Hydraulic Performance and Mitigation of Biofouling in Drippers Applying Aquaculture Effluent with Anti-Clogging Fertilizer

Abstract

Water scarcity in Brazil’s semi-arid region necessitates the agricultural reuse of aquaculture effluents, although emitter clogging remains a challenge. This study evaluated clogging mitigation in drip irrigation systems using liquid anti-clogging fertilizer. The experiment employed a split–split–plot scheme with three water treatments (supply water, aquaculture effluent, and effluent with liquid fertilizer) and three emitter types (ST, SL, and GA), assessing performance over 360 h. A water quality analysis at 0, 160, and 360 h complemented hydraulic evaluations of the average flow rate variation and Christiansen uniformity coefficient measured every 40 h. Energy-dispersive X-ray spectroscopy, X-ray diffractometry, and scanning electron microscopy were used to characterize biofouling. The results showed that the liquid fertilizer mitigated the clogging by biofouling in the three types of emitters, but only the ST emitter presented acceptable hydraulic performance rates. There are relationships between the anti-clogging effect of the liquid fertilizer, the structural characteristics of the emitters, and the flow velocity inside the labyrinths. The SL dripper applying only aquaculture effluent presented the highest clogging rate due to biofouling. Agricultural reuse is a strategy for the rational use of water resources that is of great relevance for arid and semi-arid regions and can insert aquaculture into the circular economy.

1. Introduction

Freshwater scarcity is driven by multiple factors, including population growth, urbanization, increasing per capita consumption, water pollution, and climate change [1]. Climate change has been particularly detrimental to water availability in semi-arid regions, exacerbating existing scarcity challenges [2]. As agricultural water use remains essential for global food security [3], the sector faces mounting pressures from both extreme weather events and human activities [4].

Among food production systems, aquaculture has emerged as a vital component of the global food supply. The cultivation of fish and crustaceans represents one of the fastest-growing food production sectors worldwide [5] and a dynamic element of modern food systems [6]. However, this rapid expansion generates substantial volumes of wastewater containing metabolic byproducts, organic waste, undigested feed, and nitrogenous compounds that undergo microbial conversion from ammonia to nitrite and nitrate [7]. Without proper treatment, these effluents can lead to significant environmental impacts, including organic pollution, eutrophication, and chemical contamination [8].

Paradoxically, aquaculture wastewater contains valuable nutrients that could benefit agricultural irrigation while addressing water scarcity [9]. This potential aligns with the United Nations Sustainable Development Goal 6 (Clean Water and Sanitation)—specifically Target 6.3, which promotes the treatment and reuse of wastewater [10,11]. High-efficiency irrigation systems offer a promising solution for utilizing these alternative water sources while reducing the demand for fresh water [1].

Drip irrigation systems provide multiple advantages for water-scarce regions, including improved crop productivity, reduced soil salinity in root zones, decreased weed pressure, and superior water-use efficiency, particularly in arid climates [12]. However, their effectiveness is frequently compromised by emitter clogging [13], which can become particularly severe when using aquaculture effluents [14,15,16]. Emitter performance is crucial for system longevity and irrigation efficiency, requiring effective prevention of particle-induced blockages [17].

Dripper clogging is the main barrier that restricts the application and promotion of drip irrigation, caused by two factors that participate in this process: (1) the internal architecture of the drippers, and (2) the quality of the irrigation water endowed with physical, chemical, and biological agents [13,17]. On the other hand, Li et al. [18] reported that emitter clogging actually does not manifest separately as physical, chemical, and biological clogging; rather, these clogging agents generally interact and couple as composite clogging.

Understanding the clogging mechanism is a key factor in finding mitigating solutions. Thus, in the work of Li et al. [18], the following findings were obtained regarding the clogging mechanism: The average transverse velocity, influenced by geometric parameters of the emitters, directly affects the formation and accumulation of all clogging agents. The same authors also reported that all components of the clogging substances—solid particles, and CaCO₃ and MgCO₃ precipitates—directly affected the emitter-clogging process, while phospholipid fatty acids (PLFAs) and extracellular polymeric substances (EPSs) depended mainly on indirect impacts.

Completing the clogging mechanisms, the study by Muhammad et al. [19] presents the dynamics of chemical clogging of emitters, where system performance indices were closely related to chemical precipitations inside the emitters, and especially to the relative contents of and variations in primary components such as carbonates, quartz, and silicates.

Current approaches to address clogging include physical methods (e.g., system flushing, filtration, and advanced water treatment technologies), chemical treatments (e.g., specialized fertilizers and nanoparticles), and biological solutions using specific bacterial strains [20]. Recent evidence suggests that ammonium polyphosphate and new urea phosphate reduce CaCO₃ formation in emitters and act as anti-clogging fertilizers [21,22]. According to Ramachandrula and Kasa [20], fertigation with urea phosphate in low concentrations for longer periods reduced the pH of the irrigation water and contributed to the removal of chemical precipitates in the lateral lines and emitters, functioning as a type of anti-clogging fertilizer.

Therefore, an in situ experiment in open-air experimental benches was conducted to (1) verify the clogging mitigation capacity with liquid anti-clogging fertilizer in drippers operating with aquaculture effluent; (2) monitor and classify the hydraulic performance indices (average flow rate variation and Christiansen uniformity coefficient) over 360 h of operation; (3) characterize and classify the physical, chemical, and microbiological agents that cause dripper clogging in water sources; and (4) characterize the biofouling formed in emitters applying aquaculture effluent, with and without liquid anti-clogging fertilizer, using energy-dispersive X-ray spectroscopy, X-ray diffractometry, and scanning electron microscopy. Thus, the present work proposes the following hypothesis: the use of liquid fertilizer, based on nitrogen, phosphorus, and total organic carbon, exerts an anti-biofouling effect on drippers that apply aquaculture effluent under the conditions of experimental benches set up in the Brazilian semi-arid region.

2. Materials and Methods

The experiment was conducted from August to October 2023 in the outdoor area of the Rural Construction and Ambience Laboratory at the Federal Rural University of the Semi-Arid (UFERSA), located in Mossoró, Rio Grande do Norte, Brazil (5°12′13.14″ S, 37°19′26.93″ W).

For the experimental trials, we used (1) aquaculture effluent from a 92 m³ storage tank at UFERSA’s Aquaculture Sector, and (2) supply water from the Rio Grande do Norte Water and Sewage Company network, sourced from individual use or the mixture of groundwater from deep wells in the municipality of Mossoró-RN and surface water from the Armando Ribeiro Gonçalves Dam in the municipality of Açu-RN.

Three experimental benches were set up for the trials. Each bench occupied a surface area of 8 m² (1 m width × 8 m length), featuring a base constructed with reinforced concrete pillars and a wooden framework supporting corrugated fiber–cement roofing sheets with a 2.5% slope. This design enabled gravity-driven water flow and recirculation through the benches.

Downstream of each bench, we installed a 0.31 m³ reservoir and a drip irrigation system consisting of a 0.5 hp motor pump, 130 µm disk filter, gate valve, sampling port, service pressure gauges, a 32 mm main line, a 50 mm distribution line, nine rubber-sealed connectors, and nine 8 m lateral lines each equipped with an end cap (Figure 1).

The lateral lines were installed on the experimental benches, each measuring 8 m in length and equipped with three types of emitters: two non-pressure-compensating models (ST and SL) and one pressure-compensating model (GA), as commonly used in irrigation systems throughout the semi-arid region of Rio Grande do Norte (

Table 1. Technical specifications of the three tested emitter types (non-pressure-compensating and pressure-compensating) in the experimental bench trials.

