Integrated Zinc and Boron Fertilization Enhances Growth and Yield of Fine Rice (cv. Binadhan-25)

Rice (Oryza sativa L.) is a staple cereal crop and primary food source in Bangladesh, cultivated in 78% of the country’s total cropped area (Hasan et al., 2025; Roy et al., 2024; Jahan et al., 2017). Bangladesh ranks 3^rd among the countries that cultivate rice in terms of production (Mamun et al., 2021). Rice is grown on over 11.7 million hectares in Bangladesh and produced 20,768 metric tons of Boro rice in the year 2023-2024 (BBS, 2024). With the population growing by approximately 2 million people each year, the total population is projected to reach 238 million by 2050 (Shelley et al., 2016). To ensure food security for this expanding population, a substantial increase in rice production will be essential.

Boosting rice production requires effective fertilizer management and the correction of micronutrient deficiencies. Micronutrient deficiencies, such as those in zinc (Zn) and Boron (B), are highly prevalent in many Asian nations, as well as Bangladesh, due to factors such as high soil pH, low organic matter, salinity, drought, calcareous soils, and unbalanced fertilizer use (Akhtar et al., 2013; Chatzistathis, 2014; Malakouti, 2008). Zinc is essential for the synthesis of tryptophan, a precursor of the plant hormone auxin, and functions as a cofactor for over 300 enzymes. It plays a vital role in preserving the integrity of biological membranes, supporting pollen development, enhancing disease resistance, and facilitating protein synthesis and photosynthesis (Bhadra et al., 2023; Farooq et al., 2018). Rice yield increased with basal treatment of ZnSO₄, as reported by Zulfiqar et al., (2021). Research on micronutrients will help satisfy the growing demand for increased food production in the millennium, with improved nutritional content from minerals.

Boron is responsible for improved pollination, seed setting, and grain formation in various rice varieties. The maximum number of grains per panicle in the treatment plots compared to the control plots may be due to a reduction in pollen sterility of rice and proper grain filling (Bithy et al., 2020; Das et al., 2022).  Fatima et al., (2018) stated that maximum grain yield by soil application of B at the flowering stage might be the direct effect of a higher number of grains panicle^-1 and 1000-grain weight. Many reports indicate that B applied at the heading or flowering stage in rice resulted in increased rice grain yield and the number of grains per panicle (Hanifuzzaman et al., 2022). Similarly, Rehman et al., (2018) reported an enhanced paddy yield due to reduced panicle sterility following B application.

Due to the deficiency and crop responses, farmers in Bangladesh have been applying zinc (Zn) and boron (B) fertilizers to their crops lately. There are numerous interactions among nutrients when they are applied to soil, and these interactions are complex and depend on a wide range of factors (Hanifuzzaman et al., 2022). However, to our knowledge, no study has been reported to date on the interactions and efficiency of zinc and boron fertilizers applied together in rice crops. Therefore, this study was undertaken to investigate the effect of Zn and B on the growth and yield of fine rice (cv. Binadhan-25) using both basal and foliar applications.

Location and climate

The experiment was carried out at the Agronomy Field Laboratory of Bangladesh Agricultural University, Mymensingh, Bangladesh (24°25′ N latitude and 90°50′ E longitude, 18 meters above sea level) from November 2023 to April 2024 to evaluate the impact of various zinc and boron application methods on the growth and yield performance of rice. The experimental site is situated on non-calcareous dark grey floodplain soil, classified under the Sonatala soil series, which falls within the Old Brahmaputra Floodplain (Agro-Ecological Zone 9, AEZ-9). The field was medium-high land with moderate drainage capacity. The soil was a silty loam in texture, with a nearly neutral pH (6.48), low organic matter content (0.88%), and contained 0.67% total nitrogen, 15.37 ppm available phosphorus, 0.23 meq/100g exchangeable potassium, and 13.46 ppm available sulfur. Soil tests indicated that available zinc (0.23 ppm) and boron (0.16 ppm) were in the deficient range. Meteorological data recorded during the experimental period (Figure 1) provided information on temperature, rainfall, and relative humidity trends, which are essential factors influencing crop growth and yield performance.

