Relationship of Selected Soil Properties with the Micronutrients in Salt-Affected Soils

Abstract

The present study aimed to assess the relationship of soil properties in salt-affected soils. The soil samples were collected from 14 districts of Pakistan. Soil salinity and sodicity are the common features of the arid and semiarid regions. The effects of the salt’s interactions with soil micronutrients have not been well studied. Therefore, saline and non-saline soil samples were collected from different locations. The microelements (Fe, Cu, Mn, and Zn) were fractionated into water-soluble, exchangeable, carbonate, Fe + Mn oxide, organic, and residual fractions. Univariate and multivariate analysis (PCA) was carried out to determine the linear relationship between soil properties and micronutrients fractions. Results showed that the magnitude of micronutrients appeared to be affected by the salinity in soils. In saline soil, the Fe fractions differed in the order of residual > organic bound > Fe + Mn bound > carbonate bound > exchangeable > water soluble. Iron fractions varied in the non-saline soils as residual > Fe + Mn bound > organic bound > exchangeable > carbonate bound > water soluble. Copper concentration was higher in the residual and carbonate forms, and the amount was lower in the exchangeable and water-soluble forms under both saline and non-saline conditions. The water-soluble Mn fraction was lower, and the residual Mn fraction was proportionately higher than other forms of Mn in soils. Zinc was found mostly in the residual fraction in both saline and non-saline soils. The mobility factor of micronutrients in non-saline soil was greater than in saline soil. PCA revealed that organic matter (OM) and pH directly affected the fractionation of Cu, Mn, Zn, and Fe in soil. Thus, it could be inferred that salts can bring changes to the composition of micronutrients depending on the nature of the soil and the magnitude of salts.

1. Introduction

Micronutrient deficiency in soils is one of the significant problems at the regional and global level affecting more than two billion people [1,2]. Though the chemical fertilizer has made a significant contribution to the continuous supply of nutrients, it has imbalanced the concentrations of micronutrients in the soil [3]. The availability and transformation of micronutrient fractions in the soil are affected by the physicochemical properties of the soil and the cropping system. In soil, essential elements such as copper (Cu), zinc (Zn), iron (Fe), and manganese (Mn) are present in different chemical forms [4]. These elements are required for plant growth and act as a cofactor. Plants utilize these micronutrients for the metabolism of lipids, proteins, and carbohydrates [5]. The reported concentration of Fe, Zn, Mn, and Cu per kg of agricultural soil range between 20,000–50,000 mg, 10–300 mg, 450–4000 mg, and 2–100 mg, respectively [6,7]. Fluctuation in micronutrients in soils is a global phenomenon and caused by several governing factors that affect the movement and transformation of these elements in soils such as organic matter content, pH, salinity, and exchangeable capacity [8,9,10]. It is essential to determine different fractions of nutrients found in the soil since the transformation and bioavailability of these elements are dependent upon the chemical and physical processes in the soil.

In arid and semiarid regions, salinity in soil and water has been considered a severe problem adversely affecting plant growth and nutrient availability. In agricultural productivity, salinity and sodicity reduced the availability of water, uptake of nutrients including both micro and macronutrients, and enhanced the toxicity of Na and Cl ions [11]. Furthermore, saline and sodic soils contain a higher concentration of Na and Cl ions that increase the ratio of Na to Ca, Na to K, and Na to Mg concentrations in plant tissues, resulting in a nutrient deficiency in plants [12]. Salinity and micronutrient deficiency have a complex interaction that has been poorly understood [13]. There is competition between the cations in soil that results in lower uptake of micronutrients in saline soil. In saline and sodic soils, the bioavailability and solubility of the micronutrients are extremely low. Thus, the crops grown on such soils are deficient in micronutrients [14]. Salt stress also affects the bioavailability of other essential nutrients depending upon the soil’s pH and ionic strength of the solution [15].

In the soil-plant systems, the nutrient distribution depends upon soil properties that make it available for a crucial role in the bioavailability of nutrients. In addition, different chemical forms of the micronutrients differ in their availability to plants. Soil factors such as soil pH, percentage of organic matter, redox potential and conditions, and chemical forms of micronutrients affect the bioavailability and mobility of micronutrient fractions in soil [16,17]. The fractionation of the micronutrients provides better information than the single extraction method, e.g., the fraction available for plant uptake [18]. The water-soluble, exchangeable, carbonate, oxide, and organic fractions are known as non-residual fractions. The higher recovery of elements in the form of these fractions indicates their high mobility in soils and availability to plants [19]. In contrast, a fraction such as residual is considered immobile. The amount of recovery of elements in this fraction shows low mobility and unavailability to plants [20,21]. The fractionation of micronutrients in saline soils is vital to understanding the micronutrient’s behavior, mobility, and bioavailability. Several extraction methods have been proposed for the extraction of micronutrients [22,23,24], but Tessier et al. [22] categorized the micronutrient fractions in water-soluble (WO), exchangeable (E), carbonate-bound (CA), iron-manganese oxide-bound (FeMnOX), organic matter-bound (OM), and residual (RES) forms. Micronutrients present in the form of water-soluble and exchangeable are considered bioavailable forms while the residual form is considered an unavailable form.