Parameters	ST1	SL1	GA2
NF (L h−1)	1.6	1.6	4.0
K	0.567	0.568	4
X	0.45	0.45	0
FA (mm2)	24	15	2
ES (m)	0.3	0.3	0.3
Dim (mm)	0.66 × 0.63 × 18	0.65 × 0.55 × 13	1.32 × 0.92 × 35
MRF μm/Mesh)	200/80	130/120	130/120

Notes: ST¹ and SL¹—non-pressure-compensating flat emitters; GA²—pressure-compensating cylindrical button-type emitter; NF—nominal flow rate at 100 kPa; K—flow coefficient; X—flow exponent; FA—filtration area; ES—emitter spacing; Dim—dimensions of the water passage dimensions (width × depth × length); MRF—manufacturer-recommended filtration.

). Each bench contained nine lateral lines, with three lines of each emitter type.

In the experimental trials, the first bench received AB, the second received EB, and the third received ET. For the daily supply of aquaculture effluent to two of the three experimental benches, weekly transport of 1 m³ of this effluent was conducted using a 1 m³ plastic reservoir from UFERSA’s Aquaculture Sector to the experimental area. The 0.31 m³ reservoirs of the EB and ET benches were replenished daily through manual addition using 12 L buckets. Additionally, the ET bench received a daily dosage of 20 mL of liquid anti-clogging fertilizer per 300 L of aquaculture effluent to prevent emitter clogging. The anti-clogging liquid fertilizer should be applied at a dosage of 50 to 100 mL per 1000 L of solution, and in the present study, a dosage of 20 mL per 300 L was used, equivalent to 67 mL per 1000 L of solution. The product contained nitrogen (13%), phosphorus (6% P₂O₅), and total organic carbon (8%).

The reservoirs of all three benches were refilled daily, without allowing complete drying. For the bench supplied with AB, daily replenishment was performed using a hose connected to a water source near the experimental area. All three benches operated for six hours daily until completing 360 h of total operation time to induce the emitter-clogging process—equivalent to 60 consecutive days of drip irrigation system operation with the three water qualities. In the Brazilian semi-arid region, 360 h of operation of a drip irrigation system is equivalent to approximately two melon crop cycles, at which point the lateral lines are replaced due to obstruction of the emitters. Therefore, the proposal of anti-clogging measures is of great relevance for the Brazilian semi-arid region in order to extend the useful life of the drip tapes, reduce costs, and reduce the plastic footprint in agroecosystems. For this reason, the time period of 360 h was adopted in this study. It should be noted that the service pressure after the filtration system was maintained at 80 ± 10 kPa at the lateral line inlet. According to Batista et al. [23], this service pressure value enhances the emitter-clogging process. Periodic monitoring of the service pressure in the drip units was performed using graduated pressure gauges ranging from 0 to 400 kPa, with an accuracy class of ±1% of full scale.

To analyze emitter clogging with the three water types (AB, EB, and ET), 16 emitters per lateral line were randomly marked for flow measurement, adapting the methodology of Keller and Karmeli [24]. The emitter flow rates were measured every 40 h using collection containers, 100 mL graduated cylinders, and a digital stopwatch to control a 3 min measurement period. Using the emitter flow rate values, the clogging levels were determined throughout the operational time through the average flow rate variation (AFRV) [25] and the Christiansen uniformity coefficient (CUC) [26], as presented in Equations (1)–(3).

$$\mathrm{A}\mathrm{F}\mathrm{R}\mathrm{V}=100·{\displaystyle \frac{{\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{q}}_{\mathrm{i}}}{\mathrm{n}·{\mathrm{q}}_{0\mathrm{h}}}}$$

(1)

where

• AFRV—average flow rate variation (%);
• q_i—discharge of the ith loop (L h⁻¹);
• i—number of loops;
• q_0h—loop discharge at 0 h (L h⁻¹);
• n—total number of loops.

For the classification of the emitter AFRV values, we used the criteria proposed by Pei et al. [27]: AFRV ≥ 95% for non-clogged condition (NC), 80% ≤ AFRV < 95% for slight clogging (SLC), 50% ≤ AFRV < 80% for partial clogging (PC), 25% ≤ AFRV < 50% for severe clogging (SVC), and AFRV < 25% for complete clogging (CC).

$$\overline{\mathrm{q}}={\displaystyle \frac{{\sum }_{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{q}}_{\mathrm{i}}}{\mathrm{n}}}$$

(2)

$$\mathrm{C}\mathrm{U}\mathrm{C}=100·\left[1-{\displaystyle \frac{\sum _{\mathrm{i}=1}^{\mathrm{n}}\left|{\mathrm{q}}_{\mathrm{i}}-\overline{\mathrm{q}}\right|}{\sum _{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{q}}_{\mathrm{i}}}}\right]$$

(3)

where

• CUC—Christiansen uniformity coefficient (%);
• q_i—discharge of ith loop (L h⁻¹);
• i—number of loops;
• $\overline{\mathrm{q}}$—average loop discharge (L h⁻¹);
• n—total number of loops.

The classification of CUC values followed the criteria established by Merriam and Keller [28], where CUC > 90% was classified as excellent (E), 80% ≤ CUC ≤ 90% as good (G), 70% ≤ CUC < 80% as regular (R), and CUC < 70% as worst (W). The experiment was arranged in a completely randomized design (CRD) using a split–split–plot scheme with three replications. The main plots consisted of the three water treatments: municipal supply water (AB), aquaculture effluent (EB), and aquaculture effluent with a daily addition of 20 mL of liquid anti-clogging fertilizer per 300 L of effluent (ET), following the manufacturer’s anti-clogging recommendations. Split plots contained the emitter types (ST-1.6 L h⁻¹, SL-1.6 L h⁻¹, and GA-4.0 L h⁻¹), while split–split plots represented the evaluation times during the 360 h of operation (0, 40, 80, 120, 160, 200, 240, 280, 320, and 360 h). Water samples were collected downstream of the filtration system at 0, 160, and 360 h to monitor variations in physicochemical parameters and predict the risk of clogging. Physicochemical samples were stored in 1 L polyethylene bottles, while microbiological samples were stored in sterile glass bottles, with all samples preserved at 4 °C during transport to UFERSA laboratories, following the Standard Methods for the Examination of Water and Wastewater [28].

Physicochemical analyses were performed at UFERSA’s Soil, Water, and Plant Analysis Laboratory (LASAP), including pH (electrometric method); electrical conductivity (conductimetry); Na⁺ and K⁺ (flame photometry); Ca²⁺, Mg²⁺, HCO₃⁻, and Cl⁻ (titrimetry); hardness (calculated from Ca²⁺+Mg²⁺ concentrations); total suspended solids (gravimetry); and Fe and Mn (atomic absorption spectrometry). Microbiological analyses conducted at UFERSA’s Environmental Biotechnology and Microbiology Laboratory (LABIOMA) quantified the total heterotrophic bacteria using the pour plate method, following standard methods [29].

