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Article

Modeling of P-Loss Risk and Nutrition for Mango (Mangifera indica L.) in Sandy Calcareous Soils: A 4-Years Field Trial for Sustainable P Management

1
School of Biological and Environmental Engineering, Guiyang University, Guiyang 550005, China
2
Department of Biology, Faculty of Science and Arts, King Khalid University, Mohail 61321, Assir, Saudi Arabia
3
Soils, Water and Environment Research Institute, Agricultural Research Center, Giza 12112, Egypt
4
Haikou Experimental Station, Chinese Academy of Tropical Agricultural Sciences (CATAS), Haikou 571101, China
5
College of Resources and Environment, Hunan Agricultural University, Changsha 410128, China
6
Departments of Soils and Water, Faculty of Agriculture, Assiut University, Assiut 71526, Egypt
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Horticulturae 2022, 8(11), 1064; https://doi.org/10.3390/horticulturae8111064
Submission received: 18 October 2022 / Revised: 10 November 2022 / Accepted: 11 November 2022 / Published: 13 November 2022

Abstract

:
The continuous addition of phosphorus (P) fertilizers above plant requirements increases P loss risks, especially if such fertilization practices continue long-term. The current study aims to determine the threshold value of P in plants and soil, which achieves the maximum mango fruit yield without P loss risk. P fertilizer doses (0–240 g tree−1) were added to 12-year-old mango (Mangifera indica L.) cv Hindy planted in sandy soil for four consecutive years. Soil and plant samples were collected each year to estimate the critical p values by linear–linear, quadratic, and exponential models. The relationships between fruit yield and available soil P were positive and significant in all the mathematical models. Mango fruit yield is expected to reach its maximum value if the sandy calcareous soil contains an available P amount ranging between 10–12 mg kg−1 and increasing the soil available P above this level leads to negligible increases in the fruit yield. Increasing the available soil P above 20.3 mg kg−1 increases P-loss risk. P concentrations in blades and petioles of mango leaves can be arranged as follows: beginning of the flowering stage > the full blooming stage > beginning of the fruiting stage. The analysis of petioles of mango leaves in the beginning of the flowering stage significantly corelated with mango fruit yield and can be used in predicting the response of mango to P fertilization. The findings of the present investigation revealed that the critical P in mango petioles ranged between 2.34 and 3.53 g kg−1. The threshold of available soil P for maximum fruit yield is half of P loss risks. The combined analysis of soil and plants is a powerful diagnostic tool for P management in sandy degraded soil. The findings of the current study are a good tool in achieving the optimum utilization of P fertilizer resources in maximizing mango fruit yield and reducing the risks of environmental pollution that result from excessive fertilization doses.

