Zeolite and Inorganic Nitrogen Fertilization Effects on Performance, Lint Yield, and Fiber Quality of Cotton Cultivated in the Mediterranean Region

Abstract

The continuous provision of nitrogen (N) to the crop is critical for optimal cotton production; however, the constant and excessive application of synthetic fertilizers causes adverse impacts on soil, plants, animals, and human health. The current study focused on the short-term effects (one-year study) of adding different rates of clinoptilolite zeolite, as part of an integrated nutrient management plan, and different rates of inorganic N fertilizer to improve soil and crop performance of cotton in three locations (ATH, MES, and KAR) in Greece. Each experiment was set up according to a split-plot design with three replications, three main plots (zeolite application at rates of 0, 5, and 7.5 t ha⁻¹), and four sub-plots (N fertilization regimes at rates of 0, 100, 150, and 200 kg N ha⁻¹). The results of this study indicated that increasing rates of the examined factors increased cotton yields (seed cotton yield, lint yield, and lint percentage), with the greatest lint yield recorded under the highest rates of zeolite (7.5 t ha⁻¹: 1808, 1723, and 1847 kg ha⁻¹ in ATH, MES, and KAR, respectively) and N fertilization (200 kg N ha⁻¹: 1804, 1768, and 1911 kg ha⁻¹ in ATH, MES, and KAR, respectively). From the evaluated parameters, most soil parameters (soil organic matter, soil total nitrogen, and total porosity), root and shoot development (root length density, plant height, leaf area index, and dry weight), fiber maturity traits (micronaire, maturity, fiber strength, and elongation), fiber length traits (upper half mean length, uniformity index, and short fiber index), as well as color (reflectance and spinning consistency index) and trash traits (trash area and trash grade), were positively impacted by the increasing rates of the evaluated factors. In conclusion, the results of the present research suggest that increasing zeolite and N fertilization rates to 7.5 t ha⁻¹ and 200 kg N ha⁻¹, respectively, improved soil properties (except mean weight diameter), stimulated crop development, and enhanced cotton and lint yield, as well as improved the fiber maturity, length, and color parameters of cotton grown in clay-loam soils in the Mediterranean region.

1. Introduction

Cotton (Gossypium hirsutum L.) constitutes the most commonly utilized natural fiber material in the globe. It has a considerable economic impact on the world’s economy due to its broad use in the textile industry and the creation of job opportunities in the countries where the crop is grown [1]. Cotton fiber is used as a raw material in textile manufacturing, seeds are used to extract oil for biodiesel agro-industries, and seed cake is used in the feed industry [1,2]. The global population growth is also increasing the need for cotton cultivation [3]. Cotton has become increasingly important as the world’s population and living standards have grown. Cotton yield needs to be increased due to limited cultivation areas and a continual growth in cotton demand [3]. Farmers must produce more quantity and quality per unit area [2,4]. Despite a variety’s potential, crop management aspects such as nutrients, water, seedbed preparation, and weed control are critical for long-term cotton production, after climatic conditions [5].

The continuous provision of plant vital nutrients to the crop is critical for optimal cotton production. Several studies on different fertilizer doses have been conducted to optimize the nutrient requirements for long-term cotton production in diverse cotton-producing zones [5,6,7]. Nitrogen (N) is essential for cotton growth and development since cotton requires a lot of this nutrient [8,9]. Nevertheless, growers depend extensively on the excessive application of N fertilizers to increase cotton yield and earnings, resulting in late crop maturity, decreased N use efficiency and yield, as well as a decline in crop productivity [9,10]. According to prior research, providing optimal N dosages at the right time and with appropriate methods may boost biomass production and physiological characteristics, therefore improving cotton yield and quality [11,12,13]. Furthermore, some published studies have indicated that by reducing N rates, efficient agronomic management practices improve N use efficiency while also increasing lint yield and quality [9,14].

The constant and excessive application of synthetic fertilizers causes adverse impacts on soil, plants, animals, and human health [15,16]. As a result of the widespread application of nitrogenous fertilizers in cotton production today, nitrogen losses are increasing through leaching away from the soil and increasing environmental pollution [16,17]. In addition, the incorrect and continual application of synthetic fertilizers causes degradation of the soil, reduced soil water holding capacity, increased soil erosion, and losses of soil nutrients, ultimately resulting in soil fertility, all of which are critical concerns for agricultural lands around the world [17]. To address these issues, the use of zeolite as a soil amendment as part of an integrated nutrient management plan is seen as a critical and sustainable way to maintain and improve soil health and crop productivity [18,19,20].

Clinoptilolite zeolite, a naturally formed crystalline aluminosilicate, has attracted significant attention as a soil amendment for carbon storage while increasing soil properties, macro- and micronutrients, crop yield, and ecological sustainability [20,21,22]. In terms of soil qualities, zeolite provides numerous advantages, including increased soil moisture, improved hydraulic conductivity, and increased yields in acidic soils [21,22]. It is commonly used as a soil conditioner to improve soil physicochemical qualities and cation exchange capacity [18,19]. In addition, applying natural zeolite to soil to manage pH boosted macronutrient availability and improved ammonium retention [18,20,21]. Zeolite is primarily used in agriculture to fixate, store, and slowly release N. The literature demonstrates that adding zeolite to the N source can improve N use efficiency [18,23,24]. Several studies have indicated that mixing zeolite with N improves the compound’s function as a slow-release fertilizer in both intensive and extensive crops, including cotton [21,22,25].

There have been several studies conducted on the impact of soil amendments and inorganic fertilizers on soil parameters, crop growth, and yields around the world. However, no substantial research has been undertaken to assess the combined impacts of inorganic N fertilization and zeolite soil amendment on soil characteristics and cotton productivity in the Mediterranean semi-arid climate. For this reason, we anticipated that inorganic N fertilizer in the form of urea and soil incorporation with zeolite would increase soil characteristics, growth, and, ultimately, cotton crop productivity and yield. As a result, the current study focused on the short-term effects (one-year study) of adding different rates of clinoptilolite zeolite on the soil properties, growth, yield, and fiber quality-related traits of cotton crops under different rates of inorganic N fertilization in three locations in Greece that represent a typical Mediterranean environment.

2. Materials and Methods

2.1. Site Description and Experimental Design

Three field experiments were set up during the spring–summer season of 2024 across three different geographical locations in Greece, situated in the hot-summer Mediterranean climate zone (Csa) [26] and characterized by the same soil type (clay loam). Characteristics of experimental sites, including geographical information and soil properties, are presented in

Table 1. Geographical information and soil properties of the studied experimental sites.

Name	Athens (ATH)	Messolonghi (MES)	Karditsa (KAR)
Geographical location (Lat., Long.)	37°59′ N, 23°42′ E	38°36′ N, 21°48′ E	39°35′ N, 22°04′ E
Altitude (m above sea level)	29	−1.5	108
Regional Unit	Central Athens	Aetolia–Akarnania	Karditsa
Administrative Region	Attica	Western Greece	Thessaly
Geographical Region	East-Central Greece	Western Greece	Central Greece
Köppen Climate Classification Category [26]	Csa	Csa	Csa
Soil Properties (0–30 cm)
Soil Order [27]	Cambisol	Fluvisol	Cambisol
Soil Type	Clay Loam (CL)	Clay Loam (CL)	Clay Loam (CL)
Clay (%)	29.6	37.0	39.1
Silt (%)	34.8	20.7	24.2
Sand (%)	35.6	42.3	36.7
pH (1:1 H2O)	7.41	7.89	7.36
Organic Matter (%)	1.733	1.699	1.842
CaCO3 (%)	14.57	18.43	13.19
Total Nitrogen (%)	0.124	0.111	0.138
Phosphorus—Olsen P (mg kg−1 soil)	13.4	14.2	15.5
Potassium (mg kg−1 soil)	215	342	277

Csa: hot-summer Mediterranean climate zone according to Köppen Climate Classification Category [26].

. Soil analysis was performed on a soil sample collected from five randomly chosen points in each experimental site, at a 0–30 cm soil depth, according to the methodology used in [24].

Each experimental trial was set up on a 988 m² area as a split-plot design, with three main plots (Zeolite application at rates of 0, 5, and 7.5 t ha⁻¹) and four sub-plots (N fertilization regimes at rates of 0, 100, 150, and 200 kg N ha⁻¹) in three replications (

Table 2. Main plot and sub-plot treatments applied in the study.

Main Plot Treatment	Zeolite (Clinoptilolite Granules)
1	0 t ha−1
2	5 t ha−1
3	7.5 t ha−1
Sub-plot treatment	N Fertilization (Urea Fertilizer)
1	0 kg N ha−1
2	100 kg N ha−1
3	150 kg N ha−1
4	200 kg N ha−1

). The main plot and sub-plot sizes were 96 m² (12 m × 8 m) and 24 m² (8 m × 3 m), respectively. The cultivated plant was upland cotton (Gossypium hisrsutum L.) cultivar ‘Elpida’ (Golden West Seed Hellas, Athens, Greece), characterized as an early maturity variety with great adaptability to various environments, good verticillium wilt tolerance, excellent storm tolerance, and reliable harvesting behavior after heavy rains, making it the most widely cultivated cotton variety in Greece [28,29]. For homogenous starting conditions, the soil in each experimental site was prepared by mouldboard plowing at a depth of 0.25 m, three days before the sowing. Zeolite and N fertilizers were spread to the soil by basal dressing and were incorporated into the soil by harrowing. The natural zeolite (clinoptilolite; Thracean Zeolite by AVGI Ltd., Photolivos, Drama, Greece) utilized in the present investigation consisted of zeolite granules with a grain size of 2.5 to 5.0 mm and was characterized by a pH of 7.28, a cation exchange capacity (CEC) that ranged between 180 and 185 (cmol (p+) kg⁻¹), an electrical conductivity (EC) of 5.6 dS m⁻¹, moisture ranging between 7.4% and 8.6% (at 105 °C), a bulk density ranging between 0.8 and 1.1 g cm⁻³, as well as silica (SiO₂) and alumina (Al₂O₃) contents ranging between 68–74% and 8–12%, respectively. The N fertilizer was a 46-0-0 urea. For sustained upland cotton growing in Mediterranean semi-arid conditions, the maximum zeolite and N fertilizer amounts used in the current study represent the greatest optimal rates of each [22,25,30,31,32]. Seed sowing took place on the 25th of April, 27th of April, and 4th of May 2024 in ATH, MES, and KAR, respectively. The seeds were manually planted in single rows, 95 cm apart, with a plant density of 130,000 plants ha⁻¹. During the experimental period, a total of 582, 597, and 569 mm of water were applied by drip irrigation systems in ATH, MES, and KAR, respectively. Throughout the study, no diseases or pests had an impact on the cotton crop at any of the experimental locations. In addition, when necessary and before canopy closing, hand hoeing was used to control weeds.