Only at the end of the experiment (360 h) were clogging material samples collected from the nine emitters (three per bench—AB, EB, and ET; one per model—ST, SL, and GA) and stored in sterilized 60 mL vials for analysis at UFRN’s Materials Engineering Department’s Structural Characterization Laboratory. The drippers were collected in the final third of the lateral lines, where the incidence of the highest number of clogged drippers was detected. In preparing the samples for XRD analysis, they were scraped inside the emitter labyrinth, and after drying in a desiccator, maceration was performed using a porcelain melting crucible and by sieving. Meanwhile, in preparing the samples for SEM, samples were collected from the labyrinths of the three types of drippers at the end of the experiment (360 h) and dried in a desiccator, taking maximum care to preserve the sample structure.

The clogging material was analyzed using X-ray diffraction (XRD) with a Shimadzu XRD-7000 with CuKα radiation, λ = 1.5406 Å, 40 kV/30 mA, 5–80° 2θ range, 0.02° step, and 1 °/min scan speed (Austin, TX, USA), with phase identification through the Crystallography Open Database. Scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS) was performed using a ZEISS FIB-SEM AURIGA 40 system operating at 2.0 kV with SemAfore 5.21 imaging. Particulate matter was mounted on carbon-tape-covered metal stubs, sputtered with gold, and then analyzed for surface elemental composition at 30× and 100× magnifications. The EDS provided semi-quantitative surface elemental estimates requiring XRD validation for comprehensive phase identification. The data from the hydraulic performance indices were used to create graphs relating the AFRV and CUC as a function of the operating time, which presented the average of the indices per time and the respective standard error (n = 3). In addition, the hydraulic performance indices (AFRV and CUC) were statistically analyzed using ANOVA (F-test, p ≤ 0.05), with Tukey’s mean comparison test (p ≤ 0.05) for significant differences.

3. Results

3.1. Analysis of the Quality of Water Used in Experimental Tests

Table 2. Physicochemical and microbiological characterization of waters used to supply drip irrigation units, and classification of emitter clogging risk based on water quality.

Attributes	0 h			160 h			360 h
	AB	EB	ET	AB	EB	ET	AB	EB	ET
pH (1)	8.53 (H)	7.77 (M)	7.70 (M)	7.50 (M)	7.70 (M)	8.40 (H)	7.70 (M)	8.10 (H)	8.50 (H)
EC (mS cm−1) (2)	0.53 (L)	4.97 (H)	5.00 (H)	0.68 (L)	8.45 (H)	9.28 (H)	0.69 (L)	8.21 (H)	11.85 (H)
Na+ (mg L−1)	82.53	636.82	656.59	90.35	2999.3	2801.1	100.35	828.79	1139.15
Ca2+ (mg L−1) (2)	8.42 (L)	527.05 (H)	513.02 (H)	24.25 (L)	1014.42 (H)	952.90 (H)	13.43 (L)	551.10 (H)	928.85 (H)
Mg2+ (mg L−1) (2)	2.31 (L)	152.00 (H)	148.35 (H)	1.09 (L)	154.43 (H)	293.18 (H)	3.77 (L)	498.32 (H)	647.52 (H)
K+ (mg L−1)	7.82	44.18	44.18	9.77	95.80	84.46	13.69	73.51	105.18
HCO3− (mg L−1)	162.31	375.27 (H)	349.03 (H)	198.32	198.32	381.38 (H)	148.28	219.06	443.62 (H)
Cl− (mg L−1)	84.84	1237.25	1201.9	141.4	1908.9	2403.8	98.98	318.15	452.48
HA (mg L−1) (3)	30.5 (L)	1940.0 (H)	1890.0 (H)	65.0 (L)	3166.0 (H)	3583.0 (H)	115.0 (L)	744.5 (H)	962.0 (H)
TSS (mg L−1) (1)	0.0 (L)	6.5 (L)	12.5 (L)	0.0 (L)	9.5 (L)	16.5 (L)	6.0 (L)	13.5 (L)	25.5 (L)
Fe (mg L−1) (1)	0.080 (L)	0.168 (L)	0.177 (L)	0.000 (L)	0.056 (L)	0.903 (M)	0.000 (L)	0.000 (L)	0.575 (M)
Mn (mg L−1) (1)	0.000 (L)	0.005 (L)	0.040 (L)	0.000 (L)	0.021 (L)	0.045 (L)	0.000 (L)	0.000 (L)	0.020 (L)
THB (UFC mL−1) (1)	406 (L)	280 (L)	170 (L)	18.2 (L)	45.5 (L)	131.00 (L)	43.00 (L)	54.50 (L)	194.00 (L)

Note: AB—municipal supply water; EB—aquaculture wastewater; ET—aquaculture wastewater with liquid anti-clogging fertilizer; EC—electrical conductivity; HA—hardness; TSS—total suspended solids; THB—total heterotrophic bacteria; L—low emitter clogging risk; M—moderate emitter clogging risk; H—high emitter clogging risk; ⁽¹⁾ Bucks, Nakayama, and Gilbert [30]; ⁽²⁾ Capra and Scicolone [25]; ⁽³⁾ Haman [31].

presents the physicochemical and microbiological characterization of the water used to supply the drip irrigation units, along with the classification of emitter clogging risk based on water characteristics.

Variations in the values of the physicochemical and microbiological attributes were observed over time in the three water sources. In the case of AB, among the emitter clogging parameters, the variation in pH stands out, with a severe risk of obstruction at the beginning of the experiment (0 h), which changed to moderate at 160 and 360 h. It is noteworthy that other parameters, such as Ca²⁺, Mg²⁺, K⁺, Cl⁻, hardness, and Fe, also presented considerable variations in their values over time. All of these variations may have been related to the water supply sources, since Mossoró-RN is supplied by groundwater, surface water, or a mixture of the two. In relation to EB, temporal variations in the values of the physicochemical and microbiological attributes were also detected, particularly in the case of the dripper clogging parameters, where greater risks occurred in relation to AB. At 0 h and 160 h of EB, a moderate risk of clogging was present only for pH variations, while a severe clogging risk was present for variations in EC, Ca²⁺, Mg²⁺, HCO₃⁻, and hardness. At 360 h of EB, the risk of clogging was severe for pH, EC, Ca²⁺, Mg²⁺, HCO₃⁻, and hardness. These variations can be attributed to the feeding of aquaculture animals with feed, their excretions, and the cleaning of the tanks. It should be noted that limestone or lime is not used to correct the pH in these tanks. ET presented clogging risk classifications similar to those of EB at all three times, except for Fe, which is probably present in the anti-clogging liquid fertilizer, allowing for a moderate clogging risk at 160 and 360 h. Fe can cause the formation of precipitates and enable the emergence of filamentous bacteria that form biofilms.

Regarding pH, the initial values (0 h) for AB, EB, and ET were 8.53, 7.77, and 7.70, respectively. EB and ET represented a moderate clogging risk (7.0 ≤ pH ≤ 8.0), while AB posed a severe clogging risk (pH > 8.0). At 160 h, the pH values for AB, EB, and ET were 7.50, 7.70, and 8.40, respectively, with AB and EB now at moderate risk and ET at severe risk. By the end of the tests (360 h), the pH values were 7.70, 8.10, and 8.50 for AB, EB, and ET, respectively, with AB classified as moderate risk and EB and ET as severe clogging risks.