Physicochemical properties of soil-controlled metal association and its fractionation in soil were studied in [25]. To assess the relationship of metal fractions with soil properties, multivariate methods such as principal component analysis (PCA) are preferred over the univariate method [26]. Therefore, PCA has been used to determine the influence of soil physicochemical properties, distribution of the metal fractions in soils, and the linear relationship between them [27]. It is helpful for the identification of significant data sets and variables and interaction between data sets [28]. The fractionation of different soil nutrients differ in bioavailability depending upon the structure and properties of the soil. Previous studies have been focused on the availability of different fractions of metals in soils [28,29,30]; still, the literature is insufficient on the comparison of metal fractionation in saline and non-saline soil.

Much of the research on saline and non-saline soil has been focused on the availability of major nutrients and the effects of salinity on crop production [31,32,33], whereas the information on the fractionation of micronutrients in saline and non-saline agricultural soils are scanty. It has been hypothesized that salinity affects the mobility and availability of micronutrients in the soil. Therefore, it is essential to understand the impact of salts on nutrient availability in soils. The fact is that large amounts of soluble salts are continually being introduced into the soils in the arid and semiarid regions. The relationship between salinity and micronutrients is complex, and an understanding of these interactions is still required [19]. Therefore, this study aimed to investigate the availability of micronutrient fractions in both saline and non-saline soils under varied physicochemical characteristics.

2. Materials and Methods

2.1. Study Area

Pakistan is located in an arid and semiarid climate zone, with about 6.3 million hectares of land affected by salt. The salt-affected soils are primarily found in Chardsada, Khewara, and Bhalwarpul areas. Due to the poor irrigation practices and high evapotranspiration rate, agricultural soils are facing severe problems of salinity [34]. In general, high evapotranspiration in arid and semiarid regions is the root cause of soil surface salinity accumulation. The average temperature in summer and winter ranges between 2 °C and 40 °C while annual precipitation across the country varies between 100 to 1500 mm [35]. Evaporation rates are usually very high, exceeding the precipitation rate, thus enhancing the movement of salt toward the soil surface [36].

2.2. Soil Sampling

A total of 70 soil samples (taken from a 0–20 cm depth), representing different salinity levels, were collected from 14 arid and semiarid agricultural areas of Pakistan during the spring season of 2019 (Figure 1). Soil samples were collected from agricultural lands that are under different types of crop cultivation.

2.3. Soil Analysis

Soil samples were air-dried, sieved via a 2 mm sieve, and characterized for physicochemical properties. The samples were processed and analyzed in triplicates. Soil pH and electrical conductivity (EC) were measured in soil water solution (1:5) using a pH meter and EC meter (model: HANNA HI 8520). One molar ammonium acetate solution (NH₄OAc) (pH 7) was used for the extraction of exchangeable cations, and the contents were determined using an atomic absorption spectrophotometer (model: Analyst 700, Perkin Elmer, Waltham, MA, USA). Total carbon was determined via the loss-on-ignition method [37]. Total nitrogen was determined by the Kjeldahl method. Bicarbonates and chlorides were determined by the standard titration method. Tressier et al. [22] sequential extraction method of micronutrient fractionation in soil were used. The microelements were fractionated into water-soluble, exchangeable, carbonate, Fe + Mn oxide, organic, and residual fractions in soil samples as detailed in

Table 1. Tessier et al. [22] extraction method.