The automatic weather station of the Agricultural University of Athens (Davis Vantage Pro2 Weather Station; Davis Instruments Corporation, Hayward, CA, USA) provided the average monthly air temperature and rainfall data for the ATH experimental site, which are shown in Figure 1. The automated weather stations of the Institute for Environmental Research, National Observatory of Athens [33], which are situated 5–10 km from each experimental trial, provided the relevant data for the MES and KAR experimental sites during the corresponding growing period (Figure 1). Between April and September 2024, the average air temperature was 26.3 °C in ATH, 25.4 °C in MES, and 23.0 °C in KAR. At the same time, the total precipitation was 38, 85, and 194 mm in ATH, MES, and KAR, respectively.

2.2. Sampling, Measurements, and Methods

Ninety days after sowing (90 DAS), two topsoil samples (0–30 cm) were collected from each sub-plot to analyze the chemical properties of the soil. Debris, roots, and stones were removed from soil samples using a 2 mm square-hole filter before air-drying at room temperature (25 °C) and analyzing for soil organic matter (SOM) and soil total nitrogen (STN). To accomplish these analyses, the wet oxidation method of Walkley and Black [34] and the Kjeldahl method [35] were utilized, with the use of a Büchi B-316 device (Buchi Labortechnik AG, Flawil, Switzerland) for combustion and extraction of soil. The mean weight diameter (MWD) of soil aggregates was determined at 90 DAS according to the procedure given by Van Bavel [36] using an oscillation apparatus Analysette 3 (Spartan, Fritsch Ltd., Oberstein, Germany). The oscillation time was 4 min., using 2 kg of air-dried soil from a depth of 0 to 60 cm and sieve mesh sizes where five aggregate fractions (40–20, 20–10, 10–5, 5–2, and <2 mm) were considered and calculated by the following equation:

$$\mathit{MWD} = {\sum }_{i=1}^n{x}_i w_i$$

(1)

where:

x_i—Mean diameter of different sizes of aggregates.

w_i—Proportion of different sizes of aggregates to total weight of aggregate

Total Soil Porosity (TP) was evaluated for each sub-plot at 90 DAS by obtaining undisturbed soil cores with 100 cm³ cylinders (5 cm height and 5.04 cm inner diameter) at depths ranging from 0 to 25 cm [37].

Moreover, a cylindrical substance corer (25 cm long and 10 cm broad) was utilized to pick root samples from the 0–35 cm layer between two plants in a row, avoiding border plants. Specifically, three root samples per sub-plot were analyzed at 90 DAS. After an overnight soak in H₂O + (NaPO₃)₆ + Na₂CO₃, the roots were extracted from the soil and decanted into a 0.1% trypan blue FAA staining solution (10% CH₂O, 50% CH₃CH₂OH, 5% CH₃COOH, and 35% H₂O). The root length density (RLD) was determined by scanning root samples via a high-resolution scanner (HP Scanjet 200 Flatbed Photo Scanner, Hewlett-Packard Inc., Palo Alto, CA, USA) and then analyzing the images using Delta-T software (Delta-T Scan ver. 2.04; Delta-T Devices Ltd., Burwell, Cambridge, UK) [38].

At 100 DAS, the leaf area index (LAI) in each sub-plot was assessed by taking five measurements in rapid succession with a Delta-T SunScan SS1 plant canopy analyzer (Delta-T Devices Ltd., Burwell, Cambridge, UK). The SunScan is a frequently employed, accurate, and nondestructive LAI measurement method that has been successfully utilized in numerous past research [24,32,39].

After the cotton bolls reached full maturity (9.5% boll moisture), the bolls from the whole plot were harvested on 16 September 2024 (145 DAS), 14 September 2024 (140 DAS), and 22 September 2024 (142 DAS). After harvesting, the bolls were weighted to estimate the crop’s yield. The yield was estimated (kg ha⁻¹) according to the following Equation (2):

$$\mathrm{Yield} (\mathrm{kg} {\mathrm{ha}}^{-1})={\displaystyle \frac{weight of bolls in plot in kg \ast \mathrm{10,000}}{size of plot in square meters}}$$

(2)

After ginning, seed and lint yield were estimated by weighing the seeds and lint. Lint percentage, the fraction of fiber weight to seed-cotton weight, was also calculated. In addition, 500 g of unginned cotton was utilized from each sub-plot to evaluate and assess fiber quality. The samples were analyzed at the National Centre for Quality Control, Classification, and Standardization of Cotton, Institute of Industrial and Forage Crops of the Hellenic Agricultural Organization “DIMIΤRA” (Karditsa, Greece) via a High-Volume Instrument (HVI) (Uster HVI 1000; Uster Technologies AG, Uster, Switzerland), and the evaluated quality parameters are fully presented and described in

Table 3. Short description and methodology of the evaluated cotton fiber quality traits.

Trait Group	Trait	Description	Method	Reference
Fiber Maturity Traits	Micronaire (MIC)	An indicative measurement of the air permeability of compressed cotton fibers	Via evaluating the resistance of airflow in a specific amount of cotton fibers	[40]
	Maturity (MAT)	The probability of breakage and entanglement	Measure of secondary walls’ thickness	[41]
	Fiber Strength (STR)	The needed strength for fiber breakage	Exert force until the breakage of a bundle of fibers	[42]
	Elongation (ELG)	The percentage of fiber’s extension before the breakage	Pull fibers and measure the length right before the breakage	[43]
Fiber Length Traits	Upper Half Mean Length (UHML)	A measurement of the length of fiber	The mean length of fiber’s longer half	[44]
	Uniformity Index (UI)	The ratio of the Upper-Half Mean Length (UHML) to the mean length of the fibers	Uniformity Index = Mean Length/Upper Half Mean Length	[45]
	Short Fiber Index (SFI)	The amount of fibers < 12.5 mm	Via HVI instrument	[46]
Color Traits	Fiber Reflectance (Rd)	The value of reflectance (Rd)	Measurement of the reflectance of the fiber using the Nickerson–Huntercolor chart	[47]
	Spinning Consistency Index (SCI)	An indicator that classifies fibers according to their quality and spinnability	SCI = −414.67 + 2.9 × Str − 9.32 × MIC + 49.17 × UHML + 4.74 × UI + 0.65 × Rd + 0.36 × (+b)	[48]
Trash Traits	Trash Area (TrAr)	The area covered with trash	Counting the pieces of trash that are exposed to the glass window	[44]
	Trash Grade (TrID)	The trash grade	Determined by calibrating HVI with known samples	[44]

.

2.3. Statistical Analysis

The data were subjected to a two-way analysis of variance (ANOVA) using the JMP 12 statistical program (SAS Institute Inc., Cary, NC, USA). The mean differences were separated using Tukey’s honestly significant difference (HSD) test. Principal component analysis (PCA) and Pearson’s correlation were used to describe the connections among all of the characteristics that were being examined. The significance level for each comparison was set at 5%.

3. Results

The interaction effect among zeolite addition and N fertilization had a considerable impact on soil total nitrogen (STN), total porosity (TP), root length density (RLD), elongation (ELG), upper half mean length (UHML), uniformity index (UI), short fiber index (SFI), and spinning consistency index (SCI), according to the current study’s three-way analysis of variance (ANOVA) (

Table 4. Combined analysis of variance (F values) for all studied variables over three experimental sites (ATH, MES, and KAR).

Source of Variance	Df	Soil Organic Matter (SOM)	Soil Total Nitrogen (STN)	Total Porosity (TP)	Mean Weight Diameter (MWD)	Root Length Density (RLD)	Plant Height
Location (L)	2	10.259 ***	286.807 ***	58.993 ***	4.438 *	2.366 ns	7.694 **
Zeolite (Z)	2	17.264 ***	11.798 ***	9.878 ***	14.350 ***	27.635 ***	27.707 ***
Fertilization (F)	3	5.423 **	17.429 ***	18.754 ***	19.796 ***	63.851 ***	20.384 ***
L × Z	4	0.887 ns	0.188 ns	0.317 ns	0.882 ns	0.036 ns	0.207 ns
L × F	6	0.318 ns	1.213 ns	1.289 ns	0.337 ns	0.854 ns	0.923 ns
Z × F	6	0.338 ns	4.616 ***	4.799 ***	0.183 ns	2.725 *	0.566 ns
L × Z × F	12	0.299 ns	0.079 ns	0.115 ns	0.161 ns	0.393 ns	0.229 ns
Source of Variance	Df	Leaf Area Index (LAI)	Dry Weight	Boll Number	Boll Weight	Seed Cotton Yield	Lint Yield
Location (L)	2	25.779 ***	12.258 ***	99.934 ***	3.029 ns	187.244 ***	34.636 ***
Zeolite (Z)	2	24.837 ***	19.382 ***	2.541 ns	17.707 ***	20.911 ***	25.167 ***
Fertilization (F)	3	61.184 ***	46.739 ***	3.868 *	18.949 ***	26.174 ***	27.718 ***
L × Z	4	0.239 ns	0.115 ns	0.068 ns	0.428 ns	0.347 ns	1.212 ns
L × F	6	0.829 ns	0.472 ns	0.329 ns	0.096 ns	0.717 ns	0.104 ns
Z × F	6	0.379 ns	1.052 ns	0.639 ns	0.953 ns	1.586 ns	1.557 ns
L × Z × F	12	0.156 ns	0.125 ns	0.467 ns	0.215 ns	0.843 ns	1.248 ns
Source of Variance	Df	Lint Percentage	Micronaire (MIC)	Maturity (MAT)	Fiber Strength (STR)	Elongation (ELG)	Upper Half Mean Length (UHML)
Location (L)	2	3.795 *	9.851 ***	37.615 ***	3.878 *	5.485 **	26.662 ***
Zeolite (Z)	2	19.968 ***	117.189 ***	17.389 ***	24.594 ***	37.619 ***	36.950 ***
Fertilization (F)	3	20.564 ***	9.111 ***	10.805 ***	9.539 ***	13.484 ***	10.484 ***
L × Z	4	1.932 ns	0.522 ns	0.184 ns	0.214 ns	0.851 ns	0.611 ns
L × F	6	0.298 ns	0.122 ns	0.406 ns	0.235 ns	0.237 ns	0.449 ns
Z × F	6	1.474 ns	2.102 ns	3.408 **	0.918 ns	3.137 **	2.891 *
L × Z × F	12	1.399 ns	0.068 ns	0.506 ns	0.239 ns	0.198 ns	0.351 ns
Source of Variance	Df	Uniformity Index (UI)	Short Fiber Index (SFI)	Fiber Reflectance (Rd)	Spinning Consistency Index (SCI)	Trash Area (TrAr)	Trash Grade (TrID)
Location (L)	2	53.781 ***	0.030 ns	36.952 ***	39.552 ***	0.184 ns	0.052 ns
Zeolite (Z)	2	17.102 ***	15.057 ***	63.189 ***	45.484 ***	31.359 ***	11.229 ***
Fertilization (F)	3	11.005 ***	9.354 ***	13.172 ***	15.035 ***	9.583 ***	0.679 ns
L × Z	4	0.149 ns	0.134 ns	0.098 ns	0.582 ns	0.293 ns	1.507 ns
L × F	6	0.138 ns	0.069 ns	0.172 ns	0.378 ns	0.216 ns	0.012 ns
Z × F	6	2.827 *	2.721 *	2.047 ns	3.648 **	1.426 ns	1.294 ns
L × Z × F	12	0.108 ns	0.094 ns	0.067 ns	0.241 ns	0.251 ns	1.438 ns