For EB and ET at 0, 160, and 360 h, the EC ranged from 4.97 to 11.85 dS m⁻¹, indicating a severe clogging risk (EC > 4.5 dS m⁻¹). In contrast, AB had a low clogging risk (EC < 1.0 dS m⁻¹) at all three operating times. In EB and ET, the Na⁺ concentrations were 636.82 and 656.59 mg L⁻¹ at 0 h, 2999.3 and 2801.1 mg L⁻¹ at 160 h, and 2999.3 and 2801.1 mg L⁻¹ at 360 h, respectively. Meanwhile, AB had Na⁺ levels of 82.53, 90.35, and 100.35 mg L⁻¹ at 0, 160, and 360 h, respectively. The Ca²⁺ levels in EB and ET were 527.05 and 513.02 mg L⁻¹ at 0 h, 1014.02 and 952.90 mg L⁻¹ at 160 h, and 551.10 and 928.85 mg L⁻¹ at 360 h, respectively, representing a severe clogging risk (Ca²⁺ > 450 mg L⁻¹). In AB, the Ca²⁺ levels ranged from 8.42 to 24.24 mg L⁻¹, indicating a low clogging risk (Ca²⁺ < 25 mg L⁻¹). The Mg²⁺ concentrations in EB and ET were 152.00 and 148.35 mg L⁻¹ at 0 h, 154.43 and 293.18 mg L⁻¹ at 160 h, and 498.32 and 647.52 mg L⁻¹ at 360 h, respectively, all classified as severe clogging risks (Mg²⁺ > 90 mg L⁻¹). In AB, the Mg²⁺ levels ranged from 1.09 to 3.77 mg L⁻¹, posing a low clogging risk. The K⁺ levels varied depending on water type and operating time. In AB, EB, and ET, the K⁺ concentrations were 7.82, 44.18, and 44.18 mg L⁻¹ at 0 h; 9.77, 95.80, and 84.46 mg L⁻¹ at 160 h; and 13.69, 73.51, and 105.18 mg L⁻¹ at 360 h, respectively. For HCO₃⁻, EB and ET showed a high clogging risk at 0 h (375.27 and 349.03 mg L⁻¹, respectively), while at 160 h and 360 h, only ET had a severe clogging risk (381.08 and 443.62 mg L⁻¹, respectively). The Cl⁻ concentrations in AB, EB, and ET were 84.84, 1237.25, and 1201.9 mg L⁻¹ at 0 h; 141.4, 1908.9, and 2403.8 mg L⁻¹ at 160 h; and 141.4, 1908.9, and 2403.8 mg L⁻¹ at 360 h, respectively. Hardness, a key indicator of the presence of Ca²⁺ and Mg²⁺, also influences emitter clogging. AB had a low clogging risk (hardness < 150 mg L⁻¹), while EB and ET had a severe risk (hardness > 300 mg L⁻¹) at all operating times. Total suspended solids (TSS) posed a low physical clogging risk (TSS < 50 mg L⁻¹) in all three water sources and operating times. Most Fe levels indicated a low clogging risk (Fe < 0.20 mg L⁻¹), except in ET at 160 h and 360 h, where the risk was moderate (0.20 mg L⁻¹ ≤ Fe ≤ 1.50 mg L⁻¹). The Mn levels were all below 0.1 mg L⁻¹, indicating a low clogging risk. The bacterial counts (THB) remained below 10,000 CFU mL⁻¹ in all waters, representing a low biological clogging risk.

3.2. Dynamics of the Hydraulic Performance of the Non-Pressure-Compensating Emitter

Figure 2 shows the hydraulic performance indices AFRV and CUC for drip units with ST, SL, and GA emitters using AB, EB, and ET.

In Figure 2A, the ST emitter units show a decrease in the AFRV over time with AB and EB (7% and 25%, respectively, from 0 h to 360 h). The greater reduction with EB can be attributed to its higher chemical clogging risk (Table 2) and the formation of biofilms inside the emitters and lateral lines. Conversely, ET units saw a 10% flow rate increase, likely due to the liquid anti-clogging fertilizer. Comparing EB and ET at 360 h, the liquid anti-clogging fertilizer improved performance by 32%. At 360 h, ST/AB had slight clogging (80% ≤ AFRV < 95%), ST/EB had partial clogging (50% ≤ AFRV < 80%), and ST/ET had no clogging (AFRV ≥ 95%). ST/EB showed a drastic drop in CUC after 120 h (Figure 2B), while AB and ET were less affected. At 360 h, the liquid anti-clogging fertilizer improved the uniformity of water application by 42% (EB vs. ET). AB remained excellent (E), with CUC > 90%, while EB dropped to worst (W), with CUC < 70% after 280 h, and ET changed from E to good (G) due to the 80% ≤ CUC ≤ 90%.

In addition, Figure 2C shows AFRV reductions in SL emitters for all waters: 19% (AB), 41% (EB), and 15% (ET). The smaller reduction for ET can be attributed to the liquid anti-clogging fertilizer, which even outperformed AB. Comparing EB and ET at 360 h, performance improved by 30%. At 360 h, SL/AB and SL/ET had SLC, while SL/EB had PC. Figure 2D shows SL emitters with sharp CUC declines after 80 h (EB and ET) and 120 h (AB). At 160 h, ET improved uniformity by 72% vs. EB. By 360 h, AB shifted to regular (R), with 70% ≤ CUC < 80%, while EB and ET dropped to W.

Figure 2E shows AFRV reductions in GA emitters: 15% (AB), 37% (EB), and 15% (ET). The liquid anti-clogging fertilizer reduced clogging, improving performance by 25.57% (EB vs. ET at 360 h). At 360 h, AB and ET had SLC, while EB had PC. In Figure 2F, it can be seen that GA/ET declined after 80 h, while GA/AB and GA/EB dropped after 120 h. By 360 h, AB shifted to G, while GA/EB and GA/ET shifted to R.

SL emitters showed the highest clogging levels, likely due to their smaller labyrinth depth and length (Table 1).

The AFRV index presented values > 100%, indicating an increase in flow, for the ST emitter applying AB at times of 40, 80, 120, 160, 200, and 280 h and ET at times of 40, 80, 120, 160, 200, 240, 280, 320, and 360 h. AFRV values >100% also occurred in the SL emitter applying AB (40, 80, 120, 160, and 200 h), EB (40 and 120 h), and ET (40, 80, 200, 240, and 280 h). Meanwhile, in GA, AFRV values > 100% occurred only when applying ET at 40 and 200 h (Figure 2). It should be noted that AFRV values > 100% occurred more frequently in the non-self-compensating ST and SL emitters than in the self-compensating GA emitters (Figure 2).

In general, the fluctuations in AFRV > 100% in the ST and SL emitters applying AB and ET in the 120 h period, with a low incidence of biofouling, may be associated with three factors: (1) variations in service pressure due to the pumping system; (2) carrying out the hydraulic performance assessment at different times throughout the evaluation days, where the rise in temperature may have increased the flow rate due to the expansion of the plastic material of the non-self-compensating emitters; and (3) particularly in the case of ET, the anti-clogging liquid fertilizer may contain a lubricant constituent that reduces friction inside the emitters, enabling an increase in the flow velocity and, consequently, an increase in the flow rate. In the period from 120 to 360 h, where the formation of biofouling was more intense, the increase in flow in the ST and ET emitters operating with AB and ET may be related to five factors: (1) variations in service pressure; (2) increases in temperature, which expand the plastic material; (3) random unclogging processes, due to the detachment of biofouling fragments; (4) lubrication of the interior of the emitters with the anti-clogging liquid fertilizer; and (5) reductions in friction inside the emitter due to the formation of biofouling.

3.3. Analysis of Variance and Mean Test

Table 3. Summary of the analysis of variance of the average flow rate variation (AFRV) and Christiansen uniformity coefficient (CUC) in the split–split–plot scheme.