Figure 1: Meteorological data for November 2023 to February 2024 at the experimental site

Experimental Design

The experiment was laid out using a randomized complete block design with three replications and eleven zinc and boron applications using basal and foliar methods:

1. Control (no zinc and no boron) (F₀)
2. Zn (2.0 kg ha^-1) and B (2.0 kg ha^-1) as basal (F₁)
3. 100% Zn as basal (without B) (F₂)
4. 100% B as basal (without Zn) (F₃)
5. 100% Zn foliar spray at pre-flowering stage (without B) (F₄)
6. 100% B foliar spray at pre-flowering stage (without Zn) (F₅)
7. 75% Zn and B as basal + 25% Zn and B foliar spray at pre- flowering stage (F₆)
8. 50% Zn and B as basal + 50% Zn and B foliar spray (F₇)
9. 100% Zn and B as basal + 25% Zn and B foliar spray (F₈)
10. 100% Zn and B as basal + 25% Zn foliar spray (F₉)
11. 100% Zn and B as basal + 25% B foliar spray (F₁₀)

Each block was divided into 11-unit plots, where the 11 treatments were allocated at random. There was a total of 33 unit plots in the experiment. The net size of each unit plot was 2.5 m × 2.0m. The spaces between replications and between plots were 1 m and 0.5 m, respectively.

Land Preparation and Intercultural Operation

Seeds of rice variety Binadhan-25 were collected from the Bangladesh Institute of Nuclear Agriculture (BINA), Mymensingh. Then the seeds were immersed in a water bucket for 24 hrs. These seeds were removed from the bucket and tightly covered with gunny bags. The seeds started sprouting after 48 hours, which became prepared for sowing within the next 72 hours.

The nursery bed was prepared by puddling, which involved repeated ploughing of nursery beds measuring 1.0 m in length and 1.0 m in width. Later, the seed was covered immediately, and then a light irrigation was given. The field was prepared by ploughing with tractor-drawn cultivators, followed by cross-harrowing to pulverize the soil. All uprooted weeds and crop residues were removed from the field after plowing and laddering. The experimental plots were fertilized with urea, triple superphosphate, and muriate of potash, as well as calcium sulfate at rates of 217, 119, 130, 77, 9.1, and 11.8 kg ha^-1, respectively. Except for urea, the entire amount of other fertilizers was applied before final land preparation. Urea was top-dressed in three installments at 15, 30, and 45 days after transplanting. The Zn and B were supplied at 2 kg ha^-1 in the form of zinc sulfate and boric acid, following respective treatments. The 35-day-old seedlings were transplanted in the main field with a spacing of cm as row to row and hill to hill distance, respectively, with 2-3 seedlings per hill. A thin layer of water was maintained at the time of transplanting to facilitate the better establishment of the seedlings. From the third day onwards, a 2 to 3 cm depth of water was maintained up to the panicle initiation stage, except at the time of top dressing with urea, when the water was drained out and re-irrigated to maintain a 5 cm depth of water up to physiological maturity. After the dough stage, water was entirely drained out to make harvesting easier.

Data Collection and Harvesting

The crop was harvested at full maturity, when approximately 80% of the seeds turned golden yellow. Five hills (excluding border hills) were randomly pre-selected from each plot and uprooted before harvest to record data on various plant characteristics. After harvesting, the crops from each plot were separately bundled, tagged, and brought to the threshing floor. The crops were threshed using a pedal thresher, and the grains were sun-dried and cleaned. The straws were also properly sun-dried. Both grain and straw yields were then converted to tonnes per hectare (t ha^-1).

Plant height

Five hills were randomly selected soon after transplanting and marked with bamboo sticks in each plot, excluding border rows, to record the data on plant height at 45, 60, and 75 DAT. Then the plant height at 45, 60, and 75 DAT was measured from the base to the tip of the longest panicle and expressed in cm.

Total tillers hill^-1

Five hills were randomly selected in each plot, excluding border rows, to record the data of the number of tillers hill-1 at 45, 60, and 75 DAT. Then, the number of tillers hill^-1 at 45, 60, and 75 DAT was measured.