Df: Degrees of freedom. ^ns  =  not significant (p  >  0.05), * = p  ≤  0.05, ** = p  ≤  0.01, *** = p  <  0.001.

). Except for boll number, the zeolite application effect was statistically significant for all evaluated traits. In addition, all traits, except trash grade (TrID), were substantially impacted by N fertilization. Finally, the location effect was also significant in all traits, except the RLD, boll weight, SFI, trash area (TrAr), and TrID.

3.1. Soil Characteristics of the Experimental Sites

The zeolite addition had a significant impact on soil organic matter (SOM) across all experimental sites (

Table 5. Soil organic matter (SOM), soil total nitrogen (STN), total porosity (TP), and mean weight diameter (MWD) as influenced by zeolite addition and N fertilization regimes over three experimental sites (ATH, MES, and KAR).

	Soil Organic Matter (SOM) (%)	Soil Total Nitrogen (STN) (%)	Total Porosity (TP) (%)	Mean Weight Diameter (MWD) (mm)
ATH
	Zeolite (t ha−1)
0	1.818 ± 0.017 B	0.121 ± 0.001 B	43.16 ± 0.44 B	7.91 ± 0.14 A
5	1.916 ± 0.032 A	0.127 ± 0.002 A	44.63 ± 0.73 AB	7.79 ± 0.16 AB
7.5	1.895 ± 0.025 AB	0.129 ± 0.002 A	45.12 ± 0.71 A	7.44 ± 0.10 B
	N Fertilization (kg N ha−1)
0	1.833 ± 0.033 a	0.120 ± 0.001 b	42.67 ± 0.54 b	7.27 ± 0.08 c
100	1.876 ± 0.035 a	0.125 ± 0.002 ab	44.01± 0.69 ab	7.65 ± 0.16 bc
150	1.882 ± 0.037 a	0.128 ± 0.002 a	44.76 ± 0.85 ab	7.86 ± 0.18 ab
200	1.914 ± 0.019 a	0.129 ± 0.003 a	45.78 ± 0.64 a	8.09 ± 0.11 a
	Source of Variation
FZeolite	3.653 *	5.845 **	3.890 *	4.280 *
FFertilization	1.144 ns	4.564 *	4.766 **	6.541 **
FZeolite×Fertilization	0.416 ns	1.676 ns	1.838 ns	0.265 ns
MES
	Zeolite (t ha−1)
0	1.727 ± 0.019 B	0.104 ± 0.001 B	38.84 ± 0.42 B	8.30 ± 0.23 A
5	1.845 ± 0.029 A	0.108 ± 0.001 A	40.43 ± 0.71 AB	7.88 ± 0.21 AB
7.5	1.901 ± 0.035 A	0.110 ± 0.002 A	40.72 ± 0.64 A	7.41 ± 0.15 B
	N Fertilization (kg N ha−1)
0	1.775 ± 0.036 a	0.103 ± 0.001 b	38.36 ± 0.41 b	7.33 ± 0.14 b
100	1.815 ± 0.039 a	0.107 ± 0.001 ab	39.82 ± 0.70 ab	7.70 ± 0.24 ab
150	1.830 ± 0.043 a	0.109 ± 0.002 ab	40.49 ± 0.78 ab	8.01 ± 0.21 ab
200	1.775 ± 0.038 a	0.111 ± 0.002 a	41.32 ± 0.59 a	8.48 ± 0.27 a
	Source of Variation
FZeolite	7.365 **	4.828 *	4.274 *	6.362 **
FFertilization	1.225 ns	4.388 *	4.871 **	5.975 **
FZeolite×Fertilization	0.070 ns	2.216 ns	1.396 ns	0.040 ns
KAR
	Zeolite (t ha−1)
0	1.854 ± 0.021 B	0.136 ± 0.001 A	41.68 ± 0.48 A	7.80 ± 0.16 A
5	1.946 ± 0.027 A	0.141 ± 0.002 A	42.48 ± 0.67 A	7.46 ± 0.17 AB
7.5	1.986 ± 0.030 A	0.142 ± 0.003 A	42.90 ± 0.81 A	7.29 ± 0.14 B
	N Fertilization (kg N ha−1)
0	1.840 ± 0.037 b	0.130 ± 0.002 b	39.66 ± 0.68 b	6.94 ± 0.14 c
100	1.944 ± 0.034 a	0.141 ± 0.003 a	43.04 ± 0.52 a	7.49 ± 0.12 b
150	1.959 ± 0.029 a	0.142 ± 0.002 a	43.18 ± 0.46 a	7.70 ± 0.15 ab
200	1.970 ± 0.031 a	0.145 ± 0.003 a	43.79 ± 0.59 a	7.94 ± 0.16 a
	Source of Variation
FZeolite	7.867 **	2.392 ns	2.078 ns	4.293 *
FFertilization	4.623 *	9.214 ***	12.874 ***	8.817 ***
FZeolite×Fertilization	0.634 ns	1.214 ns	1.795 ns	0.346 ns

^ns  =  not significant (p  >  0.05), * = p  ≤  0.05, ** = p  ≤  0.01, *** = p  <  0.001. Statistically significant differences among zeolite application treatments within a location are depicted by different capital letters, whereas statistically significant differences between N fertilization regimes within an experimental site are depicted by different lowercase letters according to Tukey’s HSD test (p ≤ 0.05).

). Specifically, in MES and KAR, the high rate of zeolite (7.5 t ha⁻¹) achieved the highest values of SOM (1.901% and 1.986%), whereas, in ATH, the highest value (1.916%) was recorded after the application of 5 t ha⁻¹ zeolite. As for the N fertilization effect on this trait, a significant difference among treatments was only recorded in KAR, with the greatest value (1.970%) observed under the highest N rate (200 kg N ha⁻¹).

In ATH and MES, soil total nitrogen (STN) was statistically affected by zeolite (Table 5), with the highest values found after the application of 7.5 t ha⁻¹ zeolite, resulting in an increase of 6.61% and 5.77%, respectively, compared to the untreated (control). In a similar vein, the STN was also affected by N fertilization, with the highest values being recorded with N applied at 200 kg N ha⁻¹ and the values being 0.129%, 0.111%, and 0.145% in ATH, MES, and KAR, respectively.

Zeolite and N fertilizer had a considerable impact on total porosity (TP) (Table 5). Concerning zeolite, except KAR, application at 7.5 t ha⁻¹ led to significantly greater values compared to the untreated, leading to a percentage difference of 4.54% and 4.84% in ATH and MES, respectively. Regarding N fertilization, the highest TP values (45.78%, 41.32%, and 43.79% in ATH, MES, and KAR) were observed under the highest N fertilizer rate (200 kg N ha⁻¹).

Mean weight diameter (MWD) was influenced by the zeolite and N fertilizer application (Table 5). In plots treated with 7.5 t ha⁻¹ zeolite, the lowest MWD values were recorded, resulting in a decrease of 5.94%, 10.73%, and 6.54% in ATH, MES, and KAR, respectively, compared to the untreated. Additionally, the application of the highest N fertilizer rate also exhibited the highest MWD value, with these being 8.09, 8.48, and 7.94 mm in ATH, MES, and KAR, respectively.

3.2. Agronomic Traits and Yield Parameters of Cotton

As shown in

Table 6. Root length density (RLD), plant height, leaf area index (LAI), and dry weight as influenced by zeolite addition and N fertilization regimes over three experimental sites (ATH, MES, and KAR).

