Effect of a Slow-Release Urea Nanofertilizer on Soil Microflora and Yield of Direct Seeded Rice (Oryza sativa L.)

Abstract

Nitrogen fertilizers have a significant impact on the growth of rice. The overuse and inappropriate application of nitrogen fertilizers have resulted in environmental pollution, in addition to subjecting both humans and livestock to negative health hazards. Finding a viable substitute for traditional nitrogen fertilizers is crucial and essential to help improve crop yield and minimize environmental damage. Nano-nitrogen fertilizers offer a possible alternative to traditional fertilizers due to a slow/controlled release of nitrogen. The present work aimed to study the effect of a slow-release urea nanofertilizer on soil ammonical (NH₄-N) and nitrate-N (NO₃-N) content, culturable soil microflora, and soil enzyme activities in three different soil samples procured from Ludhiana and Patiala districts through a soil column study. Seven treatments, including 0, 50 (75 kg/ha N), 75 (112.5 kg/ha N), and 100% (150 kg/ha N) of the recommended dose (RD) of conventional urea and nano-urea fertilizer were applied. The leachate samples collected from nano-urea treatment exhibited NH₄-N for the first two weeks, followed by NO₃-N appearance. The higher NH₄-N and NO₃-N contents in the leachate were recorded for light-textured soil as compared to medium- and heavy-textured soil samples. The soil microbial counts and enzyme activities were recorded to be maximum in light-textured soils. Therefore, this slow-release formulation could be more useful for light-textured soils to decrease applied N-fertilizer losses, as well as for improving the soil microbial viable cell counts and soil enzyme activities. The effect of urea nanofertilizer on the growth and yield of direct-seeded rice (Oryza sativa L.) was also evaluated under field conditions. Both studies were performed independently. Numerically, the highest shoot height, fresh and dry shoot weight, and significantly maximum total chlorophyll, carotenoid, and anthocyanins were recorded in the T2 (100% RDF through nano-urea) treatment. The yield-attributing traits, including the number of filled grains and thousand-grain weight, were also recorded to have increased in T2 treatment. A numerical increase in NPK for plant and grain of rice at 100% RDN through nano-urea was recorded. The soil application of the product exhibited no negative effect on the soil microbial viable cell count on different doses of nano-urea fertilizer. The soil nitrogen fixer viable counts were rather improved in nano-urea treatments. The results reflect that nano-urea fertilizer could be considered as a possible alternative to conventional fertilizer.

1. Introduction

Rice belongs to the family Gramineae and includes Asian (Oryza sativa) and African rice (O. glaberrima). It is the most widely consumed staple food across the globe, particularly in the Asia continent. The total production of rice has been estimated at a record 117.47 MT, which is greater compared to the 5-year average production (107.80 MT) (FAOSTAT 2024, https://www.fao.org/faostat/en/#data/QCL (accessed on 7 September 2024)). India is one of the biggest global producers of rice, including both white and brown rice, which is cultivated on 46.40 million hectares of land, accounting for a total production of 196.24 million tons (FAO STAT 2024, https://www.fao.org/faostat/en/#data/QCL (accessed on 7 September 2024)). Rice is popularly cultivated in specific Rice-wheat cropping systems in India. This crop requires significant amounts of inorganic fertilizers for optimal growth and grain yield, and therefore, rice productivity is directly affected by the physical and chemical properties of the soil, particularly the nutritional status as indicated through available nitrogen, phosphorus, potassium, sulfur, and zinc nutrients [1].

The rice crop relies primarily on the breakdown of organic matter in an oxygen-deprived environment to acquire nitrogen [2]. Under submerged soil conditions, ammonia, the stable form of nitrogen, is absorbed by the rice plant [3,4]. However, during cultivation of the conventional transplanted rice, ammonia volatilization becomes a significant pathway for nitrogen loss from the soil [5]. This process not only contributes to air and environmental pollution but also results in decreased fertilizer nitrogen availability [6]. To maintain high rice yields, urea is commonly used as the nitrogen fertilizer of choice for rice crops [7]. It is applied at a rate of 100 kg ha⁻¹ of urea-N through broadcasting [8]. In contrast to urea, larger amounts of ammonical and nitrate fertilizers (more than 200 kg ha⁻¹) are required, which incur higher N-losses in rice field conditions [9,10]. Consequently, urea demonstrates higher efficiency when compared to other nitrogen fertilizers under conventional transplanted rice cultivation conditions [10]. To minimize nitrogen loss and enhance nitrogen use efficiency, the development of improved urea fertilizer formulations is crucial for rice cultivation [11]. In spite of relatively better use efficiency than that of ammonical and nitrate-based N-fertilizers, urea exhibits significant soil losses of up to 50–70% of the applied nitrogen, primarily through leaching, evaporation, or transformation [12]. These losses depreciate fertilizer use efficiency and result in increased production costs [11].

Encapsulation and embedding of urea in polymer and inorganic matrices, respectively, can be a possible alternative to develop new formulations of urea [13]. Encapsulated nanofertilizers serve as carriers for both macro and micronutrients, tailored to meet the specific nutritional requirements of crops [14,15]. Nitrogen nanofertilizers are anticipated to enhance the nutrient uptake by plants due to the presence of nutrient elements at nano-scale dimensions (ranging from 1 to 100 nm), facilitating improved absorption [16]. The nanofertilizer approaches provide a broad spectrum of macro- and micro-nutrients with desirable characteristics [17,18]. Apart from nutrient supply, these fertilizers substantially impact the physiological and biochemical processes of crops, resulting in higher apical growth and a larger photosynthetic area. The nano-nutrients led to improved vegetative growth through enhanced nutrient availability due to the easy penetration of nano-nutrient formulations through a variety of plant tissues, including the stomata on the leaves and root epidermal cells [19]. The primary objective of slow-release nanofertilizers in the soil is to release essential agrochemicals in a controlled manner over a specific period, ensuring optimal biological efficacy while minimizing losses and negative environmental impacts. In a published report, the use of urea-coated nanoparticle hybrids in rice showed 50% less consumption of urea [20].

