Loading...

Precision nutrient management on the growth and productivity of Rabi maize (Zea mays L.) under light textured brown forest soils of Odisha


Citation :- Precision nutrient management on the growth and productivity of Rabi maize (Zea mays L.) under light textured brown forest soils of Odisha. Res. Crop. 24: 487-495
MASINA SAIRAM, SAGAR MAITRA, LALICHETTI SAGAR, TADIBOINA GOPALA KRISHNA AND UPASANA SAHOO sagar.maitra@cutm.ac.in
Address : Department of Agronomy, M. S. Swaminathan School of Agriculture, Centurion University of Technology and Management, Paralakhemundi-761 211, Odisha, India
Submitted Date : 17-06-2023
Accepted Date : 17-07-2023

Abstract

Maize's high production potential, flexibility, and demand have led to a steady expansion of the land dedicated to growing the crop. Since maize is highly nutrient demanding crop, farmers are applying huge amount of nutrients which can lead to soil degradation and may cause environmental pollution. As an alternative for these circumstances, the present study was conducted on precision nutrient management in maize by using smart nutrient tools such as chlorophyll content meter (CCM) and leaf colour chart (LCC) and decision support systems, namely, nutrient expert (NE) for optimizing the nutrient requirement in maize. The current study was carried out for two consecutive years during Rabi season of 2021-22 and 2022-23 at P. G. Research Farm of M.S. Swaminathan School of Agriculture, Odisha. The experiment was laid out in Randomized Complete Block Design (RCBD) with 14 treatments and replicated thrice and tested on the high yielding hybrid ‘Pioneer P3396’ with recommended dose of fertilizer (RDF) of 120:60:60 kg NPK/ha. The results clearly showed that precision nutrient management had a significant influence on growth, yield attributes and yield of maize. During both the seasons, the maximum plant height (244.3 and 256.7 cm), dry matter accumulation/plan (317.9 g and 323.4 g, stem girth (8.2 mm and 8.1 mm), number of cobs/plant (1.8 and 1.9), weight of the cob (238 g and 243 g), length of the cob (23.8 cm and 24.0 cm), grain yield (7850 kg/ha and 7950 kg/ha) and stover yield (12850 kg/ha and 12667 kg/ha) was found in the treatment consisting of ample dose of nitrogen and the other treatments such as 150% RDF and  Sufficiency Index (SI) at 90-95% also performed better and remained at par with ample dose of nitrogen application during both the years. The experiment concluded that the application of primary nutrients, mainly, nitrogen in ample dose or in splits by considering CCM-based SI can be useful for optimization of nutrient requirement in Rabi maize for the light textured brown forest soils of Odisha.