	Root Length Density (RLD) (cm cm−3)	Plant Height (cm)	Leaf Area Index (LAI) (m3 m−3)	Dry Weight (kg ha−1)
ATH
	Zeolite (t ha−1)
0	0.665 ± 0.037 B	94.2 ± 3.2 B	2.50 ± 0.08 B	4185 ± 221 B
5	0.754 ± 0.046 A	107.4 ± 2.9 A	2.74 ± 0.07 A	4546 ± 296 AB
7.5	0.813 ± 0.051 A	113.3 ± 3.0 A	2.83 ± 0.08 A	5014 ± 308 A
	N Fertilization (kg N ha−1)
0	0.561 ± 0.019 c	95.3 ± 3.5 c	2.39 ± 0.06 c	3450 ± 153 c
100	0.721 ± 0.026 b	102.6 ± 3.6 bc	2.63 ± 0.07 b	4345 ± 182 b
150	0.792 ± 0.050 ab	107.0 ± 4.8 ab	2.70 ± 0.08 b	4984 ± 247 a
200	0.902 ± 0.049 a	114.9 ± 3.2 a	3.04 ± 0.06 a	5549 ± 244 a
	Source of Variation
FZeolite	8.053 **	17.539 ***	14.751 ***	6.115 **
FFertilization	21.354 ***	9.324 **	27.909 ***	21.533 ***
FZeolite×Fertilization	1.498 ns	0.816 ns	0.545 ns	0.239 ns
MES
	Zeolite (t ha−1)
0	0.635 ± 0.037 C	95.9 ± 3.8 B	2.46 ± 0.07 B	3979 ± 252 B
5	0.732 ± 0.039 B	107.2 ± 3.6 A	2.64 ± 0.08 A	4204 ± 299 AB
7.5	0.797 ± 0.048 A	110.1 ±3.9 A	2.75 ± 0.06 A	4844 ± 308 A
	N Fertilization (kg N ha−1)
0	0.521 ± 0.024 b	87.7 ± 4.0 b	2.29 ± 0.05 c	3265 ± 158 c
100	0.759 ± 0.027 a	106.6 ± 3.8 a	2.62 ± 0.07 b	4151 ± 249 b
150	0.774 ± 0.029 a	110.7 ± 2.9 a	2.67 ± 0.10 ab	4584 ± 297 b
200	0.828 ± 0.038 a	112.5 ± 3.2 a	2.91 ± 0.07 a	5368 ± 243 a
	Source of Variation
FZeolite	14.714 ***	8.049 **	7.175 **	5.394 *
FFertilization	30.816 ***	13.963 ***	11.548 ***	15.484 ***
FZeolite×Fertilization	2.210 ns	0.344 ns	0.281 ns	0.494 ns
KAR
	Zeolite (t ha−1)
0	0.688 ± 0.029 B	102.8 ± 3.2 B	2.76 ± 0.08 B	4610 ± 220 B
5	0.770 ± 0.047 AB	114.6 ± 4.0 AB	2.97 ± 0.07 A	4948 ± 239 B
7.5	0.839 ± 0.052 A	120.7 ± 3.4 A	3.01 ± 0.09 A	5593 ± 213 A
	N Fertilization (kg N ha−1)
0	0.593 ± 0.021 c	103.6 ± 3.7 b	2.50 ± 0.07 c	4223 ± 165 c
100	0.739 ± 0.032 b	112.1 ± 4.1 ab	2.94 ± 0.05 b	4877 ± 249 b
150	0.831± 0.045 ab	115.0 ± 4.9 ab	3.00 ± 0.05 ab	5327 ± 292 ab
200	0.900 ± 0.043 a	120.2 ± 3.8 a	3.19 ± 0.06 a	5775 ± 207 a
	Source of Variation
FZeolite	7.164 **	6.599 **	9.009 **	8.369 **
FFertilization	16.389 ***	2.974 *	34.360 ***	11.056 ***
FZeolite×Fertilization	0.305 ns	0.146 ns	0.230 ns	0.542 ns

^ns  =  not significant (p  >  0.05), * = p  ≤  0.05, ** = p  ≤  0.01, *** = p  <  0.001. Statistically significant differences among zeolite application treatments within a location are depicted by different capital letters, whereas statistically significant differences between N fertilization regimes within an experimental site are depicted by different lowercase letters according to Tukey’s HSD test (p ≤ 0.05).

, root length density (RLD) was affected by zeolite with the highest values (0.813, 0.797, and 0.839 cm cm⁻³ in ATH, MES, and KAR, respectively) found after the application of the high rate (7.5 t ha⁻¹), and increased by 22.26%, 25.51%, and 21.95% in ATH, MES, and KAR, respectively, compared to the untreated. In a similar vein, the increasing rate of N fertilizer resulted in significantly higher RLD values, with the greatest values observed with N applied at 200 kg N ha⁻¹ (0.902, 0.828, and 0.900 cm cm⁻³ in ATH, MES, and KAR, respectively).

According to the results of the current research, plant height was also affected by both examined factors across the three experimental trials (Table 6). Concerning the zeolite effect, the values of the experimental plots that received 7.5 t ha⁻¹ zeolite were the greatest, increasing by 20.28%, 14.81%, and 17.41% in ATH, MES, and KAR, respectively, compared to the untreated. Concerning N fertilization, the greatest results were in plots where N fertilizer was applied at 200 kg N ha⁻¹, with values of 114.9, 112.5, and 120.2 cm in ATH, MES, and KAR, respectively.

Concerning leaf area index (LAI), there were significant differences between plots that received zeolite as a soil amendment and those untreated. In all experimental sites, the highest values (2.83, 2.75, and 3.01 m³ m⁻³ in ATH, MES, and KAR, respectively) were observed after the application of the high rate of zeolite (Table 6). Regarding the effect of N fertilization, the greatest LAI values (3.04, 2.91, and 3.19 m³ m⁻³ in ATH, MES, and KAR, respectively) were observed in plots fertilized with 200 kg N ha⁻¹, which increased by 27.20%, 27.07%, and 27.60% in ATH, MES, and KAR, respectively, in comparison to the untreated.

The dry weight of the cotton crop, as affected by the application of zeolite and inorganic N fertilizer, is presented in Table 6. Concerning zeolite, application at 7.5 t ha⁻¹ resulted in substantially greater dry weight values compared to the untreated, leading to a percentage difference of 19.81%, 21.74%, and 21.32% in ATH, MES, and KAR, respectively. Regarding the N fertilization treatments, the highest dry weight values (5549, 5368, and 5593, in ATH, MES, and KAR, respectively) were noted following the highest rate of N fertilizer application.

As for boll number, there were no substantial differences between different zeolite regimes, with the values ranging between 75.9 and 76.8 m⁻², 73.7 and 74.4 m⁻², and 78.5 and 79.1 m⁻² in ATH, MES, and KAR, respectively (

Table 7. Boll number, boll weight, seed cotton yield, lint yield, and lint percentage as influenced by zeolite addition and N fertilization regimes over three experimental sites (ATH, MES, and KAR).

	Boll Number (m−2)	Boll Weight (g)	Seed Cotton Yield (kg ha−1)	Lint Yield (kg ha−1)	Lint Percentage (%)
ATH
	Zeolite (t ha−1)
0	75.9 ± 0.3 A	6.11 ± 0.02 B	4639 ± 14 C	1627 ± 31 B	35.1 ± 0.6 B
5	76.4 ± 0.2 A	6.14 ± 0.01 AB	4695 ± 19 B	1759 ± 24 A	37.4 ± 0.3 A
7.5	76.8 ± 0.4 A	6.18 ± 0.02 A	4745 ± 26 A	1808 ± 34 A	38.1 ± 0.5 A
	N Fertilization (kg N ha−1)
0	75.9 ± 0.3 a	6.09 ± 0.03 c	4633 ± 10 c	1641 ± 30 b	35.4 ± 0.6 b
100	76.2 ± 0.2 a	6.12 ± 0.01 bc	4669 ± 11 bc	1695 ± 28 b	36.3 ± 0.5 b
150	76.3 ± 0.4 a	6.18 ± 0.02 ab	4712 ± 25 ab	1786 ± 33 a	37.8± 0.5 a
200	76.9 ± 0.5 a	6.19 ± 0.02 a	4759 ± 34 a	1804 ± 53 a	37.9 ± 0.9 a
	Source of Variation
FZeolite	1.588 ns	5.291 *	14.008 ***	18.334 ***	15.410 ***
FFertilization	1.095 ns	5.406 **	11.110 ***	9.367 ***	6.861 **
FZeolite×Fertilization	1.194 ns	0.216 ns	1.989 ns	1.741 ns	1.230 ns
MES
	Zeolite (t ha−1)
0	73.7 ± 0.4 A	6.12 ± 0.02 B	4512 ± 25 B	1617 ± 35 B	35.8 ± 0.6 B
5	74.3 ± 0.5 A	6.15 ± 0.02 AB	4576 ± 31 AB	1703 ± 38 A	37.2 ± 0.6 A
7.5	74.4 ± 0.3 A	6.19 ± 0.01 A	4597 ± 26 A	1723 ± 29 A	37.5 ± 0.5 A
	N Fertilization (kg N ha−1)
0	73.6 ± 0.3 a	6.08 ± 0.02 c	4478 ± 22 b	1572 ± 31 c	35.1 ± 0.6 b
100	74.1 ± 0.4 a	6.14 ± 0.01 b	4557 ± 14 ab	1657 ± 25 bc	36.4 ± 0.4 ab
150	74.3 ± 0.7 a	6.18 ± 0.02 ab	4577 ± 39 a	1729 ± 47 ab	37.7 ± 0.7 a
200	74.7 ± 0.4 a	6.20 ± 0.01 a	4634 ± 36 a	1768 ± 35 a	38.1 ± 0.6 a
	Source of Variation
FZeolite	0.685 ns	5.494 *	3.568 *	3.869 *	3.886 *
FFertilization	0.869 ns	10.750 ***	5.593 **	6.760 **	7.192 **
FZeolite×Fertilization	0.423 ns	0.521 ns	0.648 ns	0.918 ns	1.028 ns
KAR
	Zeolite (t ha−1)
0	78.5 ± 0.5 A	6.12 ± 0.02 B	4805 ± 39 B	1776 ± 36 B	36.9 ± 0.5 B
5	79.2 ± 0.3 A	6.18 ± 0.01 A	4895 ± 17 A	1862 ± 24 A	38.0 ± 0.4 A
7.5	79.1 ± 0.4 A	6.22 ± 0.02 A	4921 ± 29 A	1847 ± 15 A	37.8 ± 0.2 A
	N Fertilization (kg N ha−1)
0	77.9 ± 0.3 a	6.11 ± 0.03 b	4768 ± 32 c	1742 ± 28 c	36.5 ± 0.5 c
100	78.6 ± 0.4 a	6.16 ± 0.02 ab	4844 ± 34 b	1798 ± 30 b	37.1± 0.4 bc
150	79.3 ± 0.6 a	6.20 ± 0.02 a	4919 ± 23 a	1882 ± 19 a	38.2 ± 0.3 ab
200	79.8 ± 0.5 a	6.22 ± 0.03 a	4964 ± 27 a	1911 ± 14 a	38.5 ± 0.4 a
	Source of Variation
FZeolite	0.735 ns	7.167 **	8.726 **	9.253 **	3.601 *
FFertilization	2.385 ns	4.920 **	12.992 ***	17.021 ***	7.095 **
FZeolite×Fertilization	0.271 ns	0.605 ns	1.243 ns	1.985 ns	2.579 *

^ns  =  not significant (p  >  0.05), * = p  ≤  0.05, ** = p  ≤  0.01, *** = p  <  0.001. Statistically significant differences among zeolite application treatments within a location are depicted by different capital letters, whereas statistically significant differences between N fertilization regimes within an experimental site are depicted by different lowercase letters according to Tukey’s HSD test (p ≤ 0.05).