Sources of Variation	Degrees of Freedom	Mean Square
		AFRV	CUC
WS	2	5147.82 **	2859.37 *
Residue (a)	4	57.23	217.39
TG	2	1668.54 **	2352.20 **
TG × WS	4	234.27 ns	726.55 **
Residue (b)	8	61.42	100.85
T	9	1515.93 **	2725.00 **
T × WS	18	428.62 **	379.80 **
T × TG	18	176.16 **	403.98 **
T × WS × TG	36	58.94 *	94.52 **
Residue (c)	168	36.95	32.42
CVplot (%)		7.93	16.69
CV split plot (%)		8.21	11.37
CV split–split plot (%)		6.37	6.45
Média geral (%)		95.41	88.32

Note: **, *, and ^ns—significant at the 1% and 5% levels, and not significant at 5% probability, respectively, by F test; CV—coefficient of variation; WS—water source; TG—types of drippers; T—operating time.

presents a summary of the analysis of variance of the AFRV and CUC in the split–split–plot scheme.

Since the interaction of water (WS) × types of drippers (TG) × operating time (T) was significant, this triple interaction was then unfolded, and the comparison of the average values of the AFRV and CUC, and for the TG factor, within each T level and each WS, is presented in

Table 4. Average values of AFRV and CUC, and for the dripper type factor (TG), within each operating time level (T) and each water source level (WS).

T (h)	TG	WS *
		AFRV (%)			CUC (%)
		AB	EB	ET	AB	EB	ET
0	ST	100aA(NC)	100aA(NC)	100aA(NC)	98.76aA(E)	98.39aA(E)	96.58aA(E)
	SL	100aA(NC)	100aA(NC)	100aA(NC)	98.66aA(E)	97.77aA(E)	97.11aA(E)
	GA	100aA(NC)	100aA(NC)	100aA(NC)	97.99aA(E)	98.81aA(E)	98.60aA(E)
40	ST	106.41abAB(NC)	96.73aB(NC)	116.25aA(NC)	97.79aA(E)	95.95aA(E)	96.57aA(E)
	SL	110.93aA(NC)	103.23aA(NC)	116.01aA(NC)	96.92aA(E)	96.83aA(E)	97.25aA(E)
	GA	97.31bA(NC)	97.77aA(NC)	101.94bA(NC)	98.33aA(E)	97.24aA(E)	96.73aA(E)
80	ST	107.20abA(NC)	96.09aA(NC)	107.97aA(NC)	97.55aA(E)	95.75aA(E)	96.92aA(E)
	SL	111.23aA(NC)	96.66aB(NC)	101.99aAB(NC)	97.24aA(E)	97.10aA(E)	96.42aA(E)
	GA	96.67bA(NC)	96.66aA(NC)	99.50aA(NC)	97.88aA(E)	97.54aA(E)	96.23aA(E)
120	ST	104.10aA(NC)	97.86aA(NC)	101.77aA(NC)	97.68aA(E)	94.72aA(E)	95.07aA(E)
	SL	101.96a.A(NC)	102.59aA(NC)	99.99aA(NC)	97.88aA(E)	95.90aA(E)	92.16aA(E)
	GA	95.85aA(NC)	98.10aA(NC)	95.75aA(NC)	97.04aA(E)	96.45aA(E)	91.98aA(E)
160	ST	100.47aA(NC)	97.67aA(NC)	101.18aA(NC)	95.31aA(E)	88.64aA(G)	96.06aA(E)
	SL	100.82aA(NC)	95.52aA(NC)	90.78aA(SLC)	95.80aA(E)	87.04aA(G)	87.32aA(G)
	GA	97.21aA(NC)	87.39aA(SLC)	93.38aA(SLC)	96.40aA(E)	94.37aA(E)	89.48aA(G)
200	ST	100.23aB(NC)	91.90aB(SLC)	117.53aA(NC)	96.28aA(E)	90.17aA(E)	86.89aA(G)
	SL	100.26aA(NC)	93.05aA(SLC)	103.13bA(NC)	94.86aA(E)	83.92aA(G)	84.70aA(G)
	GA	96.00aAB(NC)	88.09aB(SLC)	101.79bA(NC)	93.95aA(E)	94.07aA(E)	92.40aA(E)
240	ST	85.41aB(SLC)	92.37aB(SLC)	111.93aA(NC)	93.90aA(E)	80.35abA(G)	94.57aA(E)
	SL	83.78aB(SLC)	75.16bB(PC)	109.90abA(NC)	91.86aA(E)	65.53bB(W)	78.98bAB(R)
	GA	93.50aAB(SLC)	81.68bB(SLC)	96.65bA(NC)	92.05aA(E)	92.23aA(E)	85.50abA(G)
280	ST	105.68aA(NC)	82.35aB(SLC)	116.24aA(NC)	92.99aA(E)	70.38bB(R)	91.73aA(E)
	SL	99.33aA(NC)	68.79bB(PC)	110.44aA(NC)	91.55aA(E)	60.13bB(W)	76.90aA(R)
	GA	93.87aA(SLC)	75.99abB(PC)	92.70bA(SLC)	89.36aA(G)	89.44aA(G)	83.50aA(G)
320	ST	97.41aB(NC)	76.19aC(PC)	117.10aA(NC)	96.51aA(E)	62.12bB(W)	93.83aA(E)
	SL	86.69aA(SLC)	57.97bB(PC)	79.50bA(PC)	82.94aA(G)	29.98cC(W)	49.95cB(W)
	GA	87.76aA(SLC)	65.13abB(PC)	91.56bA(SLC)	91.25aA(E)	82.45aA(G)	76.21bA(R)
360	ST	93.00aB(SLC)	74.50aC(PC)	110.38aA(NC)	93.62aA(E)	51.39bB(W)	88.68Aa(G)
	SL	81.04aA(SLC)	59.43bB(PC)	84.66bA(SLC)	76.45bA(R)	27.03cC(W)	46.90bB(W)
	GA	84.97aA(SLC)	63.42abB(PC)	85.20bA(SLC)	88.32abA(G)	78.74aA(R)	75.91aA(R)

Note: AB—supply water; EB—aquaculture wastewater; ET—aquaculture wastewater with liquid anti-clogging fertilizer; AFRV—average flow rate variation; CUC—Christiansen uniformity coefficient (CUC); TG—dripper type; T—operating time; WS—water source; ST—non-self-compensating dripper; SL—non-self-compensating dripper; GA—self-compensating dripper. * Means followed by at least one lowercase letter in the columns and one uppercase letter in the rows do not differ from each other at 5% probability, according to the Tukey test. According to Pei et al. [27], AFRV ≥ 95% for no clogging (NC), 80% ≤ AFRV < 95% for slight clogging (SLC) and 50% ≤ AFRV < 80% for partial clogging (PC)). According to Merriam and Keller [28], CUC > 90% classified as excellent (E), 80% ≤ CUC ≤ 90% classified as good (G), 70% ≤ CUC < 80% classified as regular (R), and CUC < 70% classified as worst (W).

.

At operating times of 40, 200, 240, 280, 320, and 360 h, the AFRV values of the ST/ET emitter increased significantly (p ≤ 0.05) in relation to the other emitters, due to the increase in flow rate, probably as a result of the increase in water temperature that causes expansion of the emitter composition material, along with variations in service pressure and the addition of the anti-clogging liquid fertilizer.

