Leaf color chart: An innovative approach to manage nitrogen application and pest incidence in kharif rice

Introduction

Rice being one of the most important staple crops, provides food to a major portion of the world's population. So, judicious management of nitrogen fertilizers is very crucial to meet the increasing demand for rice and ensure sustainable production, (Midya et al., 2021) [15] . Nitrogen significantly influences the growth, development, and yield of rice (Jahan et al., 2022) [11] . On the other hand, injudicious nitrogen application can cause to yield losses, environmental pollution through nitrogen runoff or leaching, and increased production costs of rice (Dinnes et al., 2002) [6] . In traditional method, application of nitrogen fertilizer in rice has been based on agronomic practices, such as farmers' experience, soil testing, and crop growth stage based fertilizer application (Banayo et al., 2018) [4] . But sometimes, there are some lacunas in precision and it fails to account for proper nitrogen requirements in crop throughout the growing season (Kivi et al., 2022, Dinnes et al., 2002) [12,6] . Consequently, there is an emerging need to apply a reliable and efficient tool to optimize nitrogen fertilizer management in rice. Keeping this problem in mind, this novel approach was introduced in rice to reduce the cost of cultivation, improve soil health and curb the pest incidence in rice.

Importance of Leaf Color Chart (LCC)

Appropriate management of nitrogen fertilizer application is very essential to optimize rice production by reducing environmental impacts. The Leaf Color Chart (LCC) is an promising important device to manage nitrogen fertilizer in rice (Ali et al., 2015) [2] . This method depends on visual evaluation of rice leaf color as a marker which indicates the status of nitrogen in plant (Tao et al., 2020) [23] . LCC based nitrogen management approach can elevate nitrogen use efficiency, enhance yield, and lower nitrogen losses (Rao and Das, 2023) [19] . Appropriate time and dose of nitrogen fertilizer application can be determined by farmers and scientist by comparing the leaf color with this standardized color chart (Golicz et al., 2021) [8] . This is a simple, cost-effective, non-destructive sampling method, and real-time monitoring indicator of nitrogen status in crop (Oláh et al., 2022) [16] .

The LCC is a multipurpose approach which can be used apart from the source of nitrogen applied, including inorganic, organic, or bio-fertilizers. It facilitates the evaluation of canopy lushness as well as the green color of individual leaves (Gill et al., 2023) [7] . By measuring the leaf color with this chart, critical color grades or LCC values can be found to direct the appropriate dose of nitrogen application.

Materials and methods

Site description

The field experiment was conducted at Faridpur village, Ratua-I, Malda district of West Bengal through frontline demonstration with 50 farmers during kharif (July to October) season of 2021. The soil of the experimental site was clay loam in texture with good water holding capacity, drainage facility with moderate fertility status. The experimental area is situated under subtropical humid climate. The soil was fertile with pH 6.98, low in organic carbon 0.43% and EC 0.42 dS m -1 and high level of available nitrogen (480.32 kg/ha), phosphorus (98.07 kg/ha) and potash (213.6 kg/ha).

Description of LCC

The Leaf Color Chart is made of a 12-15-inch-long chart with a number of shades of green (Lindsay and Lindsay, 2017) [13] . The chart consists of sturdy, sunlight-defiant plastic and attributes various colored lines organized like leaf veins. The light colored shade is demarked as 1, while the darkest green one is demarked as 8. Primarily, the LCC had 8 shades of unnamed green color, but latest versions found by the International Rice Research Institute (IRRI, 2005) [10] attributed 7 or 6 shades of green color. This chart is regulated with a chlorophyll meter and helps as a indicator for top dressing of nitrogen fertilizer in rice. There is also a construction sheet written in local language, enlightening the optimal time for nitrogen fertilizer application to the farmers.