). Similarly, the impact of N fertilization was not significant on this trait, with the values ranging between 75.9 and 76.9 m⁻², 73.6 and 74.7 m⁻², and 77.9 and 79.8 m⁻² in the corresponding experimental trials.

On the contrary, boll weight was positively influenced by both zeolite addition and N fertilization, as shown in Table 7. Concerning the zeolite addition effect, the boll weight observed in plants of high zeolite rate (6.18, 6.19, and 6.22 g in ATH, MES, and KAR, respectively), were the greatest, increasing by 1.15%, 1.14%, and 1.63% in ATH, MES, and KAR, respectively, in comparison with the untreated. Regarding the influence of N fertilization, the greatest results were recorded in plots treated with the highest N rate (6.19, 6.20, and 6.22 g in ATH, MES, and KAR, respectively).

The findings of the current research reported that seed cotton yield, lint yield, as well as lint percentage were considerably impacted by zeolite and N fertilization regimes (Table 7). Increasing zeolite (from 0 to 7.5 t ha⁻¹) and N fertilization rates (from 0 to 200 kg N ha⁻¹) caused a significant increase in these yield parameters. Specifically, averaged over N fertilization regimes, the highest values for seed cotton yield, lint yield, and lint percentage were recorded in plots treated with 7.5 t ha⁻¹ zeolite, with the results being 4745 kg ha⁻¹, 1808 kg ha⁻¹, and 38.1% for ATH; 4597 kg ha⁻¹, 1723 kg ha⁻¹, and 37.5% for MES; and 4921 kg ha⁻¹, 1847 kg ha⁻¹, and 37.8% for the KAR experimental site. In addition, averaged over zeolite addition treatments, the greatest results for the aforementioned variables were recorded in plots where N fertilizer was applied at 200 kg N ha⁻¹, with the corresponding values of 4759 kg ha⁻¹, 1804 kg ha⁻¹, and 37.9% for ATH; 4634 kg ha⁻¹, 1768 kg ha⁻¹, and 38.1% for MES; and 4964 kg ha⁻¹, 1911 kg ha⁻¹, and 38.5% for the KAR experimental location.

3.3. Fiber Quality Parameters of Cotton

The ANOVA suggested that fiber maturity parameters, namely micronaire (MIC), maturity (MAT), fiber strength (STR), and elongation (ELG) were positively affected by both examined factors across the three experimental trials (

Table 8. Fiber maturity traits (micronaire (MIC), maturity (MAT), fiber strength (STR), and elongation (ELG)) as influenced by zeolite addition and N fertilization regimes over three experimental sites (ATH, MES, and KAR).

	Fiber Maturity Traits
	Micronaire (MIC)	Maturity (MAT) (%)	Fiber Strength (STR) (g text−1)	Elongation (ELG) (%)
ATH
	Zeolite (t ha−1)
0	3.58 ± 0.06 C	0.818 ± 0.02 B	28.94 ± 0.77 B	9.29 ± 0.16 C
5	4.24 ± 0.11 B	0.832 ± 0.01 AB	31.55 ± 0.74 A	10.61 ± 0.38 B
7.5	4.55 ± 0.08 A	0.857 ± 0.01 A	33.58 ± 0.79 A	11.44 ± 0.29 A
	N Fertilization (kg N ha−1)
0	3.90 ± 0.16 b	0.817 ± 0.01 b	29.43 ± 0.69 b	9.50 ± 0.28 b
100	4.11 ± 0.15 ab	0.833 ± 0.02 ab	30.94 ± 0.96 ab	10.06 ± 0.30 b
150	4.22 ± 0.17 a	0.837 ± 0.01 ab	32.35 ± 1.17 a	11.04 ± 0.46 a
200	4.27 ± 0.19 a	0.855 ± 0.02 a	32.72 ± 1.20 a	11.17 ± 0.51 a
	Source of Variation
FZeolite	40.438 ***	7.204 **	10.347 ***	25.919 ***
FFertilization	3.266 *	3.217 *	3.232 *	10.480 ***
FZeolite×Fertilization	0.798 ns	1.953 ns	0.650 ns	1.471 ns
MES
	Zeolite (t ha−1)
0	3.35 ± 0.06 B	0.797 ± 0.01 B	28.92 ± 0.99 B	8.67 ± 0.22 B
5	4.14 ± 0.11 A	0.820 ± 0.01 AB	32.11 ± 1.32 AB	10.10 ± 0.34 A
7.5	4.48 ± 0.14 A	0.834 ± 0.02 A	33.76 ± 0.86 A	10.98 ± 0.46 A
	N Fertilization (kg N ha−1)
0	3.74 ± 0.15 b	0.793 ± 0.01 b	29.05 ± 1.15 b	9.10 ± 0.26 b
100	3.94 ± 0.18 ab	0.819 ± 0.02 ab	31.17 ± 1.02 ab	9.79 ± 0.44 ab
150	4.03 ± 0.19 ab	0.821 ± 0.01 ab	31.94 ± 1.83 ab	10.09± 0.47 ab
200	4.23 ± 0.26 a	0.836 ± 0.01 a	34.23 ± 1.07 a	10.67 ± 0.70 a
	Source of Variation
FZeolite	32.127 ***	4.359 *	5.566 *	13.501 ***
FFertilization	3.072 *	3.126 *	3.149 *	3.169 *
FZeolite×Fertilization	0.819 ns	1.321 ns	0.443 ns	1.207 ns
KAR
	Zeolite (t ha−1)
0	3.62 ± 0.08 B	0.853 ± 0.01 B	29.99 ± 0.94 B	9.96 ± 0.24 B
5	4.52 ± 0.11 A	0.871 ± 0.01 A	33.71 ± 1.19 A	10.55 ± 0.37 AB
7.5	4.81 ± 0.10 A	0.886 ± 0.01 A	36.10 ± 0.83 A	11.43 ± 0.31 A
	N Fertilization (kg N ha−1)
0	4.09 ± 0.18 b	0.851 ± 0.02 c	30.44 ± 1.26 b	9.85 ± 0.18 b
100	4.26 ± 0.16 ab	0.858 ± 0.01 bc	33.08 ± 1.21 ab	10.48 ± 0.39 ab
150	4.40 ± 0.19 ab	0.882 ± 0.01 ab	34.31 ± 1.64 a	10.93 ± 0.43 a
200	4.52 ± 0.24 a	0.888 ± 0.01 a	35.24 ± 1.18 a	11.33 ± 0.51 a
	Source of Variation
FZeolite	48.052 ***	7.258 **	10.552 ***	6.172 **
FFertilization	4.067 *	6.339 **	3.624 *	3.363 *
FZeolite×Fertilization	0.613 ns	1.092 ns	0.386 ns	0.996 ns

^ns  =  not significant (p  >  0.05), * = p  ≤  0.05, ** = p  ≤  0.01, *** = p  <  0.001. Statistically significant differences among zeolite application treatments within a location are depicted by different capital letters, whereas statistically significant differences between N fertilization regimes within an experimental site are depicted by different lowercase letters according to Tukey’s HSD test (p ≤ 0.05).

).

Concerning MIC, the results of the present research indicated that the highest values for this fiber maturity parameter (4.55, 4.48, and 4.81 in ATH, MES, and KAR, respectively) were observed after zeolite addition at 7.5 t ha⁻¹, leading to percentage differences of 27.09%, 33.73%, and 32.87% in ATH, MES, and KAR, respectively, compared to the untreated (Table 8). In the same manner, averaged over zeolite addition treatments, the highest values (4.27, 4.23, and 4.52 in ATH, MES, and KAR) were found after N fertilizer application at 200 kg N ha⁻¹.

As presented in Table 8, MAT was influenced by zeolite, with the highest values (0.857%, 0.834%, and 0.886% in ATH, MES, and KAR, respectively) found after the application of the high rate (7.5 t ha⁻¹), leading to increases of 4.77%, 4.64%, and 3.87% in ATH, MES, and KAR, respectively, in comparison with the untreated. In the same way, the increasing rate of N fertilizer resulted in significantly higher MAT values, with the highest values found with N applied at 200 kg N ha⁻¹ (0.855%, 0.836%, and 0.888% in ATH, MES, and KAR, respectively).

In all experimental sites, STR was statistically influenced by zeolite (Table 8), with the highest values found after the application of 7.5 t ha⁻¹ zeolite, leading to an increase of 16.03%, 16.74%, and 20.07% in ATH, MES, and KAR, respectively, in comparison with the untreated. In a similar vein, STR was also influenced by the application of N fertilizer, with the highest values being recorded with N applied at 200 kg N ha⁻¹, yielding 32.72, 34.23, and 35.24 g tex⁻¹ in ATH, MES, and KAR, respectively.

Regarding the zeolite effect on ELG, the highest values (11.44%, 10.98%, and 11.43% in ATH, MES, and KAR, respectively) were observed after the application of the high rate of zeolite (Table 8). Concerning the effect of N fertilizer application, the greatest values of ELG (11.17%, 10.67%, and 11.33% in ATH, MES, and KAR, respectively) were recorded in plots fertilized with 200 kg N ha⁻¹, showing increases of 17.58%, 17.25%, and 15.03% in ATH, MES, and KAR, respectively, in comparison to the untreated.

The results of the fiber length traits, namely upper half mean length (UHML), uniformity index (UI), and short fiber index (SFI), as influenced by the addition of zeolite and N fertilizer, are presented in

Table 9. Fiber length traits (upper half mean length (UHML), uniformity index (UI), and short fiber index (SFI)) as influenced by zeolite addition and N fertilization regimes over three experimental sites (ATH, MES, and KAR).