	Reagents	Soil (g)	Solution Volume (mL)	Fractionation Process	Fraction Type
1.	Water (pH = 7)	5	50	The sample was shaken in a beaker for 1 h at 200 rpm and then filtered and centrifuged.	Water-soluble
2.	(NH4COOCH3) solution (pH 7.0)	Residue from step 1	40	The residue from the above was extracted with 40 mL of ammonium acetate and shaken for 1 h at 200 rpm at room temperature. After centrifugation, the supernatant solution was filtered and analyzed.	Exchangeable fraction
3.	1 M sodium acetate (pH 5.0 with acetic acid)	Residue from above step	40	The soil residue was extracted with 1 M sodium acetate (NaCOOCH3) and adjusted to pH 5.0 with acetic acid (CH3COOH). The suspension was shaken for 5 h.	Carbonate-bound fraction
4.	0.05 M hydroxylamine hydrochloride acetic acid	Residue from the above step	100	To the residue, 100 mL of 0.05 M hydroxylamine hydrochloride was added to 25% (v/v) acetic acid and extracted at 95 ± 2 °C in a water bath, stirred for 6 h. After centrifugation, we washed the residue with 20 mL of water (20 mL), filtered, and washed in combination with the original extract to form a total volume of 100 mL.	Iron-manganese oxide bound
5.	0.02 M HNO3 30% H2O2 (adjusted at pH 2 with HNO3). 3.2 M ammonium acetate	Residue from above	20	The residue from above was extracted with 10 mL of 0.02 M HNO3 and 15 mL of 30% H2O2 (adjusted at pH 2 with HNO3). The mixture was then heated to 85o C for 5 h with occasional agitation. A second 15 mL aliquot of 30% (pH 2 with HNO3) was added and the mixture was heated again to 85o C for 3 h with intermittent agitation. After cooling, 5 mL of 3.2 M ammonium acetate (NH4COOCH3) in 20% HNO3 (v/v) was added, and the samples were diluted to 20 mL and agitated continuously for 30 min. After centrifuging, the residue was washed with 20 mL of water, and the washings were added to the extracted solution after filtration to make up a final volume of l00 mL.	Bound to organic matter
6.	Perchloric acid (HClO4), hydrogen fluoride (HF), hydrochloric (HCl) acid	(1 g)	100 mL	The soil sample was taken from the above and treated with 2 mL of 70% perchloric acid (HclO4) and 10 mL of hydrogen fluoride (70% HF) in a platinum crucible. The contents were digested on a hot plate, and when the residue became a paste, 1 mL of HClO4 and 10 mL of HF were added. Again, the contents were digested to near dryness. Finally, 1 mL of HClO4 was added and evaporated again until the appearance of white fumes. The contents were then dissolved in 6 N hydrochloric acid (HCl), filtered, made up to 100 mL, then kept in clean plastic bottles for analytical work.	Residual fraction

.

Soil samples were collected and analyzed in triplicates. Atomic absorption spectrophotometry (AAS) was used to determine the amounts of micronutrients in various extracts. Standards solutions were used for the calibration curve and were verified against the reference solution.

2.4. Exchangeable Sodium Percentage

The exchangeable sodium percentage (ESP) of soil was calculated by the following equation:

$$ESP=\left[\frac{Exch.Na}{CEC}\right]\times 100$$

(1)

where K, Na, Ca, and Mg are in mg kg⁻¹.

2.5. Mobility Factor

The mobility of elements was calculated by using an equation developed by Kabala and Singh [38] and Oluwatosin [18].

Mobility factor (MF) = [water soluble + exchangeable/carbonate bound + Fe-Mn oxide bound + organic matter bound + residue) × 100]

2.6. Statistical Analysis

Statistical analyses were performed using the ORIGIN 2021 software package, where mean comparisons were performed using the least significant difference at p < 0.05. Principal component analyses (PCAs) were performed for the distribution of the data from saline and non-saline soil. The relationship between micronutrients and ESP was determined by Pearson’s correlation.

3. Results and Discussion

3.1. Soil Properties and Classification

The soil collected from the different agricultural areas was classified into saline and non-saline soils based on soil properties, i.e., EC, pH, and ESP (

Table 2. Classification of soil based on soil pH, EC, and ESP. Bastida et al. [39].

Classification	Electrical Conductivity (d S m−1)	pH	Exchangeable Sodium Percentage (ESP)
Normal	<4.0	<13	<15
Saline	>4.0	<8.5	<15
Sodic	<4.0	>8.5	>15
Saline sodic	>4.0	<8.5	>15

).

The pH of the non-saline soils ranged from 8.14 to 8.63, irrespective of the soil sample. Saline and sodic soils showed higher pH ranges (8.15 to 9.59). ESP values varied significantly and ranged between 3.2% to 21.9%. Soil collected from Charsada (21.1%) obtained the highest ESP value followed by the Kewara area (21.9%), indicating sodification in soils. Low ESP values were found in the non-saline soil of the Mansehra area (2.2%). Organic matter (OM) and total N and P contents in the non-saline soil were higher, while lower organic carbon contents were observed in the saline soil (

Table 3. Geochemical analysis of selected soils.

