Weed management through herbicide application in direct-seeded rice and yield modeling by artificial neural network

  • Dibakar Ghosh Bidhan Chandra Krishi Viswavidyalaya, Dept. Agronomy. Mohanpur, West Bengal, 74125
  • Udai P. Singh Banaras Hindu University, Institute of Agricultural Sciences, Dept. Agronomy. Varanasi, Uttar Pradesh, 221005
  • Krishnendu Ray Bidhan Chandra Krishi Viswavidyalaya, Dept. Agronomy. Mohanpur, West Bengal, 74125
  • Anupam Das Bihar Agricultural University, Sabour, Dept. of Soil Science and Agricultural Chemistry. Bhagalpur, Bihar, 813210
Keywords: Oryza sativa, direct-seeded rice, weed, herbicide, artificial neural network

Abstract

In direct seeded rice (DSR) cultivation, weed is the major constraint mainly due to absence of puddling in field. The yield loss due to weed interference is huge, may be up to 100%. In this perspective, the present experiment was conducted to study the efficacy of selected herbicides, and to predict the rice yield using artificial neural network (ANN) models. The dry weight and density of weeds were recorded at different growth stages and consequently herbicidal efficacy was evaluated. Experimental results revealed that pre-emergence (PRE) herbicide effectively controlled the germination of grassy weeds. Application bispyribac-sodium as post-emergence (POST) following PRE herbicides (clomazone or pendimethalin) or as tank-mixture with clomazone effectively reduced the density and biomass accumulation of diverse weed flora in DSR. Herbicidal treatments improved the plant height, yield attributes and grain yield (2.7 to 5.5 times) over weedy check. The sensitivity of the best ANN model clearly depicts that the weed control index (WCI) of herbicides was most important than their weed control efficiency (WCE). Besides, the early control of weeds is a better prescription to improve rice yield. Differences in sensitivity values of WCI and WCE across the crop growth stages also suggest that at 15, 30 and 60 days after sowing, herbicides most effectively controlled sedges, broad leaves and grasses, respectively. Based on the grain yield and herbicidal WCE, it can be concluded that the combined application of pendimethalin or clomazone as PRE followed by bispyribac-sodium as POST or tank-mixture of clomazone + bispyribac sodium can effectively control different weed flushes throughout the crop growth period in DSR.

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References

Ahmed S, Chauhan BS, 2014. Performance of different herbicides in dry-seeded rice in Bangladesh. Sci World J Article ID 729418, 14 pp.

Andres A, Concenco G, Theisen G, Vidotto F, Ferrero A, 2013. Selectivity and weed control efficacy of pre- and post-emergence applications of clomazone in Southern Brazil. Crop Prot 53: 103-108. http://dx.doi.org/10.1016/j.cropro.2013.06.012

Antralina M, Istina IN, Yuwariah Y, Simarmata T, 2015. Effect of difference weed control methods to yield of lowland rice in the SOBARI. Proc Food Sci 3: 323-329. http://dx.doi.org/10.1016/j.profoo.2015.01.035

Bouman BAM, Hengsdijk H, Hardy B, Bindraban PS, Tuong TP, Ladha JK, 2002. Water-wise rice production. Proc Int Workshop on Water-Wise Rice Production, 8-11 April, International Rice Research Institute, Los Baños, Philippines.

Chauhan BS, 2013. Effect of tillage systems, seeding rates, and herbicides on weed growth and grain yield in dry-seeded rice systems in the Philippines. Crop Prot 54: 244-250. http://dx.doi.org/10.1016/j.cropro.2013.09.001

Chauhan BS, Johnson DE, 2010. The role of seed ecology in improving weed management strategies in the tropics. Adv Agron 105: 221-262. http://dx.doi.org/10.1016/S0065-2113(10)05006-6

Chauhan BS, Opena J, 2013. Weed management and grain yield of rice sown at low seeding rates in mechanized dry-seeded systems. Field Crops Res 141: 9-15. http://dx.doi.org/10.1016/j.fcr.2012.11.002

Chauhan BS, Migo T, Westerman PR, Johnson DE, 2010. Post-dispersal predation of weed seeds in rice fields. Weed Res 50: 553-560. http://dx.doi.org/10.1111/j.1365-3180.2010.00807.x

Chauhan BS, Singh RG, Mahajan G, 2012. Ecology and management of weeds under conservation agriculture: a review. Crop Prot 38: 57-65. http://dx.doi.org/10.1016/j.cropro.2012.03.010

Chester J, 1993. Neural networks, a tutorial. Prentice Hall, NY.