The soil-applied nano-nutrient fertilizers can affect the biotic components of the soil, particularly the native soil microflora. The soil microbes play a crucial role in the agricultural ecosystem by aiding in the fixation, solubilization, mobilization, and recycling of both macro and micronutrients. Slow-release nanofertilizers will directly or indirectly alter the soil pH and the growth of soil microorganisms, including the changes in the microbial viable cell counts and diversity [21]. Overall, the application of nanofertilizers positively impacts soil microorganisms by providing essential nutrients, enhancing soil ecological conditions, and increasing microbial populations [22]. This contributes to improved soil fertility, nutrient cycling, and overall soil health. Considering the significance of the nanoparticulate matter in enhancing the use efficiency of urea, this research aimed to evaluate the effect of the application of conventional neem-coated urea and nano-calcium phosphate-impregnated urea formulations at three different dosages in three different soil texture types on soil ammoniacal and nitrate-N content, soil microflora and enzyme activities in soil column study. Also, these formulations were evaluated under field conditions at the same application rates as performed in the soil column study to elucidate the comparative effect on growth, yield attributes, and culturable soil microbial diversity in direct-seeded rice.

2. Materials and Methods

The nano-urea formulation was procured as prepared in the form of calcium phosphate-embedded urea [20]. The generated product has already been characterized through a variety of spectroscopy and microscopy tools (unpublished data). The composition of the synthesized nano-urea formulation involved the presence of N, Ca, and P in 39.6%, 38.7%, and 17.63%, respectively. While the neem-coated urea (conventional urea) commercial formulation, which was purchased from the market, had the following percentage of the constituent elements: Carbon: 46.65%, Nitrogen: 46.65%, and Oxygen: 6.70%.

2.1. Soil Column Study

A soil column study was performed to evaluate the slow/controlled release of the urea from the nano-urea product. Three types of soil texture samples were collected from three different locations with light or coarse textured soil collected from research fields of Rice B Block, Department of Plant Breeding and Genetics, medium textured from Vegetable farms, Department of Vegetable Science, Punjab Agricultural University, Ludhiana, while the heavy textured soil sample was collected from Experimental fields, Krishi Vigyan Kendra, Patiala, Punjab, India. The initial soil chemical properties of each soil sample have been provided in Supplementary Table S1.

2.1.1. Soil Column Design

Experiments were carried out using four sets of 16 columns fabricated with polyvinyl chloride (PVC) pipes with an inner diameter of 5.8 cm and a height of 33 cm. These PVC pipes were housed in an iron mesh enclosure (Supplementary Figure S1). The top of the iron mesh enclosure was covered with asbestos sheets/tiles so that the experimental setup was not affected by direct rain and only received a known volume of water. The study was performed under ambient conditions with natural light and relative humidity conditions. A layer of cheesecloth was positioned at the base of each column, followed by a 2 cm layer of pea gravel. This arrangement served the purpose of retaining soil within the columns and filtering soil particles from the leachate. The sampled soil was filled in each column to pack 25 cm of column height to obtain uniform density throughout the entire soil column length. Each column was plugged into a PVC cap with a drain hole at the bottom that allowed leachate to drain into collection bottles of 50 mL [23].

2.1.2. N-Fertilizer Application

The three N levels were 50, 75, and 100% of the recommended dose of N-fertilizer (RDN) along with 0% RDN (absolute fertilizer control) for two types of N-fertilizer sources (conventional neem-coated urea vs. nano-urea composite fertilizer) were evaluated in this study (Supplementary Table S2). Both fertilizers were applied after washing the soil columns with distilled water. The soil columns were irrigated once every three days, using 100 mL of deionized water. The experiments were conducted for 30 days for each soil. Leachate samples were collected every day.

2.1.3. Parameters Studied in Soil Column Experiment

Leachate samples were subjected to UV-Vis Spectroscopy for ammonical and nitrate-N analysis by recording the absorbance at λmax of 640 and 210 nm, respectively. For estimation of ammonical content from the leachate indophenol blue method was used [24] while the nitrate-N content was estimated through UV-Vis spectroscopy [25]. The soil samples were also extracted from each column, and different soil microbiological assays were performed every ten days to one-month duration to study the effect of nano-N fertilizer on the viable count of total aerobic bacteria, fungus, and non-symbiotic nitrogen fixers population through soil dilution spread plating technique [26]. Three representative soil enzymatic activities, including urease [27], protease [28] and dehydrogenase [29] were also determined.

2.2. Field Study

A field experiment was conducted at Rice B Block fields, Department of Plant Breeding and Genetics, PAU Campus, Ludhiana, Punjab. The field experiment was performed in Kharif season 2021 on rice variety PR-126. Direct seeding at the rate of 25 kg per hectare was done and maintained as per the standard agronomic practices for the cultivation of the direct seeded rice. The conventional urea and nano-urea fertilizers were applied to the soil as per the schedule. The treatments included varying rates of 0, 50%, 75%, and 100% of the recommended N-fertilizer dose of conventional and nano-urea fertilizer. The other fertilizers were applied as per the recommended practices for fertilizer application for DSR as delineated in the Package of practices. All the treatments were performed in triplicate.

2.2.1. Vegetative Growth and Photosynthetic Parameters

The plant height and shoot fresh and dry weight were measured from the three randomly selected plants at 30, 60, and 90 DAS. The root’s fresh and dry weight was also measured by cutting the plant from the root-shoot intersection. For the dry weight estimation after recording the fresh weight, samples were dried in a hot air oven at 60 °C for four days, and the dry weight of the shoot/root was taken. The SPAD at 50% flowering was determined using the SPAD photometer (SPAD-502, Soil Plant Analysis Development (SPAD) Section, Minolta Camera Co., Osaka, Japan) after two months of sowing. The chlorophyll content in leaf samples was estimated through the acetone extraction method [30]. For the total carotenoid content, the same extracted samples were used, and the absorbance at 470 nm was taken [31]. The total anthocyanin content in the leaves samples was estimated using an acidic methanol-water solution (9.9:0.1 v/v). The absorbance was measured at 530 nm and 657 nm wavelength by using a spectrophotometer [32] and the calculations were performed as per the following equation:

$$TA={\displaystyle \raisebox{1ex}{$A530-0.3A657\times V$}\!\left/ \!\raisebox{-1ex}{$M$}\right.}$$

2.2.2. Grain Yield Parameters and Straw Yield

The length of tillers was recorded from 2 different sites from each bed of treatment. The days to 50% flowering were determined after two months of sowing. After harvesting, five plants were randomly chosen from each treatment, and one panicle of each plant was collected and then weighed. Grains from each panicle per plant were collected and then weighed by weighing balance machine in grams (g). The number of filled and unfilled grains was counted manually in each treatment after 90 DAS. The thousand-grain weight was calculated using the following formula in grams (g):

$$Thousandgrainweight\left(\mathrm{g}\right)={\displaystyle \frac{Grainweight}{Numberofpanicletaken}}\times 1000$$

2.2.3. Plant Nutrient Parameters

The root, shoot, and grain samples were dried in an oven at 65 °C to obtain constant dry weight. Then, the samples were crushed in a pestle mortar and sieved through a 1 mm sieve and used for estimation of nitrogen, phosphorus, and potassium content using Kjeldahl’s method [33], ammonium vanadate-molybdate yellow color method in nitric acid [34], and flame-photometer [35] methods, respectively.