Soil Type	Sampling Area	pH (1:10)	EC	ESP	CEC	OM	Residual Fe	Residual Cu
			dS m−1	%	cmolc kg−1	%	mg kg−1
Saline	Bahawalpur	8.27 ± 0.5	4.50 ± 0.1	16.43	1.86 ± 0.4	1.8 ± 0.2	85.4 ± 2.6	98.6 ± 3.6
	Charsada	8.6 ± 0.2	7.18 ± 0.6	18.69	1.93 ± 0.1	0.5 ± 0.01	75.1 ± 3.5	92.0 ± 2.5
	Gujranwala	8.17 ± 0.4	5.16 ± 0.1	10.76	1.45 ± 0.2	1.3 ± 0.5	49.9 ± 4.1	66.4 ± 4.6
	Khewra	9.59 ± 1.2	8.53 ± 0.2	21.85	2.24 ± 0.9	0.6 ± 0.01	45.3 ± 3.2	75.6 ± 2.9
	Mian channu	8.15 ± 0.9	4.81 ± 0.7	20.65	1.82 ± 0.3	1.6 ± 0.3	63.9 ± 2.5	80.2 ± 3.6
	Mianwali	8.44 ± 0.4	4.72 ± 0.8	8.63	2.05 ± 0.95	1.4 ± 0.4	35.6 ± 3.6	91.9 ± 4.3
	Multan	8.16 ± 1.1 i	5.37 ± 0.3	10.81	1.82 ± 0.8	1.98 ± 0.2	52.7 ± 3.3	67.0 ± 2.9
Non-saline	Abbottabad	8.14 ± 1.2	0.16 ± 0.1	3.73	1.28 ± 0.7	1.2 ± 0.1	51.7 ± 2.8	84.9 ± 3.6
	Haripur	8.16 ± 0.8 i	0.15 ± 0.06	6.15	1.18 ± 0.6	1.5 ± 0.05	39.0 ± 2.5	73.9 ± 3.8
	Layyah	8.6 ± 0.2	0.77 ± 0.1	7.79	1.77 ± 0.55	2.45 ± 1.2	38.4 ± 2.3	94.8 ± 3.5
	Mansehra	8.22 ± 0.6	0.18 ± 0.04	8.01	1.35 ± 0.45	3.21 ± 1.3	48.2 ± 2.8	80.1 ± 2.8
	Okara	8.46 ± 0.8	0.39 ± 0.1	7.32	1.96 ± 0.56	2.7 ± 0.2	51.6 ± 3.6	67.4 ± 3.5
	Sahiwal	8.63 ± 0.8	0.45 ± 0.05	7.792	1.77 ± 0.64	2.9 ± 0.9	51.7 ± 3.4	82.4 ± 2.8
	Tobateksingh	8.32 ± 0.9	0.62 ± 0.02	10.2	1.44 ± 0.77	2.5 ± 0.8	58.5 ± 2.5	53.7 ± 3.9
	LSD (0.05)	0.3	0.2	0.5	6.8	1.2	5.9	6.5

).

The lower OM contents in soils could be related to the poor vegetation and the high rate of organic matter decomposition in the salt-affected soils. In non-saline soil, the OM ranged from 1.2 to 3.21%, whereas in saline soil, the OM content varied from 0.5 to 1.98%. Due to the higher OM in non-saline soil, the CEC content was also higher in those soil samples. The Ca, Mg, Na, Cl, and HCO₃ contents were higher in saline than in non-saline soils (

Table 4. Chemical properties of saline and non-saline soils.