Keywords

Fertilizer leaf colour chart maize nutrient expert sufficiency index yield

References

Agriculture Statistics at a Glance (2022). Directorate of Economics and Statistics, Ministry of Agriculture and Farmers Welfare, Government of India.
Assefa, K. and Mekonnen, Z. (2019). Effect of level and time of nitrogen fertilizer applicationon growth, yield and yield components of maize (Zea mays L.) at Arab Minch, Southern Ethiopia. Afr. J. Agric. Res14:1785-94.
Banerjee, M., Bhuiya, G. S., Malik, G. C., Maiti, D. and Dutta, S. (2014). Precision nutrient management through use of LCC and nutrient expert in hybrid maize under laterite soil of India. Uni. J. Food Nutri. Sci. 2: 33-36.
Bhuiya, G. S., Shankar, T., Banerjee, M. and Malik, G. C. (2020). Growth, productivity, nutrient uptake and economics of hybrid maize (Zea mays L.) as influenced by precision nutrient management. Int. J. Agric. Environ. Biotechnol. 13: 213-18.
FAOSTAT (2021). Food and Agriculture Organization of the United Nations, Data: Crops and Livestock Products, available online: https://www.fao.org/faostat/en/#data/QCL (accessed 25th December 2023)
Ghosh, D., Brahmachari, K., Brestic, M., Ondrisik, P., Hossain, A., Skalicky, M., Sarkar, S., Moulick, D., Dinda, N. K., Das, A., Pramanick, B., Maitra, S. and Bell R.W. (2020). Integrated weed and nutrient management improve yield, nutrient uptake and economics of maize in the rice-maize cropping system of Eastern India, Agronomy 10: doi.org/10.3390/agronomy10121906.
Gomez, K. A. and Gomez, A. A. (1984). Statistical procedures for agricultural research. John Wiley and Sons.
GoO (2020). 5-decades of Odisha agriculture statistics. Directorate of Agriculture and Food Production, Government of Odisha, India. pp. 46.
Jat, R. D., Jat, H. S., Nawaz, R. K., Yadav, A. K., Bana, A., Choudhary, K. M. and Jat, M. L. (2018). Conservation agriculture and precision nutrient management practices in maize-wheat system: Effects on crop and water productivity and economic profitability. Field Crops Res. 222: 111-20.
Jyothsna, K., Padmaja, J., Sreelatha, D., Kumar, R. M. and Madhavi, A. (2021). Study on nutrient management of hybrid maize (Zea mays L) through decision support tools. J.  Pharmacogn. Phytochem. 10:760-764.
Kumar, D., Patel, R. A., Ramani, V. P. (2019). Assessment of precision nitrogen management strategies in terms of growth, yield and monetary efficiency of maize grown in Western India. J. Plant Nutri. 42: 2844-60.
Kumar, S., Basavanneppa, M. A., Koppalkar, B. G., Umesh. M. R. and Kumar, A. G. (2018). Precision nitrogen management in maize (Zea mays L.) through leaf colour chart tool in Tunga Bhadra command area. Bull. Environ. Pharmacol. Life Sci. 7: 43-46.
Mahajan, G. R., R. N. Pandey, D. Kumar, S. C. Datta, R. N. Sahoo, and R. Parsad. (2014). Development of critical values for the leaf color chart, SPAD and field scout CM 1000 for fixed time adjustable nitrogen management in aromatic hybrid rice (Oryza sativa L.). Commun. Soil Sci. Plant Anal. 45:1877-93.
Maitra, S., Hossain, A., Brestic, M., Skalicky, M., Ondrisik, P., Gitari, H., Brahmachari, K., Shankar, T., Bhadra, P., Palai, J. B., Jana, J., Bhattacharya, U., Duvvada, S. K., Lalichetti, S. and Sairam, M. (2021). A low input agricultural strategy for food and environmental security. Agronomy. 11: doi.org/10.3390/agronomy11020343.
Mathukia, R. K., P. Rathod, and N. M. Dadhania. (2014). Climate change adaptation: Real-time nitrogen management in maize (Zea mays L.) using a leaf colour chart. Curr. World Environ. 9: 1028-33.
Mohapatro, S., Shankar, T., Maitra, S., Pal, A., Nanda, S. P., Ram, M. S. and Panda, S. K. (2021). Growth and productivity of maize (Zea mays L.) as influenced by nitrogen management options. Int. J. Agric. Environ. Biotechnol. 14: 207-14.
Pooniya, V., Jat, S. L., Choudhary, A. K., Singh, A. K., Parihar, C. M., Bana, R. S. and Rana, K. S. (2015). Nutrient Expert assisted site-specific-nutrient-management: An alternative precision fertilization technology for maize-wheat cropping system in South-Asian Indo Gangetic Plains. Ind. J. Agric. Sci. 85: 996-1002.
Pramanick, B., Kumar, M., Naik, B. M., Kumar, M., Singh, S. K., Maitra, S. and Minkina, T. (2022). Long-Term Conservation Tillage and Precision Nutrient Management in Maize–Wheat Cropping System: Effect on Soil Properties, Crop Production, and Economics. Agronomy 12: doi.org/10.3390/agronomy12112766.
Ram, M. S., Shankar, T., Maitra, S., Adhikary, R. and Swamy, G. V. V. S. N. (2020). Productivity, nutrient uptake and nutrient use efficiency of summer rice (Oryza sativa) as influenced by integrated nutrient management practices. Crop Res. 55: 65-72.
Sagar, L., Singh, S., Sharma, A., Maitra, S., Attri, M., Sahoo, R. K., Ghasil, B. P., Shankar, T., Gaikwad, D. J., Sairam, M., Sahoo, U., Hossain, A. and Roy, S. (2023). Role of soil microbes against abiotic stresses induced oxidative stresses in plants. In microbial symbionts and plant health: Trends and applications for changing climate. Springer Nature Singapore, pp.149-77.
Sairam, M., Maitra, S., Praharaj, S., Nath, S., Shankar, T., Sahoo, U. and Aftab, T. (2023). An insight into the consequences of emerging contaminants in soil and water and plant responses. In:  Emerging contaminants and plants: Interactions, adaptations and remediation technologies, Aftab, T. (Ed.), Cham, Springer International Publishing. pp. 1–27.
Sampathkumar, T. and Pandian, B. J. (2010). Efficiency of applied nutrients and SPAD values in hybrid maize under drip fertigation. Madras Agric. J. 97: 237-41.
Scharf, A., P. C. (2010). Precision nitrogen fertilizer management of maize and cotton using crop sensors. 19th World congress of soil science, soil solutions for a changing world 1-6 August 2010, Brisbane, Australia. Pp. 29-32.
Shankar, T., Malik, G. C., Banerjee, M., Dutta, S., Maitra, S., Praharaj, S. and Hossain, A. (2021). Productivity and nutrient balance of an intensive rice–rice cropping system are influenced by different nutrient management in the red and lateritic belt of West Bengal, India. Plants (Basel) 10: doi: 10.3390/plants10081622.
Sharma, L. K. and Bali, S. K. (2018). A review of methods to improve nitrogen use efficiency in agriculture.  Sustainability 10: doi.org/10.3390/su10010051.
Shivashankar, K., Potdar, M. P., Biradar, D. P. and Balol, K. M. G. (2023). Effect of sensor based precision nitrogen management through SPAD and green seeker on dry matter accumulation and growth indices of maize. Pharma Innov. 12: 3555-59.
Singh, B. and Ali, A. M. (2020). Using hand-held chlorophyll meters and canopy reflectance sensors for fertilizer nitrogen management in cereals in small farms in developing countries. Sensors 20: doi.org/10.3390/s20041127.
Singh, J., and Singh, V. (2022). Chlorophyll meter-based precision nitrogen management in spring maize. J. Plant. Nutri. 46: 17-27.
Swamy, G. V. V. S. N., Shankar, T., Maitra, S., Adhikary, R., Praharaj, S. and Sairam, M. (2022). Influence of nitrogen management on productivity, nutrient uptake and efficiency of summer maize (Zea mays). Res. Crop. 23: 313-20.
Wang, Y., Li, C., Li, Y., Zhu, L., Liu, S., Yan, L. and Gao, Q. (2020). Agronomic and environmental benefits of nutrient expert on maize and rice in Northeast China. Environ. Sci. Pollut. Res. 27: 28053-65.
Xiong, D., Chen, J., Yu, T., Gao, W., Ling, X., Li, Y., Peng, S., Huang, J. (2015). SPAD-based leaf nitrogen estimation is impacted by environmental factors and crop leaf characteristics. Sci. Rep. 5: doi: 10.1038/srep13389.

Global Footprints