1. Introduction

Mango plants belong to the Anacardiaceae family and are considered one of the most important fruit trees, especially in tropical and subtropical climate zones [1]. Mango can be grown in arid and semiarid regions where other crops cannot thrive due to poor soil quality and harsh weather [2,3]. Mango is one of the fruits that is of particular importance in the tropical and subtropical regions due to its high nutritional value and unique taste, resulting in its significant contribution to increased exports and income, as the global production of it reached about 56 million tons in 2020 [4]. It is possible to expand the cultivation of mango, especially in the sandy soils that are spread in many arid conditions. Newly reclaimed soils are obligatory to provide food for an increased population. Nevertheless, the newly reclaimed soils in most cases have a high content of calcium carbonate, coarse texture, low fertility, and organic matter content [5]. The effective fertilization management through determining the optimal dose of fertilizer can be a good strategy for the arid degraded sandy soils.
P is an essential macronutrient and is added to soil in organic or inorganic forms to provide plants with their requirements [6]. The global use of P fertilizer has raised from 4.6 to 21 million tons during the last fifty years (1970–2020) and it is expected that the demand for P fertilizers will reach 26–39 million tons P year−1 by 2050 [7,8]. Many researchers have stated that the demand for P fertilizers will reach its peak in 2030 and that the earth’s stock of raw phosphates may be depleted during the next 70 to 300 years [9]. Therefore, the preservation of this non-renewable natural resource requires the development of fertilizer policies that are compatible with sustainable development and the preservation of the ecosystem [8]. Huge amounts of P fertilizer have been added to the soil to increase P availability and crop productivity; however, excessive phosphate fertilization has increased the risks of surface run-off and environmental pollution [10]. The amount of phosphate rock available for the manufacture of phosphate fertilizers is limited, as it is a non-renewable resource and therefore consumption must be rationalized [11,12]. Now, there are many methods that are used to predict the risks of P loss from soil to environmental ecosystems [13,14]. The degree of phosphorus saturation (DPS) is widely used for predicting P mobility and P loss from soil [13,14,15]. DPS is estimated from P bound to reactive aluminum (Al) and iron (Fe) oxides by the extraction with ammonium oxalate (pH 3) [16]. Jalali and Jalali [13] and Kleinman and Sharpley [17] have indicated that the method of ammonium oxalate often is highly correlated to DPS in alkaline soils. The Olsen [18] method is one of the most recommended methods for extracting available P from calcareous soils [14,19], but there is little information about the relationship of P extracted by this method and the risks of P runoff. Therefore, this study aims to study the relationship between phosphorus extracted by the Olsen method and the potential environmental risk of P loss.
Critical soil P refers to soil available P which produce the maximum yield and where potential increase is negligible [20]. The threshold of available soil P depends on plant species, soil type, and environmental conditions [6]. Extraction of the available soil P mainly depends on the top soil layer and may not represent the actual value of P, which makes the soil P test alone a poor prediction method for fertilization management [6,21]. Phosphorus management for optimum plant growth should depend on both plants and soil analysis [21,22]. Combined analysis of soil and plant tests is an effective diagnostic method to predict nutrient requirements [22,23]. P concentration in plant tissue varies according to soil fertility, environmental conditions, plant growth stage, plant species, and sampling method [22,23]. The concentration of P in plant tissues is the final result of the state of the element in the soil and all the factors affecting plant growth, and therefore it may serve to predict the need for plants to fertilize [21,24].
The use of phosphate fertilizers in each agricultural season to supply plants with their phosphorus requirements will lead to environmental pollution and profit reduction if fertilizers are added at rates higher than the plant requirements [25]. The available information about the response of mango trees to P nutrition is scarce, especially in calcareous soils. Consequently, the P threshold to obtain the highest mango fruit yield needs to be investigated. Furthermore, the study aims to predict the critical soil and plant p values for maximum mango fruit yield by different mathematical models. The current study also aims to study the possibility of using available soil p values to predict P loss risks.

2. Materials and Methods

2.1. Experimental Site and Treatments

The field studies were conducted for four years (2018–2021) on a private mango orchard in Assiut, Egypt (27.05 N and 31.32 E). Mango (Mangifera indica L.) cv 12-year-old Hindy was planted at 3 × 5 m2 with a plant density of 666 plant ha−1. The farm was irrigated with a drip irrigation system at a rate of 20 m3 for each tree during the whole season. The soil of the experimental site is a sandy soil and is classified as Calcisols [26]. The studied soil contains 24% CaCO3, 0.3% organic matter, a pH of 8.21, and an available P of 4.5 mg kg−1. Soil properties were determined in soil samples (0–50 cm) collected in the first year. The maximum temperature (Tmax) of the experimental site during the experiment period is ranged between 28 and 34 °C, the minimum temperature (Tmin) is ranged between 15 and 20 °C, and the relative humidity range is between 40 and 45%, while the rainfall was zero. The experiment contained 9 doses of P fertilization, i.e., 0, 30, 60, 90, 120, 150, 180, 210, and 240 g P tree−1. The source of P was superphosphate (6.5% P), which was applied yearly in December. The experimental design was a randomized complete block design with four replicates and a plot area of 150 m2 which contained ten trees. Mango trees were fertilized with nitrogen at a dose of 350 kg N ha−1 and potassium at a dose of 180 K kg ha−1 as recommended by the Ministry of Agriculture of Arab Republic of Egypt. The nitrogen and potassium fertilizers were added as five equal doses each month starting in January and ending in May. Potassium sulphate (40% K) and of urea (46% N) were used to provide the plants with their NK requirements. The growth parameters were recorded at three growth stages, i.e., the beginning of the flowering stage, the full blooming stage, and the beginning of the fruiting stage. Ten sub-branches were selected to record the growth characteristics (number of leaves, leaf area, and shoot length). The beginning of the flowering stage was in the second week of February, the full blooming stage was five weeks later, and the beginning of fruiting was three weeks after the full blooming stage. The fruit yield of each tree was recorded by collecting the fruit by hand on the first of July each year.