Soil	Sampling Area	N	Cl	P	HCO3	Ca	Mg	K	Na
		%	mg kg−1			Cmolc kg−1
Saline	Bahawalpur	1.1 ± 0.2	1.7 ± 0.2	0.4 ± 0.03	5.8 ± 0.8	0.89	0.53	0.12	0.30
	Charsada	2.1 ± 0.2	6.7 ± 0.4	0.26 ± 0.05	5.8 ± 0.4	0.73	0.61	0.22	0.36
	Gujranwala	3.1 ± 0.3	4.4 ± 0.4	0.15 ± 0.04	4.6 ± 0.4	0.71	0.50	0.08	0.15
	Khewra	0.9 ± 0.1	10.8 ± 0.3	0.16 ± 0.02	9.4 ± 0.6	0.89	0.53	0.32	0.49
	Mian channu	0.8 ± 0.1	1.5 ± 0.2	0.4 ± 0.01	5.8 ± 0.4	0.89	0.43	0.12	0.37
	Mianwali	1.9 ± 0.3	3.4 ± 0.3	0.11 ± 0.01	5.1 ± 0.5	1.19	0.57	0.11	0.17
	Multan	1.4 ± 0.2	4.9 ± 0.4	0.13 ± 0.05	4.6 ± 0.3	0.84	0.68	0.09	0.19
Non-saline	Abbottabad	5.5 ± 0.2	0.1 ± 0.01	13.7 ± 0.06	0.3 ± 0.01	0.55	0.55	0.12	0.04
	Haripur	6.7 ± 0.5	0.02 ± 0.01	12.0 ± 0.02	0.2 ± 0.02	0.56	0.38	0.16	0.07
	Layyah	6.4 ± 0.6	2.3 ± 0.2	11.3 ± 0.01	0.4 ± 0.02	0.67	0.70	0.25	0.13
	Mansehra	5.3 ± 0.3	0.01 ± 0.01	13.8 ± 0.04	0.6 ± 0.01	0.71	0.46	0.07	0.10
	Okara	7.1 ± 0.9	1.4 ± 0.1	9.0 ± 0.3	1.8 ± 0.2	0.95	0.74	0.12	0.14
	Sahiwal	5.6 ± 0.4	2.1 ± 0.1	8.6 ± 0.5	0.6 ± 0.01	0.83	0.54	0.25	0.14
	Tobateksingh	6.3 ± 0.6	0.4 ± 0.1	9.2 ± 1.0	4.6 ± 0.5	0.67	0.43	0.17	0.14
	LSD (0.05)	0.2	0.1	0.7	0.1	0.2	0.2	0.13	0.03

).

3.2. Fractionation of Micronutrients in Saline and Non-Saline Soils

Fractions of micronutrients (Fe, Cu, Mn, and Zn) differed among saline and non-saline soils, irrespective of the sampling areas. Soil salinization had a clear effect on microelements in the soil. The Fe fractions differed in saline soil in the order of residual > organic bound > Fe + Mn bound > carbonate bound > exchangeable > water soluble. The Fe fractions varied in non-saline soils as residual > Fe + Mn oxide bound > organic bound > exchangeable > carbonate bound > water soluble (Figure 2).

The micronutrients in non-residual fractions are more likely to be bioavailable than the elements associated with the residual (detrital) fraction. Gujranwala and Charsada areas achieved higher concentrations of Fe in saline soils, whereas Multan and Khewara areas exhibited relatively lower concentrations. Copper was found to be higher in the residual and carbonate forms and lower in the exchangeable and water-soluble forms under both saline and non-saline conditions (Figure 3). These results are in agreement with the findings of Ponizovsky et al. [40], who reported a strong association of Cu with carbonate in the calcareous soils. Adamo et al. [41] reported that 75% Cu is associated with carbonate fractions of soils. Graf et al. [42] reported a greater amount of Cu in carbonate and Fe + Mn oxide fractions. The water-soluble Mn fraction was lower, and the residual Mn fraction was proportionately higher than other forms of Mn in soils (

Table 5. Fractionation of Mn in saline and non-saline soils.