DeDatta SK, Baltazar A, 1996. Weed control technology as a component of rice production systems. In: Weed management in rice; Auld B, Kim KU (eds). FAO Plant Prod Protect Paper, No. 139: 25-52.

Farooq M, Siddique KHM, Rehman HMU, Aziz T, Lee D, Wahid A, 2011a. Rice direct seeding: experiences, challenges and opportunities. Soil Till Res 111: 87-98. http://dx.doi.org/10.1016/j.still.2010.10.008

Farooq M, Flower KC, Jabran K,Wahid A, Siddique KHM, 2011b. Crop yield and weed management in rainfed conservation agriculture. Soil Till Res 117: 172-183. http://dx.doi.org/10.1016/j.still.2011.10.001

Ferhatoglu Y, Barrett M, 2006. Studies of clomazone mode of action. Pesticide Biochem Physiol 85: 7-14. http://dx.doi.org/10.1016/j.pestbp.2005.10.002

Gitsopoulos TK, Froud-Williams RJ, 2004. Effects of oxadiargyl on direct-seeded rice and Echinochloa crus-galli under aerobic and anaerobic conditions. Weed Res 44: 329-334. http://dx.doi.org/10.1111/j.1365-3180.2004.00407.x

GOI, 2014. Agricultural statistics at a glance 2014. Directorate of Economics & Statistics, Department of Agriculture & Cooperation, Ministry of Agriculture, Government of India. http://eands.dacnet.nic.in/PDF/Agricultural-Statistics-At-Glance2014.pdf [Accessed: 03.04.2015].

Gupta RK, Ladha JK, Singh S, Singh RG, Jat ML, Saharawat Y, Singh VP, Singh SS, Singh G, Sah G, et al., 2006. Production technology for direct-seeded rice. Rice-Wheat Consortium for the Indo-Gangetic Plains, New Delhi, India.Technical Bulletin 8, 16 pp.

ISA, 2009. Agronomic terminology, 5th rev. ed. Ind Soc Agron, Ind Agric Res Inst, New Delhi, 319 pp.

Jabran K, Cheema ZA, Farooq M, Basra SMA, Hussain M, Rehman H, 2008. Tank mixing of allelopathic crop water extracts with pendimethalin helps in the management of weeds in canola (Brassica napus) field. Int J Agric Biol 10: 293-296.

Jabran K, Ehsanullah E, Hussain M, Farooq M, Babar M, Doǧan MN, Lee DJ, 2012. Application of bispyribac-sodium provides effective weed control in direct-planted rice on a sandy loam soil. Weed Biol Manage 12: 136-145. http://dx.doi.org/10.1111/j.1445-6664.2012.00446.x

Jung HI, Kuk YI, 2007. Resistance mechanisms in protoporphyrinogen oxidase (PROTOX) inhibitor-resistant transgenic rice. J Plant Biol 50: 586-594. http://dx.doi.org/10.1007/BF03030713

Kamoshita A, Ikeda H, Yamagishi J, Ouk M, 2010. Ecophysiological study on weed seed banks and weeds in Cambodian paddy fields with contrasting water availability. Weed Biol Manage 10: 261-272. http://dx.doi.org/10.1111/j.1445-6664.2010.00393.x

Khoshnevisan B, Rafiee S, Omid M, Yousefi M, Movahedi M, 2013. Modeling of energy consumption and GHG (greenhouse gas) emissions in wheat production in Esfahan province of Iran using artificial neural networks. Energy 52: 333-338. http://dx.doi.org/10.1016/j.energy.2013.01.028

Labrada R, 1996. Weed control in rice. In: Weed management in rice; Auld B& Kim KU (eds). FAO Plant Prod Protect 139: 3-5.