2.2. Collection of Soil and Plant Samples

Soil samples (0–50 cm) were collected at fruit harvest to determine the available soil P and the degree of P saturation. A leaf sample of twenty leaves for each tree was collected from the 3rd and 4th node below the panicle at the beginning of the flowering stage, in the full blooming stage, and at the beginning of the fruiting stage [3,27]. Then, the collected leaves of each sample were separated into blades and petioles to study the P concentrations. Blade and petiole samples of mango leaves were washed with tap and distilled water and then dried in the oven at a temperature at 70 °C for 48 h. Ground dried plant samples were subjected to acid digestion by using H2O2 and H2SO4 [28]. The extracted P in the digest solution was measured by spectrophotometer at 660 nm [29].

2.3. Soil and Plant Analysis

Available phosphorus was extracted from soil samples by the Olsen method [18], which is the recommended method for high pH soils [14,19]. P was extracted from soil samples with NaHOC3 (pH of 8.5 and 0.5 M) and then estimated by spectrophotometer [29]. After shaking the soil sample (5 grammes) with 100 mL of sodium bicarbonate for 30 min, a filtration procedure was carried out through Whatman No. 42 filter paper. Stannous chloride and ammonium molybdate solution reagents were used to measure the amount of phosphorus in the extract by spectrophotometer at 660 nm. An appropriate volume of the sample was taken in a standard flask (50 mL) and 2 mL of ammonium molybdate solution (2.5%, w/w) was added to it; then, the distilled water was added to complete the flask. One mL of SnCl2 solution (2.5 g/50 mL concentrated HCL) was added, and the mixture was left until a blue color was formed, which was measured on a spectrophotometer. The degree of P saturation (DPS) is used for predicting P mobility and P loss from agricultural soils [13]. DPS is calculated based on the P bound to reactive Al and Fe oxides by the extraction with ammonium oxalate (pH 3) [16]. Jalali and Jalali [13] and Kleinman and Sharpley [17] indicated that the method of ammonium oxalate often is highly correlated to DPS in alkaline soils. In the current studied alkaline soil (pH = 8.25), DPS was calculated based on the equation given by Jalali and Jalali [13]:
DPS = 100 × Pox Al + Fe
where Pox is P extracted with ammonium oxalate (mmol kg−1), Al, and Fe are concentrations of Al and Fe in mmol kg−1.
Chlorophyll values were obtained by SPAD 502 plus. Ten ripe fruits from each experimental unison were selected to measure the fruit quality. The total sugar, total soluble solids (TSS), vitamin C, and % pulp were determined according to the Official Methods of Analysis [30]. The following method was used to determine the amount of sugar in fruit samples: 5 mL of mango fruit juice, 5 mL of phenol (5%) and 10 mL of concentrated H2SO4 were added to the reaction mixture, which was allowed to sit at room temperature for 30 min. Using a spectrophotometer, the absorbance was measured at 490 nm, and glucose was used as a reference [30]. The mango fruit juice was filtered through cheesecloth to measure the TSS using refractometry (Digit 032, CETI, Belgium) [30]. Using a titration method with a 2,6-dichlorophenolindophenol solution and ascorbic acid, vitamin C in mango fruit juice was measured [30].

2.4. Statistical Analysis of Data

The threshold value of P in soil and plant was calculated with linear–linear, exponential, and quadratic models by SigmaPlot 14 Software. The maximum fruit yield, which was used to calculate the critical P, is considered to be 90% of the maximum yield [20,31]. Relative yield (RY) was designed to avoid the seasonal variations in fruit yield and was calculated by the following equation:
RY = Yf / Ym
where RY is the relative yield, Yf is the fruit yield of a treatment (t ha−1); and Ym is the maximum yield of each year (t ha−1).
The Analysis of Variance (ANOVA) and Duncan’s test at a 5% level of probability were used to test the significant between the treatments after a normality test. Data statistical analyses were performed using SPSS statistical software, version 15. The relations between growth parameters and fruit yield were determined by the liner regression and Pearson correlation coefficients (R).