	Fiber Length Traits
	Upper Half Mean Length (UHML) (mm)	Uniformity Index (UI) (%)	Short Fiber Index (SFI) (<12.5 in mm)
ATH
	Zeolite (t ha−1)
0	27.56 ± 0.17 C	79.48 ± 0.49 B	8.02 ± 0.49 B
5	28.88 ± 0.33 B	80.94 ± 0.51 AB	9.43 ± 0.57 AB
7.5	29.73 ± 0.26 A	82.35 ± 0.70 A	10.97 ± 0.78 A
	N Fertilization (kg N ha−1)
0	27.87 ± 0.32 b	79.75 ± 0.51 b	8.29 ± 0.38 c
100	28.81 ± 0.28 a	80.04 ± 0.46 b	8.58 ± 0.53 bc
150	29.04 ± 0.46 a	81.94 ± 0.64 a	10.42 ± 0.62 ab
200	29.17 ± 0.51 a	81.97 ± 1.02 a	10.60 ± 0.49 a
	Source of Variation
FZeolite	25.959 ***	7.995 **	6.771 **
FFertilization	5.619 **	4.133 *	3.415 *
FZeolite×Fertilization	1.429 ns	1.032 ns	1.058 ns
MES
	Zeolite (t ha−1)
0	26.82 ± 0.27 B	78.05 ± 0.52 B	7.91 ± 0.59 B
5	28.33 ± 0.34 A	79.71 ± 0.48 A	9.52 ± 0.62 AB
7.5	29.21 ± 0.44 A	81.14 ± 0.79 A	10.86 ± 0.77 A
	N Fertilization (kg N ha−1)
0	27.20 ± 0.31 b	78.39 ± 0.59 c	8.27 ± 0.67 c
100	28.09 ± 0.47 ab	78.86 ± 0.51 bc	8.53 ± 0.60 bc
150	28.53 ± 0.39 a	80.51 ± 0.57 ab	10.33 ± 0.73 ab
200	28.67 ± 0.70 a	80.77 ± 0.74 a	10.61 ± 1.02 a
	Source of Variation
FZeolite	13.766 ***	8.001 **	6.295 **
FFertilization	3.138 *	3.514 *	4.128 *
FZeolite×Fertilization	1.007 ns	1.194 ns	0.893 ns
KAR
	Zeolite (t ha−1)
0	29.08 ± 0.29 B	83.39 ± 0.59 B	8.43 ± 0.62 B
5	29.73 ± 0.48 AB	84.18 ± 0.70 AB	9.16 ± 0.68 AB
7.5	30.83 ± 0.37 A	85.96 ± 0.73 A	11.09 ± 0.59 A
	N Fertilization (kg N ha−1)
0	28.96 ± 0.21 b	83.07 ± 0.53 b	8.24 ± 0.40 b
100	29.73 ± 0.69 ab	83.21 ± 0.27 b	8.31 ± 0.42 b
150	30.04 ± 0.42 ab	85.72 ± 0.72 a	10.55 ± 0.91 ab
200	30.80 ± 0.40 a	86.04 ± 0.89 a	11.13 ± 1.24 a
	Source of Variation
FZeolite	6.614 **	3.409 *	3.407 *
FFertilization	3.671 *	3.715 *	3.048 *
FZeolite×Fertilization	1.279 ns	0.899 ns	0.967 ns

^ns  =  not significant (p  >  0.05), * = p  ≤  0.05, ** = p  ≤  0.01, *** = p  <  0.001. Statistically significant differences among zeolite application treatments within a location are depicted by different capital letters, whereas statistically significant differences between N fertilization regimes within an experimental site are depicted by different lowercase letters according to Tukey’s HSD test (p ≤ 0.05).

.

Zeolite and N fertilizer had a considerable impact on the UHML parameter (Table 9). Concerning zeolite, 7.5 t ha⁻¹ treatment produced noticeably higher values compared to the untreated, leading to a percentage difference of 7.87%, 8.91%, and 6.01% in ATH, MES, and KAR, respectively. Regarding N fertilization, the greatest results of the UHML parameter (29.17, 28.67, and 30.80 mm, in ATH, MES, and KAR, respectively) were observed after the application of the highest N fertilizer rate.

According to Table 9, UI was positively influenced by both evaluated factors. In response to the zeolite addition effect, the UI values observed in plants of high zeolite rate (82.35%, 81.14%, and 85.96% in ATH, MES, and KAR, respectively) were the greatest, increasing by 3.61%, 3.96%, and 3.08% in ATH, MES, and KAR, respectively, compared to the untreated. As for the effect of N fertilizer application, the greatest results were recorded in plots treated with the highest N rate (81.97%, 80.77%, and 86.04% in ATH, MES, and KAR, respectively).

The SFI parameter was also significantly affected by the application of zeolite and N fertilizer (Table 9). In plots that received 7.5 t ha⁻¹ zeolite, the highest SFI values were found, increasing by 36.78%, 37.29%, and 31.55% in ATH, MES, and KAR, respectively, compared to the untreated. Moreover, the addition of the highest N fertilizer led to the highest SFI values, leading to percentage differences of 27.86%, 28.30%, and 35.07% in ATH, MES, and KAR, respectively, as compared to the untreated.

Finally, the fiber color traits of cotton, namely fiber reflectance (Rd) and spinning consistency index (SCI), as well as the trash traits, namely trash area (TrAr) and trash grade (TrID), were significantly influenced by different zeolite treatments (

Table 10. Fiber color (fiber reflectance (Rd) and spinning consistency index (SCI)) and trash traits (trash area (TrAr) and trash grade (TrID)) as influenced by zeolite addition and N fertilization regimes over three experimental sites (ATH, MES, and KAR).

	Color Traits		Trash Traits
	Fiber Reflectance (Rd)	Spinning Consistency Index (SCI)	Trash Area (TrAr) (%)	Trash Grade (TrID) (1–7 index)
ATH
	Zeolite (t ha−1)
0	71.39 ± 0.93 C	141.75 ± 0.94 C	0.343 ± 0.06 C	3.8 ± 0.4 C
5	74.88 ± 0.57 B	149.28 ± 1.72 B	0.622 ± 0.11 B	4.9 ± 0.2 B
7.5	78.56 ± 0.63 A	154.69 ± 1.68 A	0.916 ± 0.07 A	5.8 ± 0.2 A
	N Fertilization (kg N ha−1)
0	73.57 ± 1.06 b	143.38 ± 1.90 b	0.520 ± 0.11 b	4.7 ± 0.5 a
100	73.95 ± 0.93 b	148.40 ± 1.61 a	0.533 ± 0.13 b	4.8 ± 0.4 a
150	75.43 ± 1.19 ab	150.86 ± 2.24 a	0.609 ± 0.14 ab	4.9 ± 0.3 a
200	76.83 ± 1.73 a	151.64 ± 3.13 a	0.848 ± 0.08 a	5.1 ± 0.4 a
	Source of Variation
FZeolite	29.273 ***	35.435 ***	14.625 ***	11.703 ***
FFertilization	3.802 *	8.748 ***	3.094 *	0.315 ns
FZeolite×Fertilization	0.832 ns	1.912 ns	1.077 ns	1.072 ns
MES
	Zeolite (t ha−1)
0	69.04 ± 0.79 C	137.51 ± 1.53 B	0.353 ± 0.05 B	4.3 ± 0.3 B
5	72.71 ± 0.66 B	146.12 ± 1.80 A	0.698 ± 0.13 A	5.3 ± 0.3 A
7.5	76.18 ± 1.02 A	151.54 ± 2.60 A	0.851 ± 0.10 A	5.0 ± 0.2 AB
	N Fertilization (kg N ha−1)
0	70.92 ± 1.10 c	139.28 ± 1.98 b	0.437 ± 0.07 b	4.7 ± 0.5 a
100	71.29 ± 1.15 bc	144.37 ± 2.50 ab	0.491 ± 0.13 b	4.9 ± 0.2 a
150	73.44 ± 1.33 ab	147.59 ± 2.41 a	0.709 ± 0.16 ab	4.9 ± 0.2 a
200	74.93 ± 1.56 a	148.98 ± 4.04 a	0.901 ± 0.12 a	5.0 ± 0.4 a
	Source of Variation
FZeolite	23.188 ***	16.389 ***	6.941 **	3.901 *
FFertilization	4.857 **	4.553 *	3.621 *	0.222 ns
FZeolite×Fertilization	0.620 ns	1.151 ns	0.359 ns	2.389 ns
KAR
	Zeolite (t ha−1)
0	74.81 ± 0.83 C	151.59± 1.63 B	0.246 ± 0.06 B	4.3 ± 0.5 A
5	77.59 ± 0.89 B	155.56 ± 2.12 B	0.649 ± 0.12 A	4.8 ± 0.3 A
7.5	81.65 ± 0.97 A	162.50 ± 2.86 A	0.884 ± 0.10 A	5.3 ± 0.3 A
	N Fertilization (kg N ha−1)
0	76.13 ± 0.99 b	150.60 ± 1.18 b	0.418 ± 0.08 b	4.6 ± 0.6 a
100	76.31 ± 0.86 b	156.59 ± 2.28 ab	0.454 ± 0.12 b	4.7 ± 0.3 a
150	78.91 ± 1.51 ab	156.67 ± 2.44 ab	0.679 ± 0.18 ab	4.9 ± 0.3 a
200	80.72 ± 1.92 a	162.34 ± 4.23 a	0.822 ± 0.14 a	5.0 ± 0.6 a
	Source of Variation
FZeolite	15.121 ***	8.359 **	12.099 ***	1.338 ns
FFertilization	4.654 *	4.722 *	3.188 *	0.196 ns
FZeolite×Fertilization	0.743 ns	1.391 ns	0.669 ns	1.123 ns

^ns  =  not significant (p  >  0.05), * = p  ≤  0.05, ** = p  ≤  0.01, *** = p  <  0.001. Statistically significant differences among zeolite application treatments within a location are depicted by different capital letters, whereas statistically significant differences between N fertilization regimes within an experimental site are depicted by different lowercase letters according to Tukey’s HSD test (p ≤ 0.05).

). In particular, averaged over the different N fertilization rate treatments, the highest values of Rd, SCI, TrAr, and TrID were observed in plots treated with 7.5 t ha⁻¹ zeolite, with the results being 78.56, 154.69, 0.916%, and 5.8 for ATH; 76.18, 151.54, 0.851%, and 5.0 for MES; and, 81.65, 162.50, 0.884%, and 5.3 for the KAR experimental site. In addition, averaged over zeolite regimes, the highest values of Rd, SCI, and TrAr were found in plots where N fertilizer was applied at 200 kg N ha⁻¹, with the corresponding values being 76.83, 151.64, and 0.848% for ATH; 74.93, 148.98, and 0.901% for MES; and, 80.72, 162.34, and 0.822% for the KAR experimental trial. As for TrID, there were no significant differences among different N fertilization regimes, with values ranging between 4.7 and 5.1, 4.7 and 5.0, and 4.6 and 5.0 in ATH, MES, and KAR, respectively (Table 9).