Description of Technology under demonstrated plot and farmers'practice

The frontline demonstration was carried out during July to October in kharif rice var. MTU-1010 with seed treatment with NPK (30:30:40 kg/ha and 30 kg N/ha at 3 split doses) along with carbendazim 50% WP @ 2 gm/kg of seed, soil treatment with well rotten cow dung manure @ 375 kg/ha and Trichoderma viride @ of 1.5 ton/ha and Pseudomonas fluorescens @ of 1.5 ton/ha, weed management with glyphosate @ 2.5 kg/ha, micronutrient treatments with boron 20% @ 450 g/ha and zinc @ 900 g/ha, insect management with one spray of novaluron 5.25% + emamectin benzoate 0.9% SC @ 900 ml/ha and disease management with one spray of captan 70% + hexaconazole 5% @ 900 gm/ha. The farmers' plot was treated with NPK (60:40:40 kg/ha as basal and 30 kg N/ha at 2 split doses) and boron and zinc as basal along with 7-8 sprays of insecticides and fungicides. Other intercultural operations like weeding and irrigation were done as and when required.

Collection of data

Leaf Color Chart is made of 6 colored shades varying from light yellowish green to dark green strips formulated with veins akin to rice leaves. 30 kg N/ha was applied as basal within 7 days after transplanting (DAT) and LCC readings were taken at 7 days intervals initiating from 15 DAT until commencement of flowering stage. 30 kg N/ha was applied as top dressing when color of 6 leaves out of 10 leaves of rice fell below a threshold of shade 4 on the LCC. For sampling, 10 insect free hills and most fully expanded leaf from each hill top were randomly selected from the selected area in each plot. Readings on LCC were taken by placing the middle portion of the leaf on the chart and leaf color was observed by keeping blockage of the sun by body as sunlight influences leaf color reading. At 30, 45, 60, and 75 days after transplanting of rice, a plant with any hint of insect infestation was randomly selected from five 1 m 2 areas of demonstrated plots and recorded as infected. All data regarding yield components and yield were documented at 115 DAS.

Per cent yield increase over control = × 100

The percentage of damage (disease incidence) was determined by the following formula:

To determine the extension gap (EG) and technology gap (TG), the following formulae were used (Samui et al., 2000) [20]: EG = Yield of demonstrated technology -farmers' yield (control) TG = Potential yield-demonstration yield

Results and Discussion Effect on plant height

The average plant height observed for leaf color chart practice was 65.74 cm, while average plant height observed for farmers' practice was 58.3 cm during the time of harvest. Application of crop specific need of nitrogen fertilizer in split doses encourages plant growth, enhances the number and length of internodes of stem which eventually boosts the plant height (Amin, 2011) [2] . Nitrogen fertilizer management through Leaf Color Chart helps in plant growth enhancement, possibly by escalating the accessibility, uptake, and utilization of soil nutrients resulting from a elevated rate of split doses of nitrogen fertilizer.

Effect on leaf number

The maximum leaf number for leaf color chart practice was 87 at 75 DAT, while maximum leaf number for farmers' practice was 68 at 75 DAT. The higher leaf number was due to the balanced dose of nitrogen fertilizer application, which advanced the method of cell division and cell elongation, directing to amplification in both number and size of leaves (Om et al, 1989) [17] . The reduction in leaf number recorded after 75 DAT was mainly due to the senescence of lower leaves (Subedi et al, 2019) [22] . Chandrashekhar et al. (2001) opinioned that reduction of leaf size and number occurs after panicle initiation due to retransmission of stored metabolites from leaf sheath and stem to panicles.

Effect on tiller number

At 45, 60 and 75 DAT, LCC-based practice exhibited higher plant tillers than farmers' practice. This result may be due to proper split application of nitrogen fertilizer as nitrogen enhances cytokinin level within tiller nodes, which further encourages the germination of tiller primordium, thereby causing elevated tiller number (Liu et al, 2011) [14] .