Particularly in ST/ET, the AFRV classification did not change during the experimental period, indicating that the anti-clogging liquid fertilizer in this dripper model prevented the reduction in flow. On the other hand, there was a change in the AFRV classification in GA/EB after 160 h, going from NC to slightly clogged (SLC) at 160, 200, and 240 h, and from SLC to partially clogged (PC) at 280, 320, and 360 h. Furthermore, GA/EB and GA/ET also differed statistically (p ≤ 0.05) after 160 h, proving the anti-clogging effect of the liquid fertilizer.

The CUC was reduced significantly (p ≤ 0.05) after 240 and 280 h in the SL and ST emitters, respectively. Thus, when comparing SL/EB and SL/ET at 240 h, it was noted that the liquid fertilizer did not mitigate the clogging due to the constructive characteristics of the labyrinth of this emitter, such as the smaller filtration area, depth, and labyrinth length in relation to ST (Table 1). However, when comparing ST/EB and ST/ET at 280 h, the anti-clogging effect of the liquid fertilizer was noted. The CUC classification changed from excellent (E) to good (G) at 160 h in ST/EB, SL/EB, and GA/ET. After 240 h, the CUC of SL/EB changed from G to worst (W) until 360 h. Similarly, SL/ET at 320 and 360 h presented a CUC classified as W. The CUC of GA/ET went from G to regular (R) after 320 h; therefore, the liquid fertilizer did not mitigate the clogging in this emitter, due to its smaller filtration area and the presence of a self-compensating membrane whose operation was compromised by the fertilizer dosage and biofilm accumulation.

3.4. Analysis of Bioincrustation at the End of the Experiment

Figure 3 and

Table 5. Energy-dispersive X-ray spectroscopy analysis of the elemental composition of biofilm samples from drip units supplied with supply water (AB), aquaculture wastewater (EB), and wastewater with continuous application of liquid anti-clogging fertilizer (ET).

Constituent	Elemental Composition
	AB		EB		ET
	Mass %	Atomic %	Mass %	Atomic %	Mass %	Atomic %
O	70.44	82.53	68.55	81.62	25.16	24.88
Ca	15.26	7.14	16.23	7.71	12.17	4.81
Si	5.44	3.63	5.84	3.96	0.74	0.42
Na	5.02	4.09	3.87	3.21	2.25	1.55
Mg	2.39	1.84	2.15	1.69	0.69	0.45
Cl	1.45	0.77	3.37	1.81	6.23	2.78
C	-	-	-	-	47.40	62.44
S	-	-	-	-	3.24	1.6
P	-	-	-	-	2.11	1.08

Note: O—oxygen; Ca—calcium; Si—silicon; Na—sodium; Mg—magnesium; Cl—chlorine; C—carbon; S—sulfur; P—phosphorus.

present the results of the energy-dispersive X-ray spectroscopy (EDS) analysis of the elemental composition of samples of the clogging material of the drip units supplied with AB (Figure 3A), EB (Figure 3B), and ET (Figure 3C).

Figure 4 and Figure 5 show the XRD patterns of clogging material from EB and ET emitters. EB’s primary clogging component was CaCO₃ (likely Ca-Mg carbonate), with a possible presence of silica. ET showed amorphous material, likely due to the liquid anti-clogging fertilizer. Phosphorus (P) and sulfur (S) were detected but not in crystalline form.

The SEM images (Figure 6) revealed biofilm in all samples, appearing as a viscous, smooth, gel-like mass. EB and ET had more cohesive deposits, typical of biofilm extracellular polymeric substances (EPSs). In ET, the biofilm was looser, likely due to the liquid anti-clogging fertilizer’s action, particularly in vortex regions.

4. Discussion

Assays on experimental benches that work via the recirculation of open-air water sources do not create the same scenario as field irrigation. In the field, water does not undergo recirculation, leading to an increase in some attributes because of concentration, at the expense of water evaporation. Furthermore, experiments on open-air benches are not subject to the shading provided by plants that can occur in the field, depending on the plant species, in addition to the fact that they have shorter lateral lines; on the other hand, experiments on experimental benches with recirculation allow for safer use of wastewater without negative impacts on the soil, allowing for faster and more intensified simulation of obstruction problems in laboratory conditions. It is also worth noting that improvements in the conduct of experiments on benches can be aimed at increasing the length of the lateral lines, using shaded areas, and improving water quality control to mitigate the effects of the accumulation of physical and chemical attributes.

4.1. Water Quality and Classification of Emitter Clogging Risk

The concurrent occurrence of pH > 7.5 and high levels of Ca²⁺ or Mg²⁺, combined with elevated water hardness, enhances carbonate precipitation in irrigation systems [30]. This phenomenon is exacerbated by the synergistic effect of increasing temperature and pH, which reduces the solubility of CaCO₃, promoting its deposition in emitters [31]. Such conditions were observed in the EB and ET waters in this study, where the pH values (7.70–8.50) and concentrations of Ca²⁺ (513.02–1014.02 mg L⁻¹) and Mg²⁺ (148.35–647.52 mg L⁻¹) indicated a severe clogging risk [25,30,31].

The electrical conductivity (EC) of the wastewater (EB: 4.97–8.45 dS m⁻¹; ET: 4.97–11.85 dS m⁻¹) was lower than that reported by Paiva et al. [16] for similar effluents (5.88–10.33 dS m⁻¹) but higher than that of the reverse-osmosis reject studied by Teixeira et al. [32] (1.56–1.76 dS m⁻¹). These variations reflect differences in the ionic composition of the effluents, with direct implications for clogging risk. Although there is no specific classification for Na⁺, its presence in saline waters (EB: up to 2999.3 mg L⁻¹; ET: up to 2801.1 mg L⁻¹) was associated with sodium chloride deposits in clogged emitters [33].

The Ca²⁺ and Mg²⁺ levels in this study exceeded the critical thresholds for clogging (>450 mg L⁻¹ and > 90 mg L⁻¹, respectively), surpassing even the values reported by Paiva et al. [16] and Teixeira et al. [32]. This disparity underscores the influence of the effluent source on scale formation. Additionally, the presence of HCO₃⁻ (up to 443.62 mg L⁻¹) amplifies the risk, as carbonates account for >63% of scaling in systems with saline waters [34].

The precipitation of CaCO₃, the main component of chemical clogging, is facilitated by the polymeric biofilm matrix, which encapsulates crystals and particles [31]. XRD analysis confirmed the predominance of CaCO₃ in EB samples, while amorphous material was observed in ET, attributed to the action of the liquid anti-clogging fertilizer. This morphological difference supports studies describing the coexistence of crystalline (calcite and aragonite) and amorphous (ACC) carbonate phases in irrigation systems [20].

Biofilm formation, observed via SEM in all treatments, plays a central role in clogging, even with low bacterial counts (<10⁴ CFU mL⁻¹). Its extracellular matrix, rich in polysaccharides and proteins [35], acts as a cementing agent, encapsulating particles and reducing hydraulic efficiency. In ET, the biofilm adhesion was less pronounced, particularly in turbulent flow regions, suggesting that the liquid anti-clogging fertilizer altered the deposition dynamics.

Finally, elevated Fe levels (up to 1.50 mg L⁻¹ in ET) and the presence of organic matter create favorable conditions for combined biological and chemical clogging [31], highlighting the need for integrated monitoring of these parameters in drip irrigation systems.