3. Results

3.1. Soil Available P and P Loss Risk

Increasing the doses of P fertilizer significantly (p < 0.05) increased P availability in soil (Table 1). The values of available soil P varied between 3.10 and 27.28 mg kg−1. The highest P availability was found in the soil fertilized with 240 g P tree−1, while the lowest ones were in the control. The P availability in the soil fertilized with P doses < 90 g P tree−1 was decreased after 4 years compared to the first year, while it was increased when the soil was fertilized with P doses ≥ 90 g tree−1. P availability in the soil fertilized with 240 g P tree−1 increased from an initial value of 4.50 to reach 27.28 mg kg−1 after four years of fertilization. The available soil P accumulated at high concentrations after four years of fertilization with P doses ≥ 90 g P tree−1.
P loss risk was investigated by DPS determination and the data are shown in Table 2. Increasing the doses of P fertilizer significantly (p < 0.05) increased DPS in the sandy calcareous soil. DPS values varied between 3.83 and 32.47%. The maximum DPS values were found in the soil fertilized with 240 g P tree−1, while the lowest ones were recorded in the control. DPS in the soil fertilized with P doses < 90 g P tree−1 was decreased with time, while it was increased when the soil was fertilized with P doses ≥ 90 g Ptree−1. DPS in the soil fertilized with 240 g P tree−1 increased from an initial value of 3.83 to 32.47% after four years of P-fertilization. P doses ≥ 90 g P tre−1 caused remarkable increases in the DPS after four years of fertilization. The relationship between Olsen P and DPS is shown in Figure 1. The liner regression correlation between Olsen p values and DPS was positive and significant (R2 = 0.94); therefore, the regression equations were used to calculate the critical p value, which gives us DPS values above 25%. According to the obtained results, the sandy soil containing values of available P higher than 20.3 mg kg−1 increases P-loss risk.

3.2. Effect of P Doses on P Uptake and Mango Growth

P fertilizer significantly (p < 0.01) raised P concentrations in mango leaves at all growth stages (Figure 2). P concentrations in the blades ranged between 1.03 and 3.91 g kg−1, while in the petioles it ranged between 1.05 and 6.39 g kg−1. P concentrations in the petioles were higher than concentrations in the blades in all the studied growth stages. The concentrations of P in the blades and petioles in all the growth stages can be arranged in descending order: beginning of flowering stage > full blooming stage > beginning fruiting stage.
The addition of P fertilizer significantly (p < 0.05) increased mango growth characteristics at all growth stages (Table 3). Chlorophyll, shoot length, number of leaves, and leaf area were increased with increasing P dose. The maximum growth of mango plants was achieved at the beginning of the fruiting stage. In most cases, the maximum significant growth of mango plants was recorded when P was added at the dose of 90 g P tree−1. In most cases, the addition of P doses more than 90 g P tree−1 did not result in any significant growth increases compared to the treatment of 90 g P tree−1.
The relationships between mango fruit yield and some agronomic traits are shown in Table 4. Chlorophyll, shoot length, number of leaves, leaf area, blade-P, and petiole-P were positively and significantly correlated with the fruit yield at the beginning of the flowering stage. The relationship between mango fruit yield and chlorophyll was positive and significant in the beginning of the flowering, full blooming, and beginning of fruiting stages. The relationship between fruit yield and petiole-P was positive and significant in the beginning of the flowering and full blooming stages, while the relationship with blade-P was positive and significant only in the beginning of the flowering stage.

3.3. Effect of P Doses on Mango Fruit Yield and Quality

The response of mango fruit yield and quality to P doses was investigated and the results are illustrated in Figure 3 and Figure 4. The fruit yield ranged between 5.72 and 13.7 t ha−1. The fruit yield of mango responded significantly to the application of P doses through the four years. The maximum significant fruit yield was obtained from P doses ≥ 90 g P tree−1; the response of fruit yield to P doses above this level was in-significant. The application of P fertilizer significantly (p < 0.05) increased the fruit quality of mango. The addition of P increased the pulp, total soluble solids, total sugar, and vitamin C in the fruit of mango. In most cases, the addition of high levels of phosphate fertilization (>90 g P tree−1) did not lead to any significant increases in the measured quality characteristics.