2.2.4. Soil Nutrient and Microbiological Parameters

The soil available nitrogen, phosphorus, and potassium contents were estimated for the soil samples collected from a depth of 15 cm at every 30-day interval till 90 days after sowing. The soil available nitrogen was estimated by the alkaline permanganate method [36]. The available phosphorous was determined through the colorimetry method [37]. The soil available potassium was estimated through the flame photometry method [38].

The serial dilution spread plate method was used to enumerate the viable counts of the soil microbes on eight rich and differential solid agar-based media from soil sampled at every 30-day interval till 90 days after sowing [26]. The number of microbes per gram of soil was determined as per this equation:

$$\mathrm{N}\mathrm{u}\mathrm{m}\mathrm{b}\mathrm{e}\mathrm{r}\mathrm{o}\mathrm{f}\mathrm{C}\mathrm{F}\mathrm{U}/\mathrm{g}\mathrm{o}\mathrm{f}\mathrm{s}\mathrm{o}\mathrm{i}\mathrm{l}={\displaystyle \frac{Numberofcolonies\times dilutionfactor}{dryweightofsoilsample}}$$

2.3. Statistical Analysis

The data collected from the soil column study was subjected to an analysis of variance using factorial CRD at p ≤ 0.05 using SAS Software (version 9.3, Cary, NC, USA). The data collected from the field experiment was subjected to an analysis of variance using the Randomized Block Design (RBD) at p ≤ 0.05 using SAS Software (version 9.3, Cary, NC, USA).

3. Results

3.1. Soil Column Study

• Estimation of N-Content of the Leachate

The effect of the slow release of the urea from the nano-urea products was observed for three soil textures (light, medium, and heavy). The release of ammonical and nitrate content was studied for 30 days (

Table 1. Analysis of variance and mean effect of different nitrogen fertilizer sources, soil textures, and N-fertilizer levels on ammonical and nitrate N content of the soil.

Source	Ammonical-N Content (mg L−1)						Nitrate-N Content (mg L−1)
	1st Day		Week 1	Week 2	Week 3	Week 4	1st day	Week 1	Week 2	Week 3	Week 4
N-fertilizer Source
Conv-Urea	7.095 a		4.346 a	1.636 a	0.304 b	0.300 b	2.912 a	3.240 a	3.564 a	3.532 a	3.552 b
Nano-Urea	5.806 b		4.641 a	1.834 a	1.584 a	1.348 a	2.377 b	3.123 b	3.515 a	3.547 a	3.631 a
LSD (p ≤ 0.05)	0.053		0.437	0.258	0.182	0.008	0.019	0.050	0.083	0.023	0.030
Soil Type
Low	9.653 a		7.985 a	2.010 a	0.780 a	0.400 c	2.811 a	3.563 a	3.826 a	3.764 a	3.686 a
Medium	5.342 b		3.305 b	1.875 b	0.554 b	0.321 a	2.626 ab	3.0991 b	3.650 b	3.477 b	3.597 a
Heavy	4.355 c		2.190 c	1.320 c	0.001 c	0.251 b	2.497 b	2.882 c	3.142 c	3.377 c	3.491 b
LSD (p ≤ 0.05)	0.487		0.327	0.166	0.07	0.018	0.197	0.040	0.117	0.067	0.096
N-fertilizer Level
0	1.986 b		1.251 b	0.454 c	0.368 b	0.121 c	1.123 c	1.131 b	0.494 b	0.330 b	0.269 b
50%	7.124 a		5.1527 a	1.663 b	0.387 b	0.383 b	2.321 b	3.149 b	3.544 ab	3.528 b	3.606 a
75%	7.324 a		5.276 a	1.751 b	0.499 a	0.384 b	2.752 a	3.187 ab	3.570 a	3.531 b	3.652 a
100%	7.366 a		5.295 a	2.072 a	0.522 a	0.409 a	2.776 a	3.258 a	3.570 a	3.598 a	3.838 a
LSD (p ≤ 0.05)	0.381		0.239	0.166	0.05	0.011	0.204	0.072	0.083	0.053	0.069
ANOVA analysis	D.f.
Soil type	2	190.493 ***	226.943 ***	3.218 ***	3.883 ***	0.134 ***	0.600 **	2.91 ***	3.024 ***	0.969 ***	0.229 ***
N-fertilizer Source	1	29.906 ***	1.560 ***	0.702 ***	1.413 ***	0.042 ***	5.147 ***	0.247 ***	0.042 ns	0.004 ns	0.110 **
N-fertilizer Level	3	48.770 ***	40.315 ***	1.189 ***	0.109 ***	0.333 ***	0.446 ns	0.057 **	0.037 ns	0.031 **	0.126 ***
Soil type × N-fertilizer source × N-fertilizer level	6	3.998 ***	7.186 ***	0.133 ns	0.089 ***	0.002 ***	0.343 **	0.112 ***	0.014 ns	0.005 **	0.031 **

** = p ≤ 0.01, *** = p ≤ 0.001, ns = not significant. Mean values with different alphabetic scripting in a column depict statistical significant difference.

). The soil type, treatment, and interaction of soil type and different treatments significantly affected the ammonical content. The soil type and interaction of soil type and different treatments for nitrate content was significantly affected but was non-significantly affected by the different treatments.