Mahajan G, Chauhan BS, 2013. The role of cultivars in managing weeds in dry-seeded rice production systems. Crop Prot 49: 52-57. http://dx.doi.org/10.1016/j.cropro.2013.03.008

Mahajan G, Chauhan BS, 2015. Weed control in dry direct-seeded rice using tank mixtures of herbicides in South Asia. Field Crops Res 72: 90-96. http://dx.doi.org/10.1016/j.cropro.2015.03.002

Mahajan G, Chauhan BS, Johnson DE, 2009. Weed management in aerobic rice in northwestern Indo-Gangetic plains. J Crop Improve 23: 366-382. http://dx.doi.org/10.1080/15427520902970458

Nourani V, Fard MS, 2012. Sensitivity analysis of the artificial neural network out-puts in simulation of the evaporation process at different climatologic regimes. Adv Eng Soft 47: 127-146. http://dx.doi.org/10.1016/j.advengsoft.2011.12.014

Pathak H, 2013. Greenhouse gas mitigation in Indian agriculture. Ann Agric Res 34: 99-105.

Pathak H, Tewari AN, Sankhyan S, Dubey DS, Mina U, Singh VK, Jain N, Bhatia A, 2011. Direct-seeded rice: Potential, performance and problems - A review. Curr Adv Agric Sci 3: 77-88.

Phonglosa A, Bhattacharyya K, Ray K, Mandal J, Pari A, Banerjee H, Chattopadhyay A, 2015. Integrated nutrient management for okra in an inceptisol of eastern India and yield modeling through artificial neural network. Sci Hortic-Amsterdam 187: 1-9. http://dx.doi.org/10.1016/j.scienta.2015.02.037

Rao AN, Johnson DE, Sivaprasad B, Ladha JK, Mortimer AM, 2007.Weed management in direct-seeded rice. Adv Agron 93: 153-255. http://dx.doi.org/10.1016/S0065-2113(06)93004-1

Razzaq A, Cheema ZA, Jabran K, Farooq M, Khaliq A, Haider G, 2010. Weed management in wheat through combination of allelopathic water extracts with reduced doses of herbicides. Pakistan J Weed Sci Res16: 247-256.

Saini JP, Angiras NN, 2002. Evaluation of ethoxysulfuron against broad-leaved weeds and sedges in direct seeded puddled rice. Ind J Weed Sci 34: 36-38.

Singh M, Bhullar MS, Chauhan BS, 2014. The critical period for weed control in dry-seeded rice. Crop Prot 66: 80-85. http://dx.doi.org/10.1016/j.cropro.2014.08.009

Singh N, Singh B, Rai AB, Dubey AK, Rai A, 2012. Impact of direct seeded rice (DSR) for resource conservation. Ind Res J Exten Edu 2: 6-9.

Singh S, Singh H, Narwal S, Malik RK, 2003. Evaluation of Alkomba and tank mixture of Almix + Bulachlor for control of weeds in transplanted rice. Ind J Weed Sci35: 24-26.

Singh S, Ladha JK, Gupta RK, Bhushan L, Rao AN, 2008. Weed management in aerobic rice systems under varying establishment methods. Crop Prot 27: 660-671. http://dx.doi.org/10.1016/j.cropro.2007.09.012

Swanton CJ, Weise SF, 1991. Integrated weed management: the rationale and approach. Weed Tech 5: 657-663.

Swanton CJ, Weaver S, Cowan P, Van Acker R, Deen W, Shreshta A, 1999. Weed thresholds. J Crop Prod 2: 9-29. http://dx.doi.org/10.1300/J144v02n01_02

Tomita S, Miyagawa S, Kono Y, Noichana C, Inamura T, Nagata Y, Sributta A, Nawata E, 2003. Rice yield losses by competition with weeds rainfed paddy fields in north-east Thailand. Weed Biol Manage 3: 162-171. http://dx.doi.org/10.1046/j.1445-6664.2003.00101.x

Walia US, 2006. Weed management. Kalyani Publ, New Delhi.

Wang Y, Du L, Rai L, 2013. Photochemical degradation of pyrazosulfuron-ethyl in aqueous solution. J Braz Chem Soc 24: 26-31. http://dx.doi.org/10.1590/S0103-50532013000100005

Zhang Z, 1996. Weed management in transplanted rice. In: Weed Management in Rice; Auld B, Kim KU (eds). FAO Plant Prod Protect Paper No. 139: 75-86.

Published
2016-06-01
How to Cite
Ghosh, D., Singh, U. P., Ray, K., & Das, A. (2016). Weed management through herbicide application in direct-seeded rice and yield modeling by artificial neural network. Spanish Journal of Agricultural Research, 14(2), e1003. https://doi.org/10.5424/sjar/2016142-8773
Section
Plant protection