3.4. Critical P in Soil and Plant for Maximum Mango Fruit Yield

The critical P in plant leaves and soil was calculated based on the linear–linear, exponential, and quadratic models and the data are shown in Table 5. The critical value of available soil P ranged between 10.43 and 11.85 mg kg−1. The relationships between the fruit yield and the available soil P were positive and significant in all the studied mathematical models. Petiole-P in mango leaves was highly correlated with mango fruit yield in the beginning of the flowering and full blooming stages (Table 4). The relationship between the fruit yield and blade-P was positive and significant only in the beginning of the flowering stage, and then the relationship became insignificant in the later growth stages. Therefore, we relied on the concentrations of petiole-P in the calculating of critical p value in mango leaves. All the models adequately described the relationship between mango fruit yield and petiole-P (Table 5). The critical values of petiole-P ranged between 2.34 and 3.53 g kg−1 (Table 5). The values of R2 of soil P models were 0.88 and 0.89, while in the case of petiole-P they were 0.66 and 0.67. Although the petiole-P had a positive and significant relationship with mango fruit yield, the available soil P had a stronger relationship with the fruit yield than the petiole-P.

4. Discussion

4.1. P Management in Mango Orchards

Nutrient management in a mango orchard requires special care in order to maximize the utilization of added fertilizers and minimize environmental pollution [32,33]. Mango trees are evergreen plants that are voracious in absorbing nutrients from soil [32,34]. Phosphorus is a non-renewable resource, and therefore fertilizer requirement must be accurately determined in order to preserve natural resources in line with sustainable development [8]. The current study revealed that mango trees respond to phosphate fertilization up to 90 g P tree−1. The addition of 90 g P tree−1 increased mango fruit yield by 98% compared to the control, while the differences between the higher levels (≥90 g P tree−1) were insignificant. The maximum quality characteristics of mango fruit was achieved when the plant was fertilized with 90 g P tree−1. The response of mango trees to phosphate fertilization is expected as it is one of the essential macronutrients and is included in the composition of many vital compounds in plant cells [6,32]. Mango fruit yield was positively and significantly correlated with the chlorophyll, shoot length, number of leaves, leaf area, blade-P, and petiole-P. Providing mango trees with the optimum level of P led to an increase in the growth by increasing the leave area and chlorophyll concentration, and thus increased the photosynthesis of the mango plant [35,36]. The presence of the appropriate concentration of P in plant tissues has an important role in the production of mango fruit, as P is a vital element in nucleic acid synthesis, energy compounds, and photosynthesis [37]. Therefore, the production capacity of mango plants weakens when P deficiency occurs [35].

4.2. P Threshold for Maximum Mango Fruit Yield

The threshold value of soil P is the optimum available P that produces the highest yield and no expected increases in yield above this soil p value [6]. The critical available P in the sandy soil, based on the studied mathematical models, was 10–12 mg kg−1. Mango fruit yield is expected to reach its maximum value if the sandy soil contains an Olsen P ranging between 10 and 12 mg kg−1 and no expected increase in fruit yield with P fertilization in this case. Soil properties such as organic matter, calcium carbonate, and clay content significantly influence the critical available p values, and plant response to P fertilization depends on the type of plant species [11,33,37]. The obtained critical available P for maximum mango fruit yield was in agreement with the results of previous studies, which determined a range of critical soil P between 10 and 40 mg kg−1 [6,20,31,37,38,39,40]. The most important reasons for the difference in the critical p values, which led to this wide range, are the difference in the extraction methods and the difference in mathematical models which were used in the calculation [6,40]. The main method for achieving a desired yield is to supply P in quantities sufficient to control the high soil adsorption capacity while also meeting crop demand [13,21]. Fertilization rates must be increased in soil with high P buffering capacity because the capacity of soil to fix P increases as P buffering capacity increases [13,21].