3.1.1. Ammonical and Nitrate N Content of the Leachate Samples

The ammonical content in leachate was maximum in 100% of the recommended dose of urea treatment and decreased with the increase in the time interval (from week 1 to 4). The minimum ammonical content in leachate was observed in the treatment of 0% of the recommended dose of urea. Leaching of NH₄-N was very minimal after the 14th day. This could be due to the reason for NH₄-N fixation in the soil and conversion of NH₄-N into other forms of nitrogen. In the case of conventional urea, the leaching of NH₄-N was higher than that of nanofertilizer. Due to the high solubility and transformation of urea, higher leaching of NH₄-N in urea was observed. For different soil textures (light, medium, and heavy), the maximum ammonical content was present in light-textured soil, followed by medium and heavy-textured soil. The NH₄-N content also decreased with the increase in time interval (Table 1).

The nitrate content in leachate was maximum in treatment T1 (100% of the recommended dose of urea) and increased with the increase in time interval (first to fourth week). The minimum nitrate content was observed in treatment T7 (control). It was observed that nitrate in the leachate was maximum in conventional urea compared to the nano-urea formulation. The higher leaching of nitrate in conventional urea treatments can be attributed to the rapid release and transformation of the urea to ammonia. For different soil textures (light, medium, and heavy), the maximum nitrate content was present in leachate collected from the light-textured soil, followed by medium and heavy-textured soil samples. Furthermore, the nitrate content also increased with the increase in time interval (Table 1).

The dual interactions for soil type × fertilizer source revealed that nano-urea formulation could be useful for application in light and medium-textured soil types. At the same time, soil type × fertilizer level indicated that higher N-fertilizer levels will lead to increased NH₃-N and NO₃-N amounts in leachate. However, this effect varied among the soil types. The triple interaction indicated that the fertilizer source type and its application rate can significantly affect N-availability, though soil texture type can strongly modulate it. Therefore, tailoring of N-management strategies is critical and varied according to soil texture type and fertilizer source and its dosage to optimize N-availability in the soil. These results demonstrated the complex N-dynamics in relation to soil and type of N-fertilizer, emphasizing the need for targeted approach(es) for effective N-management and enhanced soil fertility and crop productivity.

3.1.2. Soil Enzyme Activities

The ANOVA results indicated a significant effect of all three factors of variation, i.e., soil texture, N-fertilizer types, and fertilizer application dose, and their dual and triple interactions on the soil enzymatic properties (

Table 2. Analysis of variance and mean effect of soil type and different doses of conventional and nano-urea fertilizers on soil enzyme activities.

Source	Dehydrogenase (µg TPF Formed g−1 Soil h−1)				Urease (µg Urea Hydrolyzed g−1 Soil h−1)			Protease (µmol Tyrosine Equiv. h−1)
	10th Day		20th Day	30th Day	10th Day	20th Day	30th Day	10th Day	20th Day	30th Day
N-fertilizer Source
Conv-urea	0.416 b		0.470 b	0.514 b	0.094 b	0.096 b	0.097 b	24.864 b	24.860 a	24.664 b
Nano-urea	0.448 a		0.499 a	0.564 a	0.095 a	0.097 a	0.097 a	25.342 a	24.870 a	25.313 a
LSD (p ≤ 0.05)	0.007		0.012	0.011	0.0001	0.0001	0.0001	0.3560	0.326	0.209
Soil Texture
Light	0.713 a		0.808 a	0.836 a	0.963 a	0.097 a	0.098 a	25.6706 a	24.9846 a	25.0651 a
Medium	0.318 b		0.3442 b	0.392 b	0.959 a	0.097 b	0.097 a	25.0526 b	24.8972 a	25.0223 a
Heavy	0.266 c		0.302 c	0.390 b	0.930 b	0.096 c	0.097 a	24.5867 b	24.7143 a	24.8799 a
LSD (p ≤ 0.05)	0.014		0.018	0.020	0.0005	0.0001	0.001	0.598	0.694	0.649
N-fertilizer Level (% RDF)
0	0.223 c		0.233 c	0.237 c	0.093 c	0.095 c	0.096 c	14.350 c	14.142 d	14.029 d
50	0.495 b		0.546 b	0.600 b	0.093 c	0.095 c	0.096 c	28.452 b	27.637 c	27.794 c
75	0.505 ab		0.577 a	0.660 a	0.094 b	0.096 b	0.096 b	28.537 ab	28.173 b	28.659 b
100	0.506 a		0.583 a	0.660 a	0.099 a	0.0997 a	0.101 a	29.074 a	29.510 a	29.474 a
LSD (p ≤ 0.05)	0.011		0.011	0.011	0.0004	0.0003	0.0004	0.554	0.415	0.416
ANOVA	D.f.
Soil type	2	1.431 ***	1.895 ***	1.587 ***	0.000 ***	0.000 ***	0.000 ***	7.095 **	0.4567 ns	0.226 ns
N-fertilizer Source	1	0.01897 ***	0.016 ***	0.0448 ***	0.000 ***	0.000 ns	0.000 ns	4.106 **	0.002 ns	7.5810 ***
N-fertilizer Level	3	0.350 ***	0.512 ***	0.745 ***	0.000 ***	0.000 ***	0.000 ***	926.391 ***	931.124 ***	969.480 ***
Soil type× N-fertilizer source×N-fertilizer level	6	0.0189 ***	0.032 ***	0.006 ***	0.000 ***	0.000 ns	0.000 **	0.734 ns	2.056 ***	0.655 ns

** = p ≤ 0.01, *** = p ≤ 0.001, ns = not significant. Mean values with different alphabetic scripting in a column depict statistical significant difference.

).

Soil Dehydrogenase Activity

The maximum dehydrogenase activity was recorded in light-textured soil in treatment which received 100% of the recommended dose of N-fertilizer after one month of incubation (Table 2). A significant increase in soil dehydrogenase activity was reported in light-textured soil as compared to medium and heavy-textured soils.

Soil Urease Activity

A significant increase in the soil urease activity was reported in light-textured soil compared to the medium and heavy-textured soil and exhibited an increased trend after the interval of every 10th day (Table 2). Therefore, the maximum urease enzyme activity was exhibited in light-textured soil in treatment, which received 100% of the recommended dose of N-fertilizer levels on the 30th day of the month.