Effective tillers hill^-1

The panicles that had at least one grain were considered effective tillers. The number of effective tillers in hill-1 was recorded and then averaged to determine the number of effective tillers in hill-1 and non-effective tillers in hill^-1. The tiller with no panicle was regarded as an ineffective tiller. The number of effective tillers in Hill^-1 was recorded and then averaged to determine the number of ineffective tillers in Hill^-1.

Panicle length

Panicle length was recorded from the basal node of the rachis to the apex of each panicle.

Grains panicle^-1

Grain was considered to be filled if any kernel was present there. The number of total filled grains present on five panicles was recorded and finally averaged.

 Sterile spikelet panicle^-1

Unfilled grains mean the absence of any kernel inside, and such grains present on each of the five panicles were counted and finally averaged.

1000-grain weight

One thousand cleaned, dried grains were randomly counted from each sample and weighed using a digital electric balance. At this stage, the grain retained about 14% moisture, and the mean weights were expressed in grams.

Grain yield

Grain yield was determined from the central 1 m² areas of each plot and expressed as t ha^-¹ on a basis of approximately 14% moisture. Grain moisture content was measured by using a digital moisture tester.

Straw yield

The straw yield was determined from the central 1 m² areas of each plot. After separating the grains, the sub-samples were oven-dried to a constant weight and finally converted to t ha^-1.

Biological yield

Grain yield and straw yield was all regarded together as biological yield. The biological yield was calculated with the following formula:

Biological yield (t ha^-1) = Grain yield (t ha^-1) + Straw yield (t ha^-1)

Harvest index (%)

It denotes the ratio of grain yield to biological yield and was calculated with the following formula:

Statistical Analysis

The data collected for various traits were subjected to statistical analysis to evaluate significant differences among the treatments. Analysis of Variance (ANOVA) was conducted for all recorded parameters using the R software package (R Core Team, 2024). Treatment means were compared using Duncan’s New Multiple Range Test (DNMRT), as described by Gomez and Gomez (1984).

panicle⁻¹ (GP), grain yield (GY), straw yield (SY), biological yield (BY), and harvest index (HI). This indicates that moderate to balanced combined applications of Zn and B (both basal and foliar) contributed substantially to improved performance in these traits. In contrast, treatments F₀ (control) and F₂ were distantly positioned from most of the yield-related traits, suggesting poor performance across those parameters. Treatments F₃ and F₄ were positively aligned with sterile spikelets panicle⁻¹ (SS), indicating higher spikelet sterility and hence lower yield performance. Overall, the PCA analysis revealed that treatment F7, and to a lesser extent F6 and F8, effectively enhanced yield and yield components in rice through integrated Zn and B nutrient management.

Figure 5: Biplot of principal component analysis (PCA) showing the distribution of growth and yield-related traits of fine rice across different zinc (Zn) and boron (B) management treatments. The first two principal components (Dim 1 and Dim 2) represent the significant variation among traits and treatments. Trait abbreviations: PH – Plant height (cm), TT – Total tillers hill⁻¹, ET – Effective tillers hill⁻¹, NET – Non-effective tillers hill⁻¹, PL – Panicle length (cm), GP – Grains panicle⁻¹, SS – Sterile spikelets (no.), GW – 1000-grain weight (g), GY – Grain yield (t ha⁻¹), SY – Straw yield (t ha⁻¹), BY – Biological yield (t ha⁻¹), HI – Harvest index (%). Treatments: F0 – Control (no Zn and B), F1 – Zn (2.0 kg ha⁻¹) + B (2.0 kg ha⁻¹) as basal, F2 – 100% Zn as basal (no B), F3 – 100% B as basal (no Zn), F4 – 100% Zn as foliar spray (no B), F5 – 100% B as foliar spray (no Zn), F6 – 75% Zn and B as basal + 25% as foliar spray, F7 – 50% Zn and B as basal + 50% as foliar spray, F8 – 100% Zn and B as basal + 25% Zn and B as foliar spray, F9 – 100% Zn and B as basal + 25% Zn as foliar spray, F10 – 100% Zn and B as basal + 25% B as foliar spray.