3.4. Principal Component Analysis (PCA) of Evaluated Variable

The principal component analysis (PCA) clarified 64.09% of the total variability, as presented in Figure 2. PC1 (54.4%) clarified the greatest amount of variation by distinguishing between the untreated plots of the two examined factors under study and the N fertilizer application at a level of 100 kg N ha⁻¹ (on the negative site) and the zeolite addition treatments at amounts of 5 and 7.5 t ha⁻¹, along with N fertilizer at levels of 150 and 200 kg N ha⁻¹ (on the positive side). By separating the zeolite addition at amounts of 5 and 7.5 t ha⁻¹ and N fertilizer application at levels of 150 and 200 kg N ha⁻¹ (on the positive side) from the untreated plots of the two examined factors and N fertilizer at a level of 100 kg N ha⁻¹ (on the negative side), PC2 demonstrated 9.69% of the total variance. The upper-right quadrant contained the N fertilizer application at 150 and 200 kg N ha⁻¹ and the zeolite addition treatments at 5 and 7.5 t ha⁻¹, which were more correlated with LAI, dry weight, plant height, ELG, SF, RLD, STR, MIC, lint percentage, boll weight, TrAr and TrID. In addition, N fertilizer at a level of 100 kg N ha⁻¹ and the controls of the two examined factors were observed in the low-left quarter and showed no association with the examined variables.

4. Discussion

One of the main features of soil degradation is a lack of soil organic matter (SOM), which lowers soil fertility and reduces crop production potential [49]. The extensive use of chemical fertilizers and other artificial inorganic inputs, especially in arid and semi-arid areas where agricultural soils are decomposing, low in organic matter, and unable to retain water, has resulted in air pollution, groundwater contamination, soil organic matter loss, and a decline in crop production quality [50,51]. This aligns with the current study findings, which showed that the amount of SOM increased when zeolite was added as a soil amendment (Table 5). Furthermore, prior research has demonstrated a positive correlation between clay concentration and the preservation of soil organic carbon [24,52,53]. Consequently, the use of N fertilizer led to a rise in net primary productivity (NPP), which in turn led to a considerable improvement in SOM in the current research soils, which were classified as clay loams. As NPP increased, soil moisture and temperature decreased because of variations in transpiration and shade, resulting in a decrease in SOM mineralization [54,55].

Soil total nitrogen (STN) is increasingly recognized as a crucial parameter influencing soil fertility in both managed and natural ecosystems, and therefore, it is often used as a stand-in for the N condition of the soil [56]. Table 5 presents how varied N fertilizer rates affected the average STN in the current investigation. Specifically, a considerable rise in STN was observed as N rates increased, with the effect being more pronounced at high N rates. These findings are comparable with those from some previous investigations [57,58]. Regarding zeolite, it has direct or indirect beneficial effects on the physical, chemical, and biological characteristics of soil, which enhances nutrient retention and cycling. Because of the electrostatic interaction between positively charged NH₄⁺ and negatively charged sites in zeolitic minerals, a high degree of NH₄⁺ sorption selectivity is linked to a high cation exchange capacity (CEC) in these minerals [59]. When combined with chemical fertilizers, zeolites in the soil slow mineralization, decrease greenhouse gas emissions, decrease nitrogen leaching and volatilization, and postpone the release of nutrients into the soil solution [21]. Prior research investigated how chemical fertilizers and zeolite affected several field crops to absorb macronutrients, including N, and discovered that zeolite treatments marginally increased STN because of the unique and exceptional properties of zeolites on soil [24,60]. Furthermore, the growth in SOM was accompanied by notable increases in STN, indicating that SOM had organic N bound up. This is further supported by the significant linear correlation between SOM and STN (r = 0.627, p < 0.001; Figure 3).

Total porosity (TP) constitutes one of the most crucial physical properties of soil, which aids in nitrate and water infiltration as well as root growth. The current investigation found that increasing the zeolite application dose had a favorable effect on TP, with the greatest values recorded under the highest zeolite rate (Table 5). Utilizing zeolite raises soil TP, which generally enhances soil structure and could affect crop production measures including gas exchange and water transport [61]. In a previous study conducted by Kakabouki et al. [24], it was found that after the application of 7.5 t ha⁻¹ zeolite in clay loam soil, TP increased by 5.36% as compared to the untreated. The zeolite caused the soil density to drop, the soil porosity to rise, and the soil structure to improve. High zeolite mineral porosity, and thus better soil composition and physical characteristics like TP and water retention, may also be related [62]. Furthermore, this feature appeared to benefit from a rise in the N fertilization rate. A previous study discovered that after a year-long field experiment on sandy clay loam soil for maize crop, mineral fertilizer applied at a rate of up to 200 kg N ha⁻¹ enhanced soil TP by enlarging regular and irregular pores and created a priming effect of native SOM [63].

One measure of the physical characteristics of soil is the mean weight diameter (MWD) of the soil aggregates, which describes the quality of the soil structure. According to the current study, zeolite application had a negative impact on this trait (Table 5). This was most likely brought on by exchangeable Na⁺ supplied by zeolite replacing Ca²⁺ and Mg²⁺ on the soil clays, which resulted in the dispersion of soil particles [64,65]. Because flocculation of clay particles was a fundamental prerequisite for the formation of aggregates, this led to the dissolution of soil aggregation [65]. In addition, this phenomenon can also be explained by the size of zeolite particles. Specifically, because zeolites range in size from 2.5 to 5 mm, the soil matrix particles’ agglomeration and smoothness decreased [65]. As for N fertilization, it seemed to have a positive impact on this trait, especially under high N rates (Table 5). The inclusion of cementing materials that produce nitrogen may be connected to this phenomenon. Smaller soil particles have been shown to enter big, water-stable soil aggregates when high N fertilizer is applied; these aggregates have been linked to root systems and secretions [66].

Robust root systems are essential for boosting crop yields because crops can store photosynthetic products in their leaves, stems, seeds, and roots. To absorb enough amounts of water and nutrients, particularly when biotic or abiotic stress is present, a well-developed root system is necessary, with root development and dispersion being essential characteristics [67]. Concerning the N fertilizing impact, it was shown that the root length density (RLD) increased as the administered N rate increased. Gregory [68] noted that RLD was significantly enhanced by the addition of N fertilizer to the soil. Additionally, several studies found that N fertilizer significantly boosts root growth, especially in soils with low levels of SOM (1–2.5%) [69]. Depending on the crop species being grown, zeolite composites might have varying effects on root shape and development [70]. In the current study, zeolite used as a soil amendment raised RLD in comparison to cotton, which did not receive a soil amendment. This outcome is consistent with studies by Wu et al. [71] and Kakabouki et al. [24], which found that zeolite application at a rate of 7.5 t ha⁻¹, can enhance root growth in rice and maize plants, respectively.

Zeolite can enhance plant growth and development by boosting the long-term availability of nutrients and water [22,72]. Because of its porous structure, zeolite can keep water in the rhizosphere for long periods and create humidity horizontally [73]. Reduced nitrification and N leaching, regulated nutrient release, and selective absorption are some advantages of using zeolite for vegetative development [74]. The open-ringed structure’s small molecular size provides physical protection for NH₄⁺ ions against microbiological nitrification [22]. Thus, it seems that higher N uptake caused cotton to grow taller. Additionally, the addition of N through inorganic N fertilizer increased the synthesis of cytokines, which in turn affected the number of meristematic cells, cell proliferation, and cell wall elasticity [75]. Consequently, following the N fertilizer application at the maximum rate under investigation (200 kg N ha⁻¹), the highest values of plant height were noted (Table 6).

Both zeolite addition and N fertilization greatly increased the cotton crop’s dry weight and leaf area index (LAI) (Table 6). Prior research showed that a greater supply of zeolite as soil amendment improves LAI and photosynthetic efficiency in a variety of field crops due to its slow-release nature and higher ammonium retention capacity, which boost N availability to plants [21,24]. Other studies have also noted an increase in plant biomass as a result of more nitrogen being available when N fertilizer as well as zeolite was added as a soil amendment [21,22]. Furthermore, because accessible N is required for the enzymes phosphoenolpyruvate carboxylase (PEPcase), ribulose-1,5-bisphosphate carboxylase (RuBPCase), and chlorophyll a and b, it has been shown to impact the photosynthetic processes of plants [76,77,78,79]. In fact, according to previous research, plant biomass increases with the amount of chlorophyll a and chlorophyll b present [76,77,78]. These variables, together with the ratio of relative soluble protein, total N content, carboxylase activity, and chlorophyll concentration, all contribute to accelerating photosynthesis and supplying the required nutrients and photosynthetic products to the plant and seed [76]. In the present study, higher N levels in the 200 kg N ha⁻¹ treatment, along with improved growth and development of the plant’s aboveground components, particularly the leaf area, resulted in higher photosynthetic rates, which ultimately led to the maximum dry weight. The LAI and dry weight of cotton have a strong correlation (r = 0.712, p < 0.001; Figure 3), confirming this association.

As the amounts of N and zeolite fertilization increased, the seed yield correspondingly increased (Table 7). Using zeolite as a soil amendment has been demonstrated in numerous studies to improve crop yields for a range of crops, including maize, wheat, sunflower, soybean, rapeseed, rice, and sugar cane [80,81]. Zeolite’s high porosity increased water-holding capacity, and very substantial cation exchange capacity all help to increase seed cotton yield. In addition, it improves nutrient uptake by plants by making nutrients more accessible through different amounts of application. Furthermore, zeolite’s capacity to release minerals gradually reduces the loss of vital nutrients. Applying varying amounts of zeolite seems to improve the seed cotton yield. The largest yields were obtained when cotton plants received the maximum quantity of N and zeolite supplementation, according to Kathade et al. [25], who used zeolite at varied rates in conjunction with different quantities of N. Cotton needs large amounts of N, which is the main nutrient for growth and development [82]. Accordingly, fiber quality is strongly impacted by appropriate nutritional management linked to genetic and environmental factors [83]. Given that crop yield is correlated with the variable lint percentage, it is feasible to conclude that greater lint percentage values attained with N increase show that N fertilization improves yields [84]. According to several studies, applying N fertilizers to cotton crops greatly increases the number of bolls, suggesting that cotton is responsive to N and has a wide absorption capacity. As a result, using nitrogen increases the yield and lint percentage [82,85]. This was supported by the current investigation, which found a strong and positive association between seed cotton yield, lint yield, lint percentage, and boll weight (Figure 3). Furthermore, varied zeolite and fertilization treatments had no significant effect on boll number (Table 7). This parameter is generally influenced by a wide range of factors, including soil properties, climate, cultivation methods, and genetic potential, i.e., cotton variety. Similar to Nie et al. [86], this result demonstrated that location and cotton cultivar significantly influenced this parameter.