Soil Protease Activity

The protease activity was maximum in light-textured soil for 100% of the RDF of N-fertilizer level on the 20th day, while the minimum protease activity was observed for the treatment that received no dose of N-fertilizer (Table 2).

The soil type × fertilizer source dual interaction revealed significant variation among light and medium textured soil types for soil dehydrogenase activity with higher values for nano-urea. The urease activity exhibited no significant variation among soil texture types. At the same time, the protease activity was higher for nano-urea, particularly in light-textured soil. The soil type × fertilizer dosage interaction indicated significantly higher activities of all the soil enzymes tested in light-textured soils. N-fertilizer source × dosage level indicated higher dehydrogenase and significantly higher protease activity for nano-urea at higher dosage (75% and 100% RDN) levels. Both fertilizer sources exhibited higher urease activity at higher dosage levels. The triple interaction indicated that soil type, N-fertilizer source, and dosage level significantly influenced the three test enzyme activities. Higher enzyme activities were recorded in light soil with a nano-urea application at higher dosage levels while lowest in heavy textured soil. These results demonstrated the importance of the interactive impact of the three factors for optimization of the soil enzyme activities for improved soil health as soil type limited the effectiveness of both fertilizer source type and dosage.

3.1.3. Culturable Soil Microbial Viable Cell Counts

The soil type and different treatments had significant effects on the total aerobic bacteria and interactions between soil type*N-fertilizer and source*N-fertilizer levels, except fungal and non-symbiotic nitrogen fixers, which were affected non-significantly for interactions between soil type*N-fertilizer and source*N-fertilizer levels. The effect of nano-urea fertilizer was studied on soil microflora viz., total aerobic bacteria, fungus, and non-symbiotic nitrogen fixers for different textured soil samples (light, medium, and heavy) at different N-fertilizer application levels (0, 50, 75, 100% of the RDF) at different intervals of time have been presented in

Table 3. Analysis of variance and mean effect of soil type and different doses of conventional and nano-urea fertilizers on viable cell counts (log CFU g⁻¹ soil) of different soil microbial groups.

Source		Aerobic Bacteria			Fungus			Non-Symbiotic Nitrogen Fixers
		10th Day	20th Day	30th Day	10th Day	20th Day	30th Day	10th Day	20th Day	30th Day
N-fertilizer Source
Conv-urea		6.755 a	6.634 a	6.624 a	4.218 a	4.076 a	3.952 a	4.521 b	4.541 a	4.504 a
Nano-urea		6.720 b	6.664 a	6.616 a	4.189 a	4.083 a	3.926 a	4.585 a	4.557 a	4.517 a
LSD (p ≤ 0.05)		0.017	0.041	0.030	0.043	0.120	0.098	0.035	0.038	0.035
Soil Type
Low		6.763 a	6.659 a	6.656 a	4.253 a	4.183 a	4.001 a	4.653 a	4.627 a	4.568 a
Medium		6.745 a	6.656 a	6.619 b	4.239 a	4.091 a	3.977 a	4.517 b	4.51 b	4.503 b
Heavy		6.704 b	6.633 a	6.584 c	4.118 b	3.964 b	3.838 a	4.488 b	4.507 b	4.461 b
LSD (p ≤ 0.05)		0.038	0.077	0.029	0.099	0.118	0.168	0.039	0.020	0.054
N-fertilizer level
0		6.683 b	6.614 b	6.590 c	4.169 a	3.980 c	3.872 b	4.456 b	4.405 b	4.422 b
50%		6.716 b	6.649 ab	6.602 cb	4.182 a	4.036 cb	3.937 ab	4.565 a	4.587 a	4.521 a
75%		6.769 a	6.656 a	6.635 ab	4.208 a	4.133 ab	3.957 ab	4.592 a	0.460 a	4.542 a
100%		6.781 a	6.678 a	6.652 a	4.256 a	4.169 a	3.990 a	4.597 a	4.602 a	4.557 a
LSD (p ≤ 0.05)		0.039	0.041	0.034	0.093	0.106	0.112	0.052	0.049	0.051
ANOVA analysis
Factor	D.f.
Soil type	2	0.021 **	0.005 ns	0.031 ***	0.132 **	0.290 ***	0.185 **	0.186 ***	0.111 ***	0.070 ***
N-fertilizer Source	1	0.022 **	0.016 *	0.001 *	0.016 ns	0.00 ns	0.011 ns	0.073 ***	0.005 ns	0.003 ns
N-fertilizer Level	3	0.037 ***	0.013 *	0.015 **	0.026 ns	0.136 **	0.045 ns	0.078 ***	0.165 ***	0.066 ***
Soil type× N-fertilizer source×N-fertilizer level	6	0.008 *	0.009 *	0.002 ns	0.071 ns	0.051 ns	0.015 ns	0.010 ns	0.006 ns	0.004 ns

* = p ≤ 0.05, ** = p ≤ 0.01, *** = p ≤ 0.001, ns = not significant. Mean values with different alphabetic scripting in a column depict statistically significant differences.

. The maximum bacterial and fungal viable cell counts were observed in light-textured soil, which received 100% of the RDF of N-fertilizer treatment on the 10th day of incubation (Table 3). Both the soil bacterial and fungal populations exhibited a decreasing trend with an increase in time interval. The application of different levels of N-fertilizer showed a positive impact on the viable cell counts of non-symbiotic N-fixer populations for different texture types of soil, with the maximum count recorded at 100% of the N-fertilizer levels on the 20th day of incubation (Table 3). Soil texture × fertilizer source interactions exhibited no significant effect on total aerobic bacterial count and fungi across all soil texture types, while non-symbiotic N-fixer populations improved for nano-urea fertilizer in low and medium-textured soils. Soil texture × fertilizer level interactions indicated a higher count for all three test microbes at higher fertilizer dosage levels across all soil texture types. Fertilizer source × fertilizer dosage level indicated nano-urea to exhibit higher bacterial counts at higher fertilizer levels, fungal count remaining at par for sources, and N-fixer counts increased with an increase in fertilizer dosage. The combined impact of triple interactions showcased that microbial counts are critically affected by soil texture, with enhanced counts in low and medium-textured soil types. Meanwhile, the highest dosage of 100% RDN improved the microbial counts for both fertilizer sources.