Functional relationship between the number of tillers hill^-1 and grain yield

A positive linear relationship between grain yield and number of tillers hill^-1 at 60 DAT of fine rice, which indicated that the higher the number of tillers hill^-1, the higher the grain yield (t ha^-1). The relationship between the number of tillers per hill^-1 and the grain yield of fine rice was determined using the respective interaction data between Zn and B fertilizer application. The response of the number of hills on the grain yield of fine rice followed a linear positive relationship, which could be adequately described by the regression equation Y = 4.5452x - 17.135 (R² = 0.8858), as shown in Figure 6. A similar result was also observed by Paul et al., (2021).

Figure 6: Functional relationship between the number of tillers hill^-1 and the grain yield of fine rice

Functional relationship between dry weight and grain yield

The response of total dry matter at 60 DAT to the grain yield of fine rice followed a linear positive relationship, which could be adequately described by a regression equation. In Figure 7, the regression equation suggests that an increase in dry weight is associated with a corresponding increase in fine rice grain yield. The functional relationship can be determined by the regression equation Y = 10.311x - 39.746 (R² = 0.9728) (Figure 7). A similar result was also observed by Paul et al., (2021).

Figure 7: Functional relationship between dry matter weight and grain yield of fine rice

This study emphasizes the importance of addressing micronutrient deficiencies, specifically zinc and boron, to improve rice productivity in Bangladesh. The combined application of 50% Zn and B as basal and 50% as foliar spray significantly improved key growth parameters and yield components of Binadhan-25, including plant height, tiller number, grain yield (6.98 t ha^-1), and harvest index (48.46%), compared to the control. These findings highlight the importance of balanced micronutrient management in conjunction with NPK fertilization for sustainable rice production. The study offers a practical approach for enhancing nutrient use efficiency and improving crop performance. However, its single-location and single-season design limits the generalizability of the results. Future research should evaluate the effectiveness of this approach across diverse rice varieties, soil conditions, and agro-ecological zones, along with a cost-benefit analysis to support its adoption by farmers.

Abbas, M., Z. Zahida, T. M. Uddin, R. Sajjid, I. Akhlaq, A. Moheyuddin, K. Salahuddin, J. Mari and A. H. Panhwar. 2013. Effect of Zinc and Boron Fertilizers Application on Some Physicochemical Attributes of Five Rice Varieties Grown in Agro-Ecosystem of Sindh, Pakistan. American-Eurasian J. Agric. & Environ. Sci., 13(4): 433–439.

Akhtar, S., T. Ismail, S. Atukorala and N. Arlappa. 2013. Micronutrient deficiencies in South Asia – Current status and strategies. Trends in Food Science & Technology, 31(1): 55–62. https://doi.org/10.1016/j.tifs.2013.02.005

Arif, M., M. A. Shehzad, F. Bashir, M. Tasneem, G. Yasin and M. Iqbal. 2012. Boron, zinc and microtone effects on growth, chlorophyll contents and yield attributes in rice (Oryza sativa L.) cultivar. African Journal of Biotechnology, 11(48): 10897–10905. https://doi.org/10.5897/AJB12.393

BBS. 2024. Yearbook of Agricultural Statistics of Bangladesh. Statistics Division,Ministry of Planning, Government of the People’sRepublic of Bangladesh, Dhaka. pp. 39–42

Bhadra, T., C. K. Mahapatra, M. Hosenuzzaman, D. R. Gupta, A. Hashem, G. D. Avila-Quezada, E. F. Abd_Allah, M. A. Hoque and S. K. Paul. 2023. Zinc and Boron Soil Applications Affect Athelia rolfsii Stress Response in Sugar Beet (Beta vulgaris L.) Plants. Plants, 12(19): 3509. https://doi.org/10.3390/plants12193509

Bithy, S., S. K. Paul, M. A. Kader, S. K. Sarkar, C. K. Mahapatra and A. K. M. R. Islam. 2020. Foliar application of boron boosts the performance of tropical sugar beet. Journal of Bangladesh Agricultural University, 18(3): 537–544. https://doi.org/10.5455/JBAU.121026