Effect on Yield

Grain yield of rice in demonstrated plot was observed 60.13 q/ha, whereas it was recorded only 49.99 q/ha in farmers'

practice. The number of leaves is positively correlated with nitrogen assimilation rate in leaf. Effective use of nitrogen helped in increase of chlorophyll concentration in leaves and improved photosynthetic rate, ultimately resulting to a greater availability of photosynthates during grain development (Subedi et al, 2019) [22] . Therefore, the application of nitrogen fertilizer based on the LCC value maintained the appropriate level of leaf nitrogen leading to improved crop growth and a higher yield of rice grains. This finding is also in conformity with Ahmad et al.

(2016) [1] who found that nitrogen accelerates the accumulation of carbohydrates in the culms and leaf sheaths and in the grains during pre-heading and ripening stage of rice, respectively.

Effect on Economics

The gross and net economic returns for demonstrated plots were 20.29% and 73.45% higher, respectively, in contrast to farmers' practice during respective years. In comparison with farmers' practice, 122.1% higher benefit-cost ratios was observed, which confirm the viability of the LCC based nitrogen application in demonstrated plot to enhance the gross income of the farmers.

Effect on pest incidence

In demonstrated plots, the pest incidence was 84.23% lower than farmers' practice. High doses of nitrogen fertilizer make plant tissues more tender which can be easily be attacked by insects as reported by Singh and Sarkar (2021) [21] and Pramanick et al.

Extension Gap and Technology Gap

The extension gap was 10.14 q/ha in demonstrated plot, altering the trend of extension gaps by teaching farmers through trainings for the acceptance of improved and innovative production and protection technologies (Bhowmik et al., [5] . Technology gap was 4.87 q/ha, which confirms superior results in demonstrated plot. The obtained technological gap can be associated with the variations in soil fertility of the experimental plots and agricultural production techniques practiced by the farmers and also the prevailing weather circumstances of the locality as experienced by Bhowmik et al.

Conclusion

The experiment revealed that nitrogen application based on Leaf Color Chart gave superior results in terms of plant height, leaf number, tiller number and yield of rice than farmers' practice.

The better performance of LCC based nitrogen management is mainly due to more split application of nitrogen fertilizer during growing season along with balanced practice of fertilization. The technology of split application of nitrogen fertilizer after 45 days after transplanting when nitrogen demand is escalating in rice confirmed the elevated plant height. The yield in demonstration was also higher than the farmers' practice. Higher effective tiller number implied the increased yield which has confirmed the nitrogen requirement by measuring the leaf greenness with the help of low-cost devices like LCC (Hou et al., 2020) [9] . So, it is suggested to adopt the Leaf Color Chart based nitrogen fertilizer application practice as it emphasizes on the need based application of slit doses of nitrogen fertilizers, thus reduces the loss of nitrogen, improves soil health and reduces cost of cultivation of rice up to 20.52%. It also provides way forward for how to use nitrogen fertilizer in a proper way that maintains the leaf nitrogen content at an optimal level, resulting in a thriving rice produce and effective nitrogen usage.

Acknowledgement

AcknowledgementThe authors are thankful to the ICAR-ATARI, Kolkata, Zone V, for their support and funding of the frontline demonstration programme.