3.2. Field Studies

3.2.1. Vegetative Parameters

Various N-fertilizer treatments and days after sowing significantly affected the plant height of rice variety PR-126, while a non-significant effect was recorded for the DAS and treatment interaction (

Table 4. Analysis of variance and mean effect of different doses of conventional and nano-urea fertilizers and various days after transplantation on plant vegetative and photosynthetic pigment parameters.

Source		Plant Height (cm)	Root		Shoot		Total Chlorophyll content (mg g−1 Fresh Leaf Tissue)	Total Carotenoids (mg g−1 Fresh Leaf Tissue)	Total Anthocyanins (mg g−1 Fresh Leaf Tissue)
			Fresh Weight (g Plant−1)	Dry Weight (g Plant−1)	Fresh Weight (g Plant−1)	Dry Weight (g Plant−1)
Treatment
T1 (100% RDF CU)		67.800 a	5.006 ab	1.283 ab	13.754 a	5.446 a	14.087 a	270.22 a	0.245 ab
T2 (100%RDF NU)		68.989 a	5.293 a	1.141 ab	14.089 a	5.505 a	15.879 a	273.53 a	0.256 a
T3 (75%RDF CU)		67.248 a	3.962 cdb	2.574 a	11.492 a	4.761 a	13.174 ab	257.76 a	0.212 ab
T4 (75% RDF NU)		67.456 a	4.620 cab	1.121 ab	12.910 a	4.763 a	13.161 ab	259.72 a	0.215 ab
T5 (50% RDF CU)		66.226 a	3.616 cd	0.988 b	10.550 a	4.223 a	10.639 cb	244.13 ab	0.201 ab
T6 (50% RDF NU)		66.256 a	3.885 cdb	0.941 b	11.647 a	4.614 a	13.049 ab	245.93 ab	0.205 ab
T7 (Control)		61.756 b	3.217 d	1.564 ab	10.419 a	3.877 a	8.573 c	190.96 b	0.194 b
LSD (p ≤ 0.05)		3.4048	1.283	1.531	4.707	1.900	3.318	55.995	0.0587
DAS
30		46.129 c	2.350 c	0.592 b	5.255 b	1.476 b	17.073 a	359.60 a	0.199 b
60		69.184 b	3.926 b	1.259 b	14.641 a	6.086 a	14.520 b	271.58 b	0.342 a
90		84.286 a	6.410 a	2.268 a	16.473 a	6.662 a	6.361 c	115.49 c	0.114 c
LSD (p ≤ 0.05)		2.372	1.087	0.767	2.993	1.361	1.580	34.561	0.036
ANOVA analysis
Source	D.f
Treatment	6	47.991 **	19.723 ns	3.168 ns	5.215 ns	2.909 ns	50.773 ***	6967.372 ns	0.005 ns
DAS	2	7754.526 ***	760.600 ***	169.682 ***	87.966 ***	14.948 ***	657.330 ***	320,954.751 ***	0.280 ***
Trt×DAS	12	13.301 ns	23.580 ns	4.993 ns	2.614 ns	2.915 ns	7.374 ns	1384.680 ns	0.007 ns

** = p ≤ 0.01, *** = p ≤ 0.001, ns = not significant. Mean values with different alphabetic scripting in a column depict statistically significant differences.

). The maximum plant height was recorded when nano-urea was applied at 100% of the RDF, followed by nano-urea at 75% of the RDF (Table 4). The fresh and dry weight of shoots and roots were significantly affected by the factor DAS (Table 3). The mean root fresh and dry weight was highest for T2 treatment.

Photosynthetic Parameters

The analysis of variance for the total chlorophyll content depicted that the factor treatment and DAS had a significant effect on total chlorophyll content. However, the interaction effect of both treatment and DAS had no significant effect on the total chlorophyll content of rice variety PR-126. The treatment and interaction between treatment and DAS had a non-significant impact on the total carotenoid and anthocyanin content. At the same time, DAS alone exhibited a significant effect on the total carotenoids and anthocyanin content (Table 4). The mean effect for various photosynthetic parameters showed maximum total chlorophyll content, total carotenoid, and total anthocyanin content in treatment T2 as compared to other treatments. For DAS, total chlorophyll content and total carotenoids were maximum at 30 DAS, and anthocyanin content was maximum at 60 DAS. The chlorophyll content, as represented through the SPAD readings at the 50% flowering stage, was maximum in treatment T1 (Supplementary Table S3).

3.2.2. Yield Parameters

Maximum tiller length and number of filled grains were exhibited in treatment T2 (

Table 5. Effect of different doses of conventional and nano-urea fertilizer on yield attributes and yield of rice cv PR-126.

Source	Tiller Length (cm Per m−2)	Day at 50%FLOWERING	Panicle Weight (g per Plant)	No. of Filled Grain Per Panicle	No. of Unfilled Grains Per Panicle	Weight-Filled Grains Per Panicle (g)	Grain Yield (q ha−1)	Straw Yield (q ha−1)
T1 (100% RDF CU)	337.50 a	81.66 b	2.58 a	126.9 ab	18.06 cb	2.49 ab	68.53 a	87.67 a
T2 (100%RDF NU)	360.83 a	81.33 b	2.90 a	141.2 a	15.00 c	2.80 a	70.47 a	88.00 a
T3 (75%RDF CU)	326.66 a	81.66 b	2.47 a	104.5 b	16.86 c	2.33 b	67.07 a	85.27 a
T4 (75% RDF NU)	353.33 a	81.00 b	2.57 a	130.5 ab	15.60 c	2.36 ab	68.52 a	87.33 a
T5 (50% RDF CU)	326.66 a	81.33 b	2.15 a	111.1 ab	24.86 ab	1.91 ab	62.53 a	85.66 a
T6 (50% RDF NU)	335.83 a	81.33 b	2.21 a	115.0 ab	21.06 cab	2.13 ab	65.20 a	85.67 a
T7 (Control)	302.50 b	83.66 a	1.87 a	90.6 b	28.13 a	1.71 b	49.87 b	68.93 b
LSD (p ≤ 0.05)	62.45	5.452	0.87	32.0	7.97	0.798	9.33	5.61

Values in columns having differences in the alphabetic superscripting vary significantly.

). There was no significant effect of nano-urea treatment on the weight of the panicle. At the same time, the opposite effect was recorded for the number of unfilled grains that were maximum in the treatment that received no application of N-fertilizer, i.e., T7 (Control).