4.3. P Concentrations in Blades and Petioles of Mango Leaves

The concentrations of P in the blades and petioles of mango leaves were higher in the beginning of the flowering stage and then declined when mango plants started in the formation of fruits. P is a mobile nutrient in plant tissue; when the mango plants start in the fruiting stage, most of P moves to the fruit [27,35,41]. The blades of mango leaves contained lower P concentrations than what has accumulated in the petioles. P concentrations in the petioles have a better relationship with mango fruit yield than the blades. These results were consistent with the results of Klein et al. [42] and Schreiner and Osborne [43]. The analysis of the petioles of mango leaves in the beginning of the flowering stage will give an exact report on the status of critical p value that gives the maximum fruit yield. The concentration of P in the petioles was well correlated with mango fruit yield and it can be used to determine if mango plants have sufficient P or if they need to be fertilized. Concentrations of P in plant tissues are affected directly by fertilization doses and can be used to plan fertilizer practices that lead to obtaining the best yield [6,22,23]. The results of our study revealed that the critical p values in the petioles of mango leaves ranged from 2.34 to 3.53 g kg−1 (dry weight basis). Maximum growth and yield are reported at a leaf-P concentration of 2–3 g kg−1 (dry weight basis) [43,44,45]. The maximum photosynthesis of a plant can be achieved at 2–3 g kg−1 (dry weight basis) of leaf-P, and increasing P above these concentrations does not lead to growth increase [44]. The findings of the current study suggest that a petiole-P above the threshold value (2.34–3.53 g kg−1) no longer has a valuable impact on the fruit yield. Modulating P supply to align with the plant requirement can be regulated by the plant P uptake, which gives the maximum yield [6,8].

4.4. Predicting P Loss Risk

Adding phosphate fertilizer at doses higher than 150 g P tree−1 (100 kg P ha−1) led to obtaining a degree of phosphorus saturation (DPS) above 25%. The value of DPS is used to assess the potential P-loss risk [13,15]. The soils with DPS values above 25% are considered to have high P-loss risk [6]. Increasing amounts of the added P fertilizer at doses higher than the plant’s ability to absorb leads to saturation of the soil with P and increases the runoff risks [14]. Hu et al. [6] studied the P-loss risk in sandy soils cultivated with wheat plants and they reported that the addition of P fertilizer higher than 75 kg P ha−1 increased the DPS value to be more than 25%. In the current study, the doses of P, which are associated with high P-loss risks, were higher than those obtained from Hu et al. [6] studies that were carried out in a sandy soil with the same characteristics. Field crops such as wheat grow in the soil for one season, and their P fertilization requirements are added at large doses due to their short growth period and low use efficiency of P in the case of cereal crops [46,47]. The results of the current study indicate that P-loss risk appears in mango orchards with the use of high fertilization doses (more than 100 kg P ha−1), because mango trees are evergreen throughout the year and have high nutrient requirements [34]. The estimated critical Olsen p value that gives DPS above 25% is 20.3 mg kg−1. The P-loss risks in the sandy soils that contain an Olsen p value of more than 20.3 mg kg−1 will be high and may cause pollution in the ecosystem. The significant positive relationship between the available Olsen P and DPS has been previously proven in similar studies, e.g., Hu et al. [6] and Wang [16]. The studies of Hu et al. [6] and Wang et al. [16] confirmed that P-loss risk is highly expected in sandy soil that is poor in its content of organic matter and clay minerals [15,33,48].

5. Conclusions

Despite phosphorus (P) being an essential element for mango plants, previous studies focused on studying the response of mango to increasing P doses without taking into account the amount of available P in the soil. The threshold value of available soil and plant tissue is crucial to achieve the optimum mango fruit yield. Processing the data of soil and plant analysis and its relationship to the fruit yield of mango using linear–linear, exponential, and quadratic models was used to identify the P threshold. The studied mathematical models gave similar values; therefore, it can be recommended to use any of them in calculating the critical limit of P in mango production. The findings of four years of field trials have confirmed that threshold soil P ranged between 10–12 mg kg−1, while in plant tissue it ranged between 2.34 and 3.53 g kg−1 (dry weight basis). The increase of mango fruit yield is not expected to be above the threshold value. Mathematical equations can be used to predict P loss risks and potential environmental pollution. The risks of P run-off are expected to be high if the sandy soils contain available P higher than 20.3 mg kg−1. The use of soil available P to predict the response of mango to P fertilization is better than the use of plant tissues. More studies should be conducted under different environmental conditions, along with studying the effect of methods of extracting P from the soil in calculating the critical limit.