Chattha, M. B., Q. Ali, M. N. Subhani, M. Ashfaq, S. Ahmad, Z. Iqbal, M. Ijaz, M. A. Ayub, M. R. Anwar, M. Aljabri, M. U. Hassan and S. H. Qari. 2023. Foliar applied zinc on different growth stages to improves the growth, yield, quality and kernel bio-fortification of fine rice. Notulae Botanicae Horti Agrobotanici Cluj-Napoca, 51(2): 13221. https://doi.org/10.15835/nbha51213221

Chatzistathis, T. 2014. Chapter 13—Plant Responses to Iron, Manganese, and Zinc Deficiency Stress. In P. Ahmad and S. Rasool (Eds.), Emerging Technologies and Management of Crop Stress Tolerance (pp. 293–311). Academic Press. https://doi.org/10.1016/B978-0-12-800876-8.00013-8

Das, S., S. K. Paul, M. R. Rahman, S. Roy, F. M. J. Uddin and M. H. Rashid. 2022. Growth and Yield Response of Soybean to Sulphur and Boron Application. Journal of the Bangladesh Agricultural University, 20(1): 1–10. https://doi.org/10.5455/JBAU.100644

Farooq, M., A. Ullah, A. Rehman, A. Nawaz, A. Nadeem, A. Wakeel, F. Nadeem and K. H. M. Siddique. 2018. Application of zinc improves the productivity and biofortification of fine grain aromatic rice grown in dry seeded and puddled transplanted production systems. Field Crops Research, 216: 53–62. https://doi.org/10.1016/j.fcr.2017.11.004

Fatima, A., S. Ali, M. Ijaz, R. Mahmood, S. Sattar, J. Khan, A. I. Dar and M. Ahmad. 2018. Boron Application Improves the Grain Yield and Quality of Fine Grain Rice Cultivars in Punjab, Pakistan. Pak. J. Agri. Sci., 55(4): 761–766.

Gomez, K. A. and A. A. Gomez. 1984. Statistical Procedures for Agricultural Research. 2nd Ed., John Wiley and Sons. New York. pp. 97-111.

Hanifuzzaman, M., F. M. J. Uddin, M. G. Mostofa, S. K. Sarkar, S. K. Paul and M. H. Rashid. 2022. Effect of zinc and boron management on yield and yield contributing characters of Aus rice (Oryza sativa). Research on Crops, 23(1): 1–8. https://doi.org/10.31830/2348-7542.2022.001

Hasan, R., B. R. Deb, A. Mallick, A. Roy, M. A. R. Sarkar, & S. K. Paul. 2025. Integrated nutrient management influences the morpho-physiology and yield of aromatic fine rice under subtropical conditions. Egyptian Journal of Agronomy, 47(4):781–790. https://doi.org/10.21608/agro.2025.359840.1627

Jahan, S., M. A. R. Sarkar, & S. K. Paul. 2017. Effect of Plant Spacing and Fertilizer Management on the Yield Performance of BRRI dhan39 under Old Brahmaputra Floodplain Soil. Madras Agricultural Journal, 104(1–3): 37–40. https://doi.org/10.29321/MAJ.01.000394

Malakouti, M. 2008. The Effect of Micronutrients in Ensuring Efficient Use of Macronutrients. Turkish Journal of Agriculture and Forestry, 32(3): 215–220.

Mamun, M. A. A., S. A. I. Nihad, M. A. R. Sarkar, M. A. Aziz, M. A. Qayum, R. Ahmed, N. M. F. Rahman, M. I. Hossain and M. S. Kabir. 2021. Growth and trend analysis of area, production and yield of rice: A scenario of rice security in Bangladesh. PLOS ONE, 16(12): e0261128. https://doi.org/10.1371/journal.pone.0261128

Nishad, R. A., M. R. Rahman, M. S. Kabiraj,, S. K. Sarkar, F. M. J. Uddin, M. H. Rashid, & S. K. Paul. 2025. Zinc supplementation boosts the yield performance of aromatic Boro rice (cv. BRRI dhan50). Journal of Aridland Agriculture, 11:116–120. https://doi.org/10.25081/jaa.2025.v11.9254

Paul, N. C., S. K. Paul, A. Salam and S. C. Paul. 2021. Dry Matter Partitioning, Yield and Grain Protein Content of Fine Aromatic Boro Rice (cv. BRRI Dhan50) in Response to Nitrogen and Potassium Fertilization. Bangladesh Journal of Botany, 50(1): 103–111.