Soil Type	Sampling Area	Water Soluble	Exch.	Carbonate	Fe + Mn Oxide	Organic Bound	Residual
		mg kg−1
	Bahawalpur	7.4 ± 1.2	7.7 ± 2.2	4.6 ± 0.5	2.3 ± 0.3	12.7 ± 1.5	254.2 ± 12.5
Saline	Charsada	24.4 ± 1.5	42.3 ± 3.6	4.3 ± 0.3	6.7 ± 0.9	9.4 ± 1.6	251.9 ± 13.2
	Gujranwala	30.7 ± 1.3	19.2 ± 1.3	88.1 ± 7.9	75.2 ± 6.2	88.7 ± 2.9	299.6 ± 13.6
	Kewara	3.2 ± 1.5	21.7 ± 1.4	24.3 ± 1.2	28.2 ± 1.4	33.5 ± 3.3	253.9 ± 13.5
	Mian channu	6.3 ± 2.2	1.3 ± 0.2	6.9 ± 1.3	5.8 ± 0.4	34.7 ± 2.5	239.4 ± 14.5
	Mianwali	11.7 ± 2.6	41.2 ± 2.3	54.6 ± 2.5	66.7 ± 7.2	73.7 ± 3.2	256.6 ± 13.6
Non-saline	Multan	17.6 ± 1.1	24.9 ± 2.1	103.3 ± 4.4	12.8 ± 1.1	23.9 ± 2.5	227.9 ± 10.5
	Abbottabad	17.2 ± 1.3	21.3 ± 1.5	13.4 ± 1.3	18.9 ± 1.1	28.9 ± 2.5	206.5 ± 14.4
	Haripur	18.5 ± 1.4	27.2 ± 1.5	26.4 ± 1.2	13.5 ± 1.3	13.8 ± 1.2	286.4 ± 14.1
	Layyah	16.4 ± 1.2	20.7 ± 1.8	12.1 ± 1.1	12.2 ± 1.5	11.6 ± 1.6	184.6 ± 13.2
	Mansehra	17.5 ± 1.3	18.7 ± 1.3	19.3 ± 1.1	18 ± 1.5	16.7 ± 1.4	192.6 ± 12.5
	Okara1	8.7 ± 1.2	30.6 ± 1.3	3.4 ± 0.8	3.7 ± 0.9	7.5 ± 2.5	207.8 ± 16.6
	Sahiwal	16.8 ± 1.3	20.2 ± 2.2	12.7 ± 1.3	12.4 ± 1.6	12.7 ± 2.7	169.8 ± 15.2
	Tobateksingh	16.9 ± 1.5	22.8 ± 2.6	3.7 ± 0.2	14.9 ± 1.2	10.6 ± 2.78	248.4 ± 13.6
	LSD (0.05)	1.2	2.3	1.6	1.8	2.8	6.4

). Li et al. [36] reported that around 90% of Cu was associated with the residual fraction of contaminated soils. The speciation of heavy metals using different extractants provides important information about the fundamental reactions governing the behavior of the metals in soils [41,43,44].

The effects of salinity on the extractability of Zn also varied significantly. Zinc was found mainly in the residual fraction in both saline and non-saline soils. Fe + Mn oxide and organic-bound fractions were higher than other fractions of Zn in saline soils. In non-saline soil, Zn concentrations were mostly achieved in the exchangeable and water-soluble forms compared to other fractions. The organic matter bound fraction of Zn was lower, followed by the Fe + Mn oxide and water-soluble fractions. A higher amount of Zn was achieved in the residual form (

Table 6. Fractionation of Zn in saline and non-saline soils.

Soil Type	Sampling Area	Water Soluble	Exch.	Carbonate	Fe + Mn Oxide	Organic Bound	Residual
		mg kg−1
Saline	Bahawalpur	3.1 ± 0.2	8.2 ± 0.5	20.6 ± 2.58	11.9 ± 1.3	21.8 ± 2.1	168.8 ± 3.3
	Charsada	4.9 ± 0.3	26.3 ± 1.2	25.6 ± 2.2	22 ± 2.1	41.9 ± 2.5	209.1 ± 13.4
	Gujranwala	4.4 ± 0.3	15.4 ± 0.2	12.6 ± 0.8	15.3 ± 1.1	40.6 ± 3.3	162.3 ± 13.5
	Kewara	5.3 ± 0.4	11.8 ± 1.1	8.3 ± 0.5	11.5 ± 1.3	0.8 ± 0.2	59.2 ± 5.3
	Mian channu	3.1 ± 0.2	9.9 ± 1.1	3.7 ± 0.5	17.4 ± 1.3	2.2 ± 0.36	191 ± 12.8
	Mianwali	5.5 ± 0.2	4.8 ± 0.6	6.2 ± 1.2	8.2 ± 1.5	1.4 ± 0.4	43.3 ± 4.2
	Multan	1.7 ± 0.3	9.4 ± 0.5	16.3 ± 1.1	16.1 ± 1.3	1.1 ± 0.4	78.2 ± 8.1
	Abbottabad	15.4 ± 0.8	26.5 ± 1.2	10.9 ± 1.2	3.0 ± 0.5	0.6 ± 0.1	224.8 ± 18.2
	Haripur	19.1 ± 2.1	36.6 ± 2.6	18.4 ± 1.3	1.3 ± 0.2	0.2 ± 0.01	324.0 ± 19.4
	Layyah	9.9 ± 1.1	35 ± 2.87	14.2 ± 1.8	1.9 ± 0.3	1.5 ± 0.2	271.9 ± 10.9
Non-saline	Mansehra	15.6 ± 1.8	29.4 ± 2.4	15.3 ± 1.5	1.3 ± 0.4	0.2 ± 0.03	262.4 ± 13.3
	Okara1	7.2 ± 1.3	35.9 ± 3.4	5 ± 0.5	2.1 ± 0.3	2.3 ± 0.2	321.1 ± 13.5
	Sahiwal	12.6 ± 1.2	26.5 ± 2.6	9.6 ± 1.4	2.1 ± 0.2	1.7 ± 0.2	320.6 ± 20.1
	Tobateksingh	12.3 ± 2.3	26.1 ± 2.5	9.6 ± 1.2	2.3 ± 0.77	1.9 ± 0.3	256.1 ± 12.2
	LSD (0.05)	1.3	2.4	1.2	0.3	0.3	6.8