4.2. Effect of Liquid Anti-Clogging Fertilizer on Emitter Performance

The ST/EB emitter showed a sharp reduction in AFVR and CUC values from 240 h to 360 h Figure 2A,B, indicating an increase in emitter clogging as a function of operating time, as reported by Soliman et al. [9], due to biofouling formed by precipitates, organic particles, and bacterial biofilm [13]. However, when analyzing ST/ET in relation to ST/EB, it was found that the applied dose of anti-clogging liquid fertilizer, over the course of the operating time, reduced the clogging level by 32% (AFVR) and the loss of water application uniformity by 42% (CUC). It is also worth noting that, at the end of the experiment (360 h), there was slight clogging (SLC) of the drippers and uniform application of good water (G), enabling greater longevity of drip irrigation systems in semi-arid regions that operate with water and wastewater containing agents that cause chemical and biological clogging. Thus, fertilizers such as ammonium polyphosphate and the new urea phosphate can reduce the formation of calcium carbonate scale in the emitters in different ways. While ammonium polyphosphate exerts a protective effect that reduces the probability of Ca²⁺ and Mg²⁺ reacting to form carbonate scale in the emitter, the new urea phosphate mitigates emitter clogging by reacting with CaCO₃ and inhibiting the formation of calcite scale [21]. The ST emitter has an average flow velocity of 1.07 m s⁻¹, according to the data in Table 1. Fluid dynamics simulations in the dripper labyrinths with clogging of physical and biological origin revealed regions of high velocity in the main flow (around 1 m s⁻¹) and low velocity in the vortex dead zones (less than 0.2 m s⁻¹) formed in the corners of the channel, and it was observed that particle deposition and biofilm growth in the drippers occurred mainly in the first baffles and in the initial vortex zones, which are characterized by lower values of average velocity and turbulent kinetic energy [36].

The SL/EB emitter stood out for having the highest clogging rate (AFRV), at 41%, and the highest reduction in water application uniformity (CUC), at 72%, considering the three water sources used (AB, EB, and ET). However, this was the emitter with the highest average flow velocity, at 1.24 m s⁻¹, considered high by Ait-Mouheb et al. [36], corroborating the findings of Xiao et al. [22], who related the anti-clogging effect of fertilizers to the structural characteristics of the emitter. Analyzing SL/ET and SL/EB, it was evident that the use of liquid fertilizer did not prevent drastic changes in the AFRV(PC) and CUC(W) classifications at the end of the experiment. However, SL/ET still reduced the clogging levels and water application uniformity by 30% and 42%, respectively. It was noted that even the control treatment (SL/AB) presented inferior hydraulic performance to the other emitters due to its greater susceptibility to clogging. The maximum clogging rate of SL/EB was similar to that obtained by Maroufpoor et al. [15] with emitters operating with fish farming effluent for 336 h, where the maximum clogging was 43% of two emitters.

Regarding the GA emitter, a reduction in AFRV and CUC was observed over time, but GA/EB showed a greater decrease in AFRV, and GA/ET showed a greater reduction in CUC, probably due to the homogeneous development of biofouling in a greater number of emitters along the lateral lines. GA was the emitter that presented the lowest average flow velocity, at 0.91 m s⁻¹. In this sense, Ait-Mouheb et al. [36] warned that lower flow velocities can favor the deposition of particulate matter and biofilms in the inlet channel and the first baffles of the labyrinth of an emitter. The results of the present study do not corroborate the work of Maroufpoor et al. [15] with fish farming effluent, where the same GA emitter (4 L h⁻¹) maintained clogging levels (AFRV) within acceptable levels (AFRV ≥ 75%) until 312 h of treatment without drainage of the lateral lines, but the uniformity of water application was maintained at an acceptable level with and without drainage of the lateral lines (CUC ≥ 80%) for 336 h. Comparing GA/EB with GA/ET at 360 h, there was a 26% reduction in the clogging rate due to the application of liquid fertilizer, but there was no improvement in the uniformity of water application, since the CUC values were similar.

4.3. Statistical Analysis of Performance Using Anti-Clogging Liquid Fertilizer

Analyzing Table 3, it can be seen that the interaction WS × TG × T was significant for both the AFRV (p ≤ 0.05) and CUC (p ≤ 0.01), i.e., the obstruction of the emitters was significantly influenced by these three sources of variation. Similarly, the interaction WS × T was significant (p ≤ 0.01) for both the AFRV and CUC. The T factor was also significant (p ≤ 0.01) for the AFRV and CUC. However, the interaction TG × WS was not significant (p ≤ 0.05) for the AFRV. The values of the CVs of the split–split plot are 6.37% and 6.45% for the AFRV and CUC, respectively. As the CVs are ≤15%, there is low dispersion, indicating that the data are homogeneous. In the work of Batista et al. [23], a lower CV of the split–split–plot value (1.55%) was found for the CUC.

Observing the AFRV averages followed by at least one lowercase letter in the columns (Table 4), it can be seen that, at the AB level, the AFRV averages of the SL drip subunit differed (p ≤ 0.05) from the AFRV average of the GA drip subunit at 40 and 80 h, while the AFRV averages of the ST, SL, and GA drip units did not differ (p ≤ 0.05) at the other operating times studied. At the EB level, the AFRV average of the ST drip subunit differed (p ≤ 0.05) from the AFRV averages of the SL and GA drip subunits at the operating time of 240 h. Subsequently, still at the AA level, the mean AFRV of the ST drip subunit differed (p ≤ 0.05) from the mean AFRV of the SL drip subunit at 280, 320, and 360 h. Finally, at the ET level, the mean AFRV of the ST and SL drip subunits differed (p ≤ 0.05) from the mean AFRV of the GA drip subunit at the operating time of 40 h. Furthermore, at the ET level, the mean AFRV of the ST drip subunit differed (p ≤ 0.05) from the mean AFRV of the SL and GA drip subunits at 200, 320, and 360 h, and at the ET level, the mean AFRV of the ST drip subunit differed (p ≤ 0.05) from the mean AFRV of the GA drip subunit at 240 h, while the mean AFRV of the ST and SL drip subunits differed (p ≤ 0.05) from the mean AFRV of the GA drip subunit.

Checking the average AFRVs followed by at least one capital letter in the lines, the following was established: At the operating time of 40 h, the average AFRV of the ST dripping subunit at the AA level differed (p ≤ 0.05) from the average AFRV at the ET level. At the operating time of 80 h, the mean AFRV of the SL dripper subunit at the AB level differed (p ≤ 0.05) from the mean AFRV at the EB level. At 200 h, the mean AFRV values of the ST and GA dripper subunits differed (p ≤ 0.05) from the mean AFRV of the SL dripper subunit when the AB and EB levels were compared to the ET level. At 240 h, the average AFRV of the dripper subunits ST, SL, and GA at the AB and EB levels differed (p ≤ 0.05) from the average AFRV at the ET level. At 280 h, the average AFRV of the dripper subunits ST, SL, and GA at the AA level differed (p ≤ 0.05) from the average AFRV at the AB and ET levels. At 320 and 360 h, the average AFRV of the dripper unit SL at the AB, EB, and ET levels differed (p ≤ 0.05), while for both times the average AFRV of the dripper units SL and GA at the EB level differed (p ≤ 0.05) from the average AFRV of the dripper subunit ST.