As for fiber maturity traits, micronaire (MIC) had a positive response to the highest rates of zeolite addition (7.5 t ha⁻¹) and N fertilization (200 kg N ha⁻¹) (Table 8). Given that the MIC is a crucial metric, these findings could have a direct impact on fiber quality [87]. The thickness and maturity of the fiber are correlated with the MIC index; values below 3.5 show the production of immature fibers and variations in fiber dyeing, while values above 5.0 are categorized as low resistance, which lowers the fiber’s value and is above the level that the market accepts [88]. The activity of essential enzymes, which are involved in processes that directly impact the synthesis, structure, and characteristics of cotton fibers, as well as playing vital roles in the metabolism of proteins and carbohydrates, is intimately related to the correct presence of N [85].

In the same manner, fiber maturity (MAT) was also favorably impacted by the two parameters that were investigated, with the greatest results observed in 7.5 t ha⁻¹ zeolite (0.857%, 0.834%, and 0.886% in ATH, MES, and KAR, respectively) and N fertilization at a rate of 200 kg N ha⁻¹ (0.855%, 0.836%, and 0.888% in ATH, MES, and KAR, respectively) (Table 8). According to da Silva Ribeiro [85], the values of this parameter are regarded as one of the most crucial aspects of fiber quality for the textile industry. Since immature fibers result in weaker yarns that may unravel during the spinning process, low fiber maturity is one of the issues facing the textile industry [89]. Research indicates that N is essential for the growth and maturity of cotton fibers. Specifically, Khan et al. [90] demonstrated how appropriate N treatment can encourage fiber growth and development, leading to full maturity. The physiological, biochemical, and morphological processes of plants are connected to the interaction between N and MAT [91]. N affects the production of cellular substances like cellulose and lignin, which are essential parts of cotton fibers’ cell walls. A sufficient supply of N can promote the deposition of these substances, resulting in a thicker cell wall and, ultimately, higher fiber maturity [90]. It is important to remember, nevertheless, that cotton plants’ reactions to N might differ based on several variables, including the type, time, and dosage of fertilizer applied, as well as the particular soil, soil amendments used, and climate [32]. In addition, according to previous research, high N dosages might cause excessive vegetative growth at the expense of fiber development, which lowers fiber quality and reduces MAT [85].

The findings’ assessment demonstrates how important fiber elongation (ELG) is for creating high-quality textile products. The current study found that the increasing rates of both examined factors had a favorable effect on ELG, with the greatest values observed in 7.5 t ha⁻¹ zeolite (11.44%, 10.98%, and 11.43% in ATH, MES, and KAR, respectively) and N fertilization at a rate of 200 kg N ha⁻¹ (11.17%, 10.67%, and 11.93% in ATH, MES, and KAR, respectively) (Table 8), ranking in the category of very high ELG (>7.6%). Fibers with greater ELG are best suited for creating higher-quality textile products because they enhance tensile characteristics, reducing the likelihood of breakage and yarn flaws [42]. Longer fibers with higher mechanical strength can be produced by encouraging ELG during the cotton growth cycle with adequate N availability [92]. Furthermore, plants’ production of proteins and carbohydrates—two crucial building components of cotton fibers—can be impacted by N fertilization [93]. Previous research proved that applying N in sufficient amounts can greatly boost the synthesis of structural proteins in fibers, which in turn helps to improve the fibers’ strength and flexibility [85,93].

The results of the fiber strength (STR) are shown in Table 8. As with MIC, MAT, and ELG, STR presented a similar positive trend after the application of zeolite and N fertilization, presenting significant variation among fertilized and unfertilized plants. This difference between treated and untreated plants emphasizes how essential and intricate nutritional management is. The weaving process, quality, and productivity are all much enhanced by the fiber’s strength, which also increases its commercial value [94]. It has been proved that the ELG and thickness of the cell wall control the fiber STR [95]. Cell elongation and cellulose production from the secondary cell wall essentially mediate fiber STR and length, which are the most important quality attributes for the industry [94]. Therefore, for the utilization of this crop in the textile industry to continue to grow, research showing nutritional management techniques that can improve fiber STR and length is crucial.

The four stages of differentiation and development—initiation, elongation, secondary cell wall synthesis, and maturity—define fiber length, a variable that is primarily governed by gene expression [95]. However, since the fibers’ elongation occurs during the anthesis phase, cultivation practices that encourage the development of flower buds also have an indirect impact on the differentiation process [96]. In light of this, the current study’s findings support the notion that increasing N enhances fiber length. As observed in Table 9, the increasing rates of both examined factors had a favorable effect on upper half mean length (UHML), with the greatest values observed in 7.5 t ha⁻¹ zeolite (29.73, 29.21, and 30.83 mm in ATH, MES, and KAR, respectively) and N fertilization at a rate of 200 kg N ha⁻¹ (29.17, 28.67, and 30.80 mm in ATH, MES, and KAR, respectively).

The uniformity index (UI) also has a similar trend to UHML (Table 9), showing increasing values as zeolite and N fertilization rates increased. This finding would suggest that N fertilization enhances the structural and chemical composition of the secondary cell wall, favoring the fiber’s characteristics [95]. Accordingly, optimal N supply circumstances encourage better cotton development and fiber quality, but a lack of this element can restrict cell division and expansion [97]. In addition, cultural methods such as fertilization and cultivar-specific factors might affect the typical uniformity of fiber length. Furthermore, the textile sector depends heavily on this consistent length distribution, and as it has been demonstrated, using N has improved length uniformity [97].

Zeolite addition at a rate of 5 t ha⁻¹ and N fertilization at a dose of 100 kg N ha⁻¹ have the best short fiber index (SFI) values (Table 9), with the textile industry accepting values below 10% [85]. However, the fibers were deemed to have limited economic potential because zeolite addition and N fertilization at rates of 7.5 t ha⁻¹ and 200 kg N ha⁻¹, respectively, showed values greater than 10%. According to Elmogahzy and Farag [94], a large proportion of short fibers produces yarns with varying thicknesses that break in the weakest and thinnest areas throughout the spinning and weaving operations.

In the present study, lint percentage, MIC, MAT, STR, and ELG all showed positive relations (Figure 3). Additionally, UHML and UI (r = 0.726, p < 0.001), as well as ELG and SFI (r = 0.549, p < 0.001), showed favorable associations (Figure 3). The positive correlations recorded highlight the simultaneous effect of the examined factors on the development and fiber quality of cotton.

Fiber reflectance (Rd) is used to estimate the color brightness of cotton lint [47]. Both of the factors under investigation had a significant impact on Rd in this study. The highest zeolite and N fertilization rates were positively associated with higher values for Rd (Table 10). According to previous studies, the growth environment [98], planting date and genotype [99], and harvesting methods [100] are all directly related to the color of the fiber and its reflectance. In contrast to our study, previous research demonstrated that applying N causes denser canopies, rank growth, and enhanced vegetative growth, which lowers light intensity and increases insect secretions and attractiveness [100].

As for the spinning consistency index (SCI), a measure for predicting the overall quality and spin ability of cotton fiber, this was also positively affected by zeolite and N fertilization (Table 10). Specifically, at ATH and KAR, the highest rates of examined factors resulted in values of SCI higher than 150, and consequently, their fibers are characterized by the highest grade level of the SCI as A++ [48]. In line with SCI variations in earlier research, higher SCI values at ATH and KAR environments may be associated with climatic (temperature and precipitation) variability [32].

Finally, cotton trash traits, specifically trash area (TrAr) and trash grade (TrID), were dominantly affected by zeolite and N fertilization, except N fertilization on TrID, where the differences among different regimes were not significant (Table 10). In general, there was a tendency for these traits to increase with the increase in the rates of the examined factors. According to the literature, these traits are affected by both environmental factors and cultivation methods [44]. Late blooming, in particular, regrowth, will result in issues with cotton’s fiber quality both directly (as indicated by decreased MIC and increased neps) and indirectly (as indicated by lower grades and higher trash content) [44]. At the same time, inadequate and delayed defoliation can significantly affect the quantity of leaf trash [101]. Severe weed competition in cotton, however, can have detrimental consequences on both trash contamination and fiber quality. Furthermore, plucking and defoliation procedures may be hampered by excessively high N rates that result in late regrowth. Late-season insects are supported by unnecessary and late-season rainfall, which can lower production and quality. Leafy crops can also cause boll rot in humid or rainy conditions [102].

5. Conclusions

As a result of the present study, both zeolite treatments and different N fertilizer rates had an essential impact on soil quality indicators. SOM, STN, and TP were favorably impacted by the factors studied and increased, but MWD showed the opposite trend when zeolite was added to the soil. As for root and shoot development (RLD, plant height, LAI, and dry weight), and cotton yields (seed cotton yield, lint yield, and lint percentage), both factors were positively influenced, and the greatest results were obtained at the maximum examined rate of the evaluated treatments. In terms of yield components, boll weight was also favorably impacted by the factors under investigation. Significantly higher fiber maturity traits (MIC, MAT, STR, and ELG), fiber length traits (UHML, UI, and SFI), as well as color (Rd and SCI) and trash traits (TrAr and TrID), were found in cotton plants that received the highest zeolite rate. A similar trend was also presented in all fiber quality parameters in the case of N fertilization, except TrID, where the differences among N fertilization regimes were not significant. In conclusion, the results of the current investigation indicate that raising the rates of zeolite and N fertilization to 7.5 t ha⁻¹ and 200 kg N ha⁻¹, respectively, improved soil properties (except MWD), stimulated crop development, and enhanced cotton and lint yield, as well as improved the fiber maturity, length, and color parameters of cotton grown in clay-loam soils under Mediterranean conditions. However, a longer-term study is needed to evaluate the seasonality and the long-term effects of zeolite addition as a viable, sustainable alternative or supplement to synthetic fertilizers on soil properties and cotton crop performance under these or different agroclimatic conditions.