There was no significant effect exhibited by the N-fertilizer treatments for days to the 50% flowering trait. However, treatment T7 (control) exhibited the maximum days to 50% flowering while it was the minimum in treatment T2 (Table 5). Nano-urea fertilizer had a significant effect on the grain yield and straw yield compared to the conventional neem-coated urea. Maximum grain yield (Figure 1) and straw yield were recorded in treatment T2 (Table 5). The treatment × DAS interactions were non-significant, advocating that the treatments did not lose their effectiveness or did not fluctuate over the time duration. Nano-urea at 100% of the RDN exhibited the highest values for all the parameters studied. The DAS significantly affected all measured parameters. The thousand-grain weight was numerically improved by the application of nano-urea at 100% of the RDN (Supplementary Figure S2).

3.2.3. Plant Nutrient Parameters

All the factors, such as treatment, DAS, and the interaction between treatments*DAS, exhibited significant effects on the N, P, and K content of the rice var. PR-126. Root N and shoot N, P, and K exhibited a time-dependent increase with maximum values at 90 DAS.

Root P and K and soil N, P, and K contents were maximum at 30 DAT. Among the nitrogen treatments, all three macronutrients except root P were significantly highest in treatment T2 (

Table 6. Mean effect and analysis of different treatment modalities, days after sowing (DAS), and treatment * DAS for microbial count (log CFU g⁻¹).

Source		Total Aerobic Bacteria	Fungi	Phosphate Solubilizing Bacteria	Non-Symbiotic N Fixers	Symbiotic N Fixers	Actinobacteria	Ammonia Oxidizers	Nitrate Reducing Bacteria
Treatment
T1 (100% RDF CU)		6.761 a	4.033 a	4.583 ab	4.516 a	4.466 b	4.554 a	4.440 cb	4.709 ab
T2 (100%RDF NU)		6.802 a	4.161 a	4.681 a	4.562 a	4.588 a	4.683 a	4.569 a	4.739 a
T3 (75%RDF CU)		6.726 a	4.099 a	4.552 ab	4.486 a	4.496 ab	4.657 a	4.454 cab	4.641 cab
T4 (75% RDF NU)		6.898 a	4.100 a	4.660 ab	4.541 a	4.588 a	4.670 a	4.447 cab	4.652 cab
T5 (50% RDF CU)		6.727 a	4.059 a	4.505 ab	4.492 a	4.515 ab	4.519 a	4.306 c	4.618 cb
T6 (50% RDF NU)		6.740 a	4.059 a	4.589 ab	4.520 a	4.541 ab	4.651 a	4.372 cb	4.637 cab
T7 (Control)		6.633 a	3.998 a	4.470 b	4.524 a	4.518 ab	4.495 a	4.460 ab	4.540 c
LSD (p ≤ 0.05)		0.228	0.262	0.200	0.178	0.121	0.236	0.149	0.115
DAS
30		6.729 a	4.22 a	4.577 ab	4.504 a	4.632 a	4.687 a	4.406 b	4.710 a
60		6.727 a	4.126 a	4.511 b	4.557 a	4.467 b	4.698 a	4.317 b	4.537 b
90		6.763 a	3.866 b	4.639 a	4.499 a	4.454 b	4.427 b	4.583 a	4.697 a
LSD (p ≤ 0.05)		0.115	00.117	0.124	0.138	0.104	0.123	0.106	0.113
ANOVA analysis
Source	D.F.
Treatment	6	0.027 ns	0.025 ns	0.053 ns	0.006 ns	0.013 ns	0.056 ns	0.059 ns	0.037 ns
DAS	2	0.008 ns	0.723 ***	0.086 ns	0.022 ns	0.205 **	0.497 ***	0.384 ***	0.195 **
Trt × DAS	12	0.045 ns	0.070 ns	0.036 ns	0.037 ns	0.026 ns	0.066 ns	0.027 ns	0.033 ns

** = p ≤ 0.01, *** = p ≤ 0.001, ns = not significant. Mean values with different alphabetic scripting in a column depict statistically significant differences.

).

3.2.4. Grain Macro-Nutrient Content

The grain nitrogen, phosphorus, and potassium content were recorded to be significantly highest in treatment T2 (100% of the RDN of N through nano-urea, Figure 1). However, the remaining treatments exhibited at par grain macro-nutrient content with the lowest exhibited by the treatment T7.

3.2.5. Soil Microbial Count

The application of different N-fertilizer levels non-significantly affected the culturable bacterial, actinobacterial, non-symbiotic N-fixer, and fungal population (Table 6, Supplementary Figure S3). The maximum viable cell counts of these groups of microorganisms were recorded in treatment T2 (100% of the recommended dose of N through nano-urea) at 30 DAS (Table 6). However, the maximum phosphate solubilizer counts were recorded in treatment T2 (100% of the recommended dose of N through nano-urea) at 90 DAS (Table 6). The symbiotic N-fixer population was recorded to be maximum in two treatments, which received nano-urea at application rates of 100 and 75% of the RDN 30 days after the sowing of the crop. The ammonia oxidizer viable cell counts peaked for treatment T2 at 90 DAS. The nitrate reducers were recorded to be present in the highest number in treatment T2 at 30 DAS, followed by a significant decrease at 60 DAS. However, later, the population resumed and was statistically at par with the 30 DAS counts (Table 6).

4. Discussion

Nitrogenous fertilizers have been an integral component of the customized slow- or controlled-release and site-specific nutrient-management strategies [39]. Nano-scale nitrogen fertilizers encompass a variety of fertilizer formulations that involve adsorption, encapsulation, and embedding of the N-nutrient with a suitable organic/inorganic matrix [15,40]. In the present investigation, a calcium phosphate-based inorganic matrix was utilized to adsorb urea molecules and prepare the nano-scale fertilizer [20]. On evaluation of the prepared nano-urea fertilizer in a soil column experiment, a decrease in the leaching of the urea was recorded as compared to the use of the conventional neem-coated urea fertilizer (Table 1). Due to the high solubility and transformation of urea, higher leaching of NH₄-N and nitrate in conventional urea treatments can be attributed to the rapid release and transformation of the urea to ammonia [23,41]. The soil enzymatic activities of viz., dehydrogenase, urease, and protease were recorded to be improved by soil application of the nano-urea formulation. These results could be corroborated through the earlier reports on the use of nano-hydroxyapatite as a P-fertilizer [42] and elicitor of microbial viable cell counts [17]. The microbial viable cell counts, particularly of the non-symbiotic nitrogen fixers, were positively affected in a statistically significant manner by the application of the nano-urea fertilizer. The microbial counts of the low-textured soil were most effectively improved, followed by medium and heavy-textured soils.