). Availability of micronutrients to plants is regulated by soil pH, the salt concentration in the soil solution, organic matter content, crop species and genotypes within species, salinity level, and salt composition. The interactions of micronutrient availability in salt-affected soils are extremely complex. The magnitude of micronutrient release appeared to be affected by the salinity or the salt-induced pH changes. Salt accumulation in soils affects the availability of nutrients in saline soils either by changing the form of nutrients in the soil, precipitation, or interactions among nutrient elements and non-essential salts. The lower amounts of available fractions of micronutrients in saline soil could be related to the lower amount of organic matter in saline soils. The distribution of metal among specific forms varies widely based on an element’s chemical properties and characteristics [45,46,47].

3.3. Mobility Factor (MF)

An element’s mobility in soil is determined by the mobility factor (MF). The mobility factor of micronutrients in soils showed differences in their values in both saline and non-saline soils. Irrespective of the element, the MF of micronutrients in non-saline soil was greater than in saline soil. It indicated that the micronutrients were less available to the plants in the saline soil. In saline soils, the MF for micronutrients was found in the order of Fe > Mn > Zn > Cu (

Table 7. Mobility factor (%) of micronutrients under saline and non-saline conditions.

Soil	Fe	Cu	Mn	Zn
Saline/sodic soil
Bahawalpur	5.1 i	5.5 k	5.5 j	5.1 k
Charsada	10.4 h	8.7 h	10.5 g	10.4 g
Gujranwala	8.6 j	8.5 h	9 h	8.6 i
Khewara	21.4 a	4 l	7.3 i	15.4 c
Mian channu	6.1 k	7.6 i	2.6 k	6.1 j
Mianwali	17.4 b	7.1 j	11.7 f	10.4 g
Multan	9.9 i	8.4 h	11.6 f	9.9 h
Non-saline soil
Abbottabad	17.5 b	17.9 e	14.4 cd	17.5 a
Haripur	16.2 c	25.3 a	13.4 e	16.2 b
Layyah	15.5 d	11.7 g	16.8 b	15.5 c
Mansehra	16.1 c	23.2 c	14.7 c	16.1 b
Okara	13 f	19.1 d	17.7 a	13 e
Sahiwal	11.7 g	14 f	17.8 a	11.7 f
Tobateksingh	14.2 e	23.6 b	14.3 d	14.2 d

Note: Alphabets indicate the statistical difference among metal fractions.

). The mean value of MF varied as Cu > Mn > Zn > Fe across all non-saline soils. The value of the mobility factor for micronutrients provides information about their potential mobility in soils and availability to the plants [36]. The value of MF up to 10% for any element indicates that this element is highly immobile and unavailable for plants [48].

3.4. Relationship of EC Values vs. Mobility Factor

For the relationship between micronutrients (Cu, Zn, Fe, and Mn) and their availability in saline and non-saline soil, Pearson’s correlation was used between ESP and MF of micronutrients. The ESP of soil was negatively related to the MF of micronutrients, since the degree of availability of micronutrients differed in order of Zn > Cu > Fe > Mn. This indicated that higher ESP significantly retards the mobility and availability of micronutrients (Figure 4). Similar results were observed by Carbonell-Barrachina et al. [49], Shibli et al. [50], and Swarup [51].

3.5. Multivariate Analyses

A PCA model was used to analyze the relationship between selected soil properties and fractions of the elements. A biplot was created of the first two principal components from PCAs (Zn, Fe, Mn, and Cu) of soil metal fractions (water soluble (WS), exchangeable (E), carbonate bound (Carb-B), iron-manganese oxide (Fe-MnO), organic matter bound (OM-B), and residual (Res)) and selected soil parameters (OM, pH, ESP, and EC) (Figure 5). The biplot of all four micronutrients showed the highest percentage of the total variance. In the case of Fe, pH, EC, and ESP was close with an exchangeable fraction which indicated a relationship between these variables and a moderate relationship with carbonate-bound and iron-manganese-bound fraction while the OM showed an inverse relationship with organic-bound and water-soluble fraction. It was reported that exchangeable and acid extractable fractions of Fe are normally low due to formations of their respective hydroxide and oxides in certain conditions. Fe fractions and their transformation in the soil is controlled by redox potential and pH [7]. Under aerobic conditions, Fe is found in an organic-bound complex rather than an inorganic ion [52,53]. A similar distribution pattern is shown by iron obtained as an acid-extractable fraction. Tessier et al. [22] stated that Fe bound with carbonates and metals can only be extractable by acid. For a biplot of micronutrient fractionation for the area and cumulative variance, see supplementary information.