References

1. Ahmad N, Ahmad Z, Junaid M, Akhtar A. Bridging the yield gap in rice production by using leaf color chart for nitrogen management. Journal of Botany. 2016;2016:1-6.
2. Ali AM, Thind HS, Sharma S, Singh Y. Site-specific nitrogen management in dry direct-seeded rice using chlorophyll meter and leaf colour chart. Pedosphere. 2015;25(1):72-81.
3. Amin MEH. Effect of different nitrogen sources on growth, yield and quality of fodder maize (Zea mays L.). Journal of the Saudi Society of Agricultural Sciences. 2011;10(1):1723.
4. Banayo NP, Haefele SM, Desamero NV, Kato Y. On-farm assessment of site-specific nutrient management for rainfed lowland rice in the Philippines. Field Crops Research. 2018;220:88-96.
5. Bhowmik P, Shajahan M, Biswas P. Performance of improved integrated pest management (IPM) technology component for enhancing the productivity of Kharif black gram (Vigna mungo L.) under cluster front line demonstration at Malda, West Bengal, India. International Journal of Current Microbiology and Applied Sciences. 2019;8(10):987-996.
6. Dinnes DL, Karlen DL, Jaynes DB, Kaspar TC, Hatfield JL, Colvin TS, et al. Nitrogen management strategies to reduce nitrate leaching in tile-drained Midwestern soils. Agronomy Journal. 2002;94(1):153-171.
7. Gill A, Rajput A, Sharma A, Devi OR. Soil farming techniques for climate resilient agriculture. 2023.
8. Golicz K, Hallett SH, Sakrabani R. Old problem, the millennial solution: using mobile technology to inform decision making for sustainable fertilizer management. Current Opinion in Environmental Sustainability. 2021;49:26-32.
9. Hou W, Tränkner M, Lu J, Yan J, Huang S, Ren T, et al. Diagnosis of nitrogen nutrition in rice leaves influenced by potassium levels. Frontiers in Plant Science. 2020;11:165.
10. International Rice Research Institute. Use of leaf color chart (LCC) for nitrogen management in rice. Los Baños: International Rice Research Institute; 2005.
11. Jahan A, Islam A, Sarkar MI, Iqbal M, Ahmed MN, Islam MR. Nitrogen response of two high-yielding rice varieties as influenced by nitrogen levels and growing seasons. Geology, Ecology, and Landscapes. 2022;6(1):24-31.
12. Kivi MS, Blakely B, Masters M, Bernacchi CJ, Miguez FE, Dokoohaki H. Development of a data-assimilation system to forecast agricultural systems: a case study of constraining soil water and soil nitrogen dynamics in the APSIM model. Science of the Total Environment. 2022;820:153192.
13. Lindsay L, Lindsay D. Anza-Borrego Desert Region: your complete guide to the state park and adjacent areas of the Western Colorado Desert. Wilderness Press; 2017.
14. Liu Y, Ding YF, Wang QS, Meng DX, Wang SH. Effects of nitrogen and 6-benzylaminopurine on rice tiller bud growth and changes in endogenous hormones and nitrogen. Crop Science. 2011;51:786-792.
15. Midya A, Saren BK, Dey JK, Maitra S, Praharaj S, Gaikwad DJ, et al. Crop establishment methods and integrated nutrient management improve: Part I. crop performance, water productivity and profitability of rice (Oryza sativa L.) in the lower Indo-Gangetic plain, India. Agronomy. 2021;11(9):1860.
16. Oláh L, Tanaka HK, Varga D, editors. Muography: exploring Earth's subsurface with elementary particles. John Wiley & Sons; 2022.
17. Om H, Joon RK, Singh OP. Effect of time of transplanting and age of seedling on growth and yield of dwarf rice. Indian Journal of Agronomy. 1989;34(3):325-327.
18. Pramanick M, Des M, Ghosh MR, Mukherjee N. Effect of fertilizer treatments on growth, productivity, insect-pest and disease incidences on rice. Madras Agricultural Journal. 1995;82:525-527.
19. Rao KG, Das NK. Leaf color chart (LCC): a reliable tool for nitrogen management in dry seeded rice and transplanted rice: a review. The Pharma Innovation Journal. 2023;12(6):3974-3979.
20. Samui SK, Maitra S, Roy DK, Mandal AK, Saha D. Evaluation of frontline demonstration on groundnut. Journal of the Indian Society of Coastal Agricultural Research. 2000;18(2):180-183.
21. Singh A, Sarkar S. Effect of excess use of fertilizers on insect/pest infestation in Oryza sativa: a review. Journal of Entomology and Zoology Studies. 2021;9(5):246-252.
22. Subedi P, Sah SK, Marahatta S, Yadav DR. Effect of nitrogen management and varieties on growth and yield of dry direct seeded rice. Tropical Agricultural Science. 2019;42(2):453-460.
23. Tao M, Ma X, Huang X, Liu C, Deng R, Liang K, et al. Smartphone-based detection of leaf color levels in rice plants. Computers and Electronics in Agriculture. 2020;173:105431.