Analyzing the average CUCs followed by at least one lowercase letter in the columns of Table 4, we found the following: At the AB level, the CUC of the ST dripper subunit differed (p ≤ 0.05) from the CUC of the SL dripper subunit only at the operating time of 360 h. Similarly, at the EB level, the CUC of the SL dripper subunit differed (p ≤ 0.05) from the CUC of the GA dripper subunit at the operating time of 240 h. In addition, the CUC of the SL and ST dripper subunits differed (p ≤ 0.05) from the CUC of the GA dripper subunit at the operating time of 280 h. At the same time, still at the EB level, the CUCs of the SL, ST, and GA dripper subunits differed (p ≤ 0.05) at the operating times of 320 and 360 h, respectively. Continuing, at the ET level, the CUC of the ST dripper subunit differed (p ≤ 0.05) from the CUC of the SL dripper subunit at the operating time of 240 h, while the CUCs of the SL, ST, and GA dripper subunits differed (p ≤ 0.05) at the operating time of 320 h. Finally, the CUC of the ST and GA dripper subunits differed (p ≤ 0.05) from the CUC of the SL dripper subunit at the operating time of 360 h.

By comparing the average CUCs followed by at least one capital letter in the lines, the following was established: At the operating time of 240 h, the CUC of the SL dripper subunit, at the AB level, differed (p ≤ 0.05) from the CUC at the EB level. At the operating time of 280 h, at the EB level, the average CUC of the ST and SL dripper subunits differed (p ≤ 0.05) between the AB and ET levels. At the operating times of 320 and 360 h, the CUC of the ST dripper subunit, at the EB level, differed (p ≤ 0.05) from the CUC at the AB and ET levels. For the same operating times, in the SL dripper subunit, the average CUC values differed (p ≤ 0.05) at all AB, EB, and ET levels.

The results obtained show that the type of emitter and the water quality influence both the growth of chemical scale [34] and the formation of biofilm inside the emitters [13]. Likewise, the structural characteristics of the emitter influence the effectiveness of liquid fertilizers with anti-clogging action [21,22]. It is worth noting that the flow speed and filtration area of the emitters are key factors in mitigating clogging [17,36].

4.4. Clogging Material Analysis (XRD and SEM)

Ramachandrula and Kasa [20] consider that elements below 1% are trace elements. The composition of AB is very similar to that of EB, which, in turn, differs from that of ET. The appearance of other elements is supposedly due to the addition of the anti-clogging liquid fertilizer to the water, given the chemical composition of the product. High concentrations of C and the presence of P are expected, as shown in the EDS analysis. It is noteworthy that P and S were identified in the EDS analysis and did not appear in the XRD analysis, indicating that they probably did not form crystalline structures and may have had an amorphous structure in the sample.

Figure 4 and Figure 5 show the diffractograms of the obstructing material collected from the emitter labyrinth in the EB and ET treatments, respectively. In Figure 4, the displacement peak was corrected, making the peak more intense for calcium carbonate, probably Ca-Mg carbonate. However, the amount of Mg was small according to the EDS, which makes sense considering the semi-quantification by the EDS. The XRD results also indicate the possible existence of another crystalline phase. However, it was not possible to observe a good match on a COD basis. Based on the EDS results, it can be assumed that there were silicon oxides in the sample, which may have been due to the presence of sand in the water. Thus, CaCO₃ would be the main element that caused the obstruction of the emitters in the dripper subunits supplied with EB.

In the ET (Figure 5), there was a predominance of amorphous material, judging by the large band observed. Some peaks stand out, possibly some calcium oxide. The peaks are at large angles, meaning that the spacings are small, which is typical of oxides. It can be assumed that the presence of amorphous material was due to the action of the anti-clogging agent used.

The elements P and S were also identified in the EDS analysis of the ET, but the presence of these elements was not identified in any of the crystalline compounds in the XRD analysis. It can be inferred that the P and S compounds were present in amorphous form [22].

From the XRD analysis of samples taken from the dripper mazes, the authors found that it was not possible to easily decipher the amorphous constituents. It is known that calcium carbonates exist in the form of either amorphous calcium carbonate or one of three polymorphs—namely, calcite, aragonite, and vaterite. Two hydrated phases of calcium carbonate monohydrate (CaCO₃⋅H₂O) and calcium carbonate hexahydrate (CaCO₃⋅6H₂O) are also possible forms of hydrated calcium carbonates [22].

Figure 6 shows the morphology of the material deposited in the emitter labyrinth, observed using SEM at magnifications of 30× and 100×.

In all of the samples, it is possible to note the presence of biofilm. The biofilm has the appearance of a massive, smooth, gelatinous, viscous material, as described by Li et al. [37], which is apparently interconnected with crystals and, possibly, solid particles. Biological material may have been the main agent responsible for the partial or total obstruction of the emitter, despite the low population levels present in the waters (Table 2), as it is not possible to see crystalline arrangements in the sample. The biofilm, being present in greater quantities, can camouflage the crystals. It was not possible to observe clusters of crystals with different shapes and sizes. According to Benlouali et al. [35], the presence of crystals in the sample is revealed by the appearance of crystals with different sizes, and the difference can be noted on the surface or deeper, representing different growth stages of the crystal formed during nucleation. Regarding the texture of the material, it was noted that the sample AB had an irregular and rough texture [35], different from that of the samples EB and ET, which had a smoother, well-cemented surface appearance, characteristic of biofilm ([38,39]). In addition, it is possible to note that the material of the samples EB and ET was more cohesive due to the biochemical composition of the biofilm [40,41,42]. The extracellular matrix of the biofilm is produced by microorganisms; this polymeric matrix is known as an extracellular polymeric substance (EPS) and consists of polysaccharides, proteins, exoenzymes, nucleic acids, and lipids, which immobilize the biofilm cells [13], keeping them cohesive, as seen in the samples EB and ET (Figure 6). The basis of the composition of the biofilm consists of relationships between carbon and oxygen, which present high rates in wastewater. To obtain SEM images, the samples must be dry; in this procedure, it is common for cracks to form in the samples containing biofilm, as shown in Figure 6D.

As for the deposition pattern, it was evident that the entire channel was occupied by obstructive material. However, in the ET sample, the biofilm was more detached from the labyrinth wall, especially in the vortex regions, which are recirculation regions in the emitter channel (Figure 6E). It can be assumed that this was due to the action of the liquid anti-clogging fertilizer used in the ET drip units, which was more effective in regions where the flow was more heterogeneous, in relation to the hydrodynamic characteristics of the flow [17].

5. Conclusions

There are relationships between the anti-clogging effect of liquid fertilizer, the structural characteristics of the emitters, and the flow velocity within the labyrinths.

The liquid fertilizer mitigated biofouling clogging in all three types of emitters, but only the ST emitter showed acceptable hydraulic performance rates (AFRV ≥ 75% and CUC ≥ 80%). The increasing order of improvement in anti-clogging performance with the continued use of liquid fertilizer was ST > GA > SL.

The SL dripper applying only aquaculture effluent showed the highest clogging rate and the greatest reduction in water application uniformity. The increasing order of susceptibility to clogging with aquaculture effluent was SL > ST > GA.

The analysis of the aquaculture effluent quality revealed that the parameters pH, electrical conductivity, Ca²⁺, Mg²⁺, HCO₃⁻, hardness, and Fe presented moderate and/or severe risks of obstruction throughout the experimental period, but the heterotrophic bacteria count presented a low risk of obstruction throughout.

However, scanning electron microscopy analyses revealed large biofilm formations in the dripper labyrinths, to the detriment of intense microbiological activity.