Author Contributions

Conceptualization, J.W., M.E., Y.H. (Yingdui He), X.Z., Y.H. (Yongyong Hui), M.A.E., Z.D., S.E.-N., A.E.-D.O., M.G.Z. and A.M.S.K.; methodology, M.A.E., Z.D., S.E.-N., A.E.-D.O., M.G.Z. and A.M.S.K.; software, J.W., M.E., Y.H. (Yingdui He), X.Z., Y.H. (Yongyong Hui) and A.M.S.K.; validation, J.W., M.E., Y.H. (Yingdui He), X.Z., Y.H. (Yongyong Hui), M.A.E., Z.D., S.E.-N., A.E.-D.O., M.G.Z. and A.M.S.K.; investigation, J.W., M.E., Y.H. (Yingdui He), X.Z., Y.H. (Yongyong Hui), M.A.E., Z.D., S.E.-N., A.E.-D.O., M.G.Z. and A.M.S.K.; writing—original draft preparation, J.W., M.E., Y.H. (Yingdui He), X.Z., Y.H. (Yongyong Hui), M.A.E., Z.D., S.E.-N., A.E.-D.O., M.G.Z. and A.M.S.K.; writing—review and editing, J.W., M.E., Y.H. (Yingdui He), X.Z., Y.H. (Yongyong Hui), M.A.E., Z.D., S.E.-N., A.E.-D.O., M.G.Z. and A.M.S.K. All authors have read and agreed to the published version of the manuscript.

Funding

The authors are grateful to Senior Foreign Expert Project of China (Grant number G2021034008L), Central Public-interest Scientific Institution Basal Research Fund (NO. 1630092022001) and Discipline and Master’s Site Construction Project of Guiyang University by Guiyang City Financial Support Guiyang University (2022-xk10).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The manuscript contains all data that were created or examined during the research.

Acknowledgments

The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through the Large Groups Project under grant number L.G.P. 2/138/43. All the authors are grateful for the support provided by the Soils, Water, and Environment Research Institute (SWERI), Agriculture Research Center (ARC), Egypt.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. The liner regression correlation between available P and DPS. The number of samples is 144.
Figure 1. The liner regression correlation between available P and DPS. The number of samples is 144.
Horticulturae 08 01064 g001
Figure 2. The effect of P doses on blade-P and petiole-P at different growth stages. Means (±SE, n= 16) denoted by different letters indicate significant difference according to Duncan’s test at p < 0.05.
Figure 2. The effect of P doses on blade-P and petiole-P at different growth stages. Means (±SE, n= 16) denoted by different letters indicate significant difference according to Duncan’s test at p < 0.05.
Horticulturae 08 01064 g002
Figure 3. The effect of P doses on mango fruit yield. Means (±SE, n= 4) denoted by different letters indicate significant difference according to Duncan’s test at p < 0.05.
Figure 3. The effect of P doses on mango fruit yield. Means (±SE, n= 4) denoted by different letters indicate significant difference according to Duncan’s test at p < 0.05.
Horticulturae 08 01064 g003
Figure 4. The effect of P doses on mango fruit quality. Means (±SE, n = 16) denoted by different letters indicate significant difference according to Duncan’s test at p < 0.05.
Figure 4. The effect of P doses on mango fruit quality. Means (±SE, n = 16) denoted by different letters indicate significant difference according to Duncan’s test at p < 0.05.
Horticulturae 08 01064 g004aHorticulturae 08 01064 g004b
Table 1. The effect of P doses on available P during the four years (2018–2021). Means (± SE, n = 4) denoted by different letters indicate significant difference according to Duncan’s test at p < 0.05. p is p value of the ANOVA test. P = phosphorus doses, Y = year, and PY = interaction of P and Y.
Table 1. The effect of P doses on available P during the four years (2018–2021). Means (± SE, n = 4) denoted by different letters indicate significant difference according to Duncan’s test at p < 0.05. p is p value of the ANOVA test. P = phosphorus doses, Y = year, and PY = interaction of P and Y.
Doses of P (g Tree−1)2018201920202021
04.2 ± 0.4 g3.9 ± 0.3 g3.4 ± 0.8 g3.1 ± 0.7 g
306.0 ± 0.7 f5.7 ± 0.5 f5.3 ± 0.8 f5.0 ± 0.5 f
609.3 ± 1.0 e9.1 ± 0.9 e8.9 ± 1.2 e8