This field study revealed a numerical improvement in the plant height on nano-urea fertilizer soil application, which may be due to the effective release of N-nutrients from the nano-urea fertilizer, thereby positively regulating plant development and enhancing target activity [43]. An increasing trend was observed for the fresh and dry weight of roots with respect to the days after sowing, i.e., as the days advanced, the fresh and dry weight of roots increased. The highest dry matter yield of the rice root was also recorded in response to the application of the nano-zeolite adsorbed fertilizer formulation [44]. This improvement may be attributed to the availability of the nitrogen element in its available form near the root zone from the nano-calcium phosphate templates for a longer period compared to the conventional urea fertilizer. As a result, the plant’s nutrient use efficiency improved, leading to increased dry matter production. A similar increasing trend was observed for the fresh and dry weight of shoots with respect to the days after sowing, i.e., as the days advanced, the shoot fresh and dry weight increased [44]. Furthermore, nitrogen, being the integral component of the chlorophyll heterocyclic porphyrin ring, the nano-urea must have increased the formation of the chlorophyll molecules. As given in the Section 3, the photosynthetic pigments, including total chlorophyll, carotenoids, and anthocyanins, were improved by nano-urea application at 100% of the RDN. A likewise improvement in the total chlorophyll content in the finger millet has been recorded by foliar application of urea-doped calcium phosphate nanoparticles in a pot study [45]. The pigment improvement was also reflected in the SPAD values of the crop at the 50% flowering stage. A similar effect on the SPAD values among the treatments was reported for urea-doped calcium phosphate nanoparticles in grapevines [46]. Furthermore, the rate of photosynthesis must have resulted as a consequence of the formation of a greater number of leaves [47].

This field study also indicated increasing trends for tiller numbers as a result of increased nitrogen rates. This may have occurred due to the improved efficiency of the nano-urea fertilizer, ensuring the release of the adsorbed urea for a longer period and minimizing the non-target losses. Consequently, it created additional opportunities for the fertilizer to interact with the plants, leading to enhanced nitrogen nutrient uptake. This, in turn, resulted in a higher number of tillers. A nitrogen fertilizer dose-dependent positive effect on the tiller number in rice crops has already been reported [48]. The number of effective tillers produced is a good indicator as it is the major yield determinant [49]. Though the effective tillers were not significantly affected, the panicle weight was observed to be maximum in nano-urea treatment. This effect may be due to the continuous supply of available nitrogen, which led to an increase in cell elongation, activity of meristematic cells, and also increased grain formation, due to which panicle weight increases [50]. The number of filled grains panicle⁻¹ also increased. It might be attributed to an increase in enzyme activity, which could result in the creation and transportation of photosynthates, and then cause the number of grains per panicle to increase [51]. The increase in thousand-grain yield was higher under the nano-urea treatment because the slow and sustained release of urea from the nano-urea formulation made N available to the growing crop, accelerating its vegetative growth and improving the yield attributing traits [20]. Nano-urea fertilizer had a significant effect on the grain yield compared to the neem-coated urea because the former improved the growth and metabolic processes, such as photosynthesis in plants. This led to higher photosynthate accumulation and translocation to the economically important parts (grain or seed) of the plant [20,52]. Increased straw yield with nano-urea fertilizer might be due to the quick absorption of the nanofertilizer by the plant and easiness of translocation, which aided in better rates of photosynthesis and more dry matter accumulation, resulting in higher straw yield [52,53].

The nutrient uptake in rice was found to be increased with the application of nano-urea, which might be attributed to improved root biomass and available nitrogen in the rhizosphere [54]. Furthermore, the generation of improved sink capacity due to the positive correlation between the yield and dry matter accumulation led to enhanced nutrient acquisition or uptake by the rice crop [55].

The soil microbial viable cell counts indicated a positive elicitation in response to the application of the nano-urea fertilizer. The improved counts of phosphate-solubilizing, nitrogen-fixing, ammonia-oxidizing, and nitrate-reducing bacteria in nano-urea treatments earmarked the crucial role of microflora involvement in P and N transformation. Increased availability of N, P, and K is preferentially assimilated by microorganisms [56]. Though these nutrients exist in limited availability in the soil, a differential temporal niche is established among the plant roots and rhizosphere microflora, yielding a profound mutualistic relationship enabling the improved availability of the nutrients in the rhizosphere and prevention of leaching of the nutrients during negligible or low uptake by the root system [57]. The microbial biomass, as indicated through the increased viable cell counts, presented a positive effect of soil application of nano-urea fertilizer. Furthermore, the improved plant and microbial cell count results indicated the ecological safety of the developed nano-urea fertilizer as well as being a potential nanoscale nutrient delivery vehicle for urea fertilizer.

5. Conclusions

The developed nano-urea fertilizer was evaluated through soil column study. The leachate sample results indicated that the nano-urea application exhibited NH₄-N in the first two weeks, followed by NO₃-N contents. The light-textured soil exhibited higher NH₄-N and NO₃-N contents in comparison to medium and heavy-textured soil samples. Besides the soil N-content, the soil microbial counts and enzyme activities were also maximum in light-textured soils. This field study revealed that on soil application, the vegetative growth and yield-attributing traits of rice crop were improved, as well as the plant and soil N, P, and K contents were enhanced. An increase in the plant height and fresh weight, and dry weight of shoots and roots was recorded when N-fertilizer was applied as nano-urea. These parameters were maximum in 100% of the recommended dose of N through the nano-urea treatment. The photosynthetic pigments exhibited a significant increase in application of 100% of the recommended dose of N through nano-urea compared to conventional urea. An increase in all the soil chemical parameters was observed in treatments when the recommended dose of N was applied through the nano-urea fertilizer formulation. These results establish the potential use of the developed nano-urea formulation for improving the growth and yield in direct-seeded rice.