Copper tends to form an inner sphere complex with OM as compared to other alkali metals [54,55]. For the Cu, OM in soil showed a positive relationship with the exchangeable fraction and water-soluble fraction while the pH showed a positive relationship with the residual and Fe-Mn oxide fraction. ESP and EC showed a negative relationship with the exchangeable fraction, and a positive relation with the water-soluble, carbonate-bound, and organic matter-bound fractions was noted. Due to the formation of an organic metallic complex, Cu remained in an immobile condition [56]. Therefore, Cu remained in a non-exchangeable fraction and its availability in soil remained very low. Ma and Rao [57] evaluated Cu fractionation in nine soils and observed the Cu fractions in following sequences: residual > organic bound > Fe + Mn oxide bound > carbonate bound > exchangeable > water-soluble.

In the case of Zn, OM and water-soluble fractions were close to each other, showing a stronger association, while exchangeable and residual fractions showed a moderate relationship with OM. EC and ESP showed an inverse relation with the water-soluble, exchangeable, and residual fractions while soil pH was mainly associated with the carbonate bound, Fe-Mn oxide-bound, and OM-bound fraction of Zn. Zinc deficiency is a common problem in soils where the pH of the soil medium is high and has low availability of the metal content and organic matter [58,59]. The bioavailability of Zn is controlled by pH, CEC, and organic matter. Most of the bioavailable Zn concentration is adsorbed on the mineral surface and complexes with organic matter [60]. Different organic compounds such as aliphatic and aromatic hydrocarbons play an important role in forming soluble complexes in soil [41]. These organic complexes of Zn are pH and metal-content-dependent. Alvarez et al. [24] predicted a very small fraction of organic complexes of zinc in the soil at low pH. Zhu et al. [61] reported that Mn is mainly associated with FeMnOX in calcareous soils.

Several factors affect the availability of Mn fraction in soil and are governed by pH, redox potential, OM content, and CaCO₃ content [62]. For Mn, soil OM, ESP, and EC showed an inverse association with organic bound and residual fractions while the pH showed an inverse relationship with the rest of the fractions. An inverse effect of pH on the Mn availability was reported. Therefore, with the increase in pH, the availability of Mn decreased [42,43]. The surface of fine-textured soils may adsorb the Mn fractions, which make up a significant portion of soil surface area [49]. During decomposition, organic matter releases organic acids which lower the pH and increase the availability of Mn in soil. Thus, Mn can only be available under favorable circumstances; otherwise, it remains in the locked form.

4. Conclusions

The present study ascertained the relationship between soil properties and micronutrients in salt-affected soils. The extractability of micronutrients, i.e., Cu, Mn, Zn, and Fe in the salt-affected soil was evaluated. ANOVA showed that the fraction of micronutrients varied substantially. Multivariate analysis (PCA) confirmed that Mn, Cu, Zn, and Fe fractions in soil were controlled by the pH and OM contents of the soil. Thus, the differences in the extractable fractions of micronutrients occurred due to the presence of salts in the soils. Iron fractions differed in saline soils in the order of residual > organic bound > Fe + Mn bound > carbonate bound > exchangeable > water soluble. These fractions varied in the non-saline soils as residual > Fe + Mn bound > organic bound > exchangeable > carbonate bound > water soluble. Copper concentration was higher in the residual and carbonate forms, and the amount was lower in the exchangeable and water-soluble forms under both saline and non-saline conditions. The water-soluble Mn was lower, and the residual Mn was proportionately higher than Mn forms in soils. Zinc was found mostly in the residual fraction in both saline and non-saline soils. The mobility indices of micronutrients in non-saline soil were greater than in saline soil. The mobility of micronutrients in soils was found in the order of Zn > Cu > Fe > Mn. Pearson’s correlation showed that MF and ESP were correlated negatively, hence higher ESP in soils decreased the mobility of selected micronutrients in soil. This study indicated that the composition of micronutrients varied in saline soils depending on soil properties, i. e., pH, OM, ESP, and EC.