phenotypic responses of a C4 cereal crop plant to nitrogen and water deficiency over time. J. Exp. Bot. 66(7):1817-1832.

Oliveira, M.C.; Gaines, T. A.; Jhala, A. J. and Knezevic, S. Z. 2018. Inheritance of mesotrione resistance in an Amaranthus tuberculatus (var Rudis) population from nebraska, USA. Front. Plant Sci. 9(60):1-12.

Padilla, C. D.; Peña, V. C. B.; García, E. A.; Cayetano, M. M. I. and Kohashi, S. J. 2019. Phenotypic variation and biomass partitioning during post-flowering in two common bean cultivars (Phaseolus vulgaris L.) under water restriction. South Afr. J. Bot. 121:98-104.

Prashar, A. and Jones, H. G. 2016. Assessing drought responses using thermal infrared imaging. In: Duque, P. (Ed.) environmental responses in plants: methods and protocols. Springer New York, New York, NY. 209-219 pp.

Rousseau, C.; Belin, E.; Bove, E.; Rousseau, D.; Fabre, F.; Berruyer, R.; Manceau, C.; Jacques, M. A. and Boureau; T. 2013. High throughput quantitative phenotyping of plant resistance using chlorophyll fluorescence image analysis. Plant Methods. 9:17.

Steiner, A. A. 1984. The universal nutrient solution. In: proceedings of the 6th international congress on soilless culture. International society for soilless culture. Wageningen, The Netherlands. 633-649 pp.

Thomas, H. and Ougham, H. 2014. The stay-green trait. J. Exp. Bot. 65(14):3889-3900.

Ulguim, A. D. R.; Perboni, L. T.; Westendorff, N. D. R.; Nohatto, M. A.; Silva, B. M. and Agostinetto, D. 2013. Redução do espaçamento entrelinhas do milho e sua influência na dose do herbicida. Rev. Brazilian Herbicide J. 12(3):232-241.

Wang, X.; Zhang, R.; Song, W.; Han, L.; Liu, X.; Sun, X.; Luo, M.; Chen, K.; Zhang, Y.; Yang, H.; Yang, G.; Zhao, Y. and Zhao, J. 2019. Dynamic plant height QTL revealed in maize through remote sensing phenotyping using a high throughput unmanned aerial vehicle (UAV). Scientific Reports. 9:3458.

Wu, Q.; Sun, H.; Li, M. Z.; Song, Y. Y. and Zhang, Y. E. 2015. Research on maize multispectral image accurate segmentation and chlorophyll index estimation. Guang pu xue yu guang pu fen xi Guang pu. 35(1):178-183.

Zheng, S.; Chen, B.; Qiu, X.; Chen, M.; Ma, Z. and Yu, X. 2016. Distribution and risk assessment of 82 pesticides in Jiulong River and estuary in South China. Chemosphere. 144:1177-1192.

Published

2022-12-13

How to Cite

Ramírez-Rojas, Christian, Cecilia Beatriz Peña-Valdivia, Antonio García-Esteva, and Daniel Padilla-Chacón. 2022. “Phenotyping of Corn Plants With Effect of Mesotrione Herbicide”. Revista Mexicana De Ciencias Agrícolas 13 (8). México, ME:1399-1410. https://doi.org/10.29312/remexca.v13i8.2886.

Issue

Section

Articles

Most read articles by the same author(s)