Quddus, M. A., M. H. Rashid, M. A. Hossain and H. M. Naser. 2011. Effect of Zinc and Boron on Yield and Yield Contributing Characters of Mungbean in Low Ganges River Floodplain Soil at Madaripur, Bangladesh. Bangladesh Journal of Agricultural Research, 36(1): 73–81. https://doi.org/10.3329/bjar.v36i1.9231

R Core Team. 2024. R: A Language and Environment for Statistical Computing (version 4.2.2). Vienna, Austria: R Foundation for Statistical Computing.

Rehman, A. U., M. Farooq, A. Rashid, F. Nadeem, S. Stuerz, F. Asch, R. W. Bell and K. H. M. Siddique. 2018. Boron nutrition of rice in different production systems. A review. Agronomy for Sustainable Development, 38(3): 25. https://doi.org/10.1007/s13593-018-0504-8

Roy, T. R., M. A. R. Sarkar, M. S. Kabiraj, U. K. Sarker, M. H. Rashid, A. Hashem, G. D. Avila-Quezada, E. F. Abd_Allah and S. K. Paul. 2024. Productivity and Grain Protein Status of Transplanted Aman Rice as Influenced by Three Major Agronomic Practices Under Subtropical Conditions. Applied Ecology and Environmental Research, 22(2): 1013–1028. https://doi.org/10.15666/aeer/2202_10131028

Saikh, R., K. Murmu, A. Sarkar, R. Mondal and K. Jana. 2022. Effect of foliar zinc application on growth and yield of rice (Oryza sativa) in the Indo-Gangetic Plains of India. Nusantara Bioscience, 14(2): 182–189. https://doi.org/10.13057/nusbiosci/n140208

Shaygany, J., N. Peivandy and S. Ghasemi. 2012. Increased yield of direct seeded rice (Oryza sativa L.) by foliar fertilization through multi-component fertilizers. Archives of Agronomy and Soil Science, 58(10): 1091–1098. https://doi.org/10.1080/03650340.2011.570336

Shelley, I. J., M. Takahashi-Nosaka, M. Kano-Nakata, M. S. Haque and Y. Inukai. 2016. Rice Cultivation in Bangladesh: Present Scenario, Problems, and Prospects. Journal of International Cooperation for Agricultural Development, 14: 20–29. https://doi.org/10.50907/jicad.14.0_20

Singh, V. P., S. S. Singh, R. P. Singh, K. Singh, A. P. Singh and S. K. Yadav. 2021. Study the effect of soil and foliar application of Fe, Zn and B on growth factors of rice. International Journal of Chemical Studies, 9(2): 179–182. https://doi.org/10.22271/chemi.2021.v9.i2c.11802

Soltani, S. M., M. Allahgholipoor, M. S. Katigari and A. P. Tabalvandani. 2020. Effect of Basal and Foliar Application of Zinc Sulphate Fertilizer on Zinc Uptake, Yield and Yield Components of Rice (Hashemi Cultivar). Iranian Journal of Soil and Water Research, 51(4): 1013–1026. https://doi.org/10.22059/ijswr.2020.291977.668383

Yogi, L. N., S. Bhandari, T. Thalal, M. Bhattarai, A. Upadhyay and B. Kharel. 2024. Enhancing rice yields through foliar application of essential micronutrients: A study on zinc, copper, and boron nutrition in context of Nepal. Archives of Agriculture and Environmental Science, 9(2): 373–378. https://doi.org/10.26832/24566632.2024.0902024

Zulfiqar, U., S. Hussain, M. Maqsood, M. Ishfaq and N. Ali. 2021. Zinc nutrition to enhance rice productivity, zinc use efficiency, and grain biofortification under different production systems. Crop Science, 61(1): 739–749. https://doi.org/10.1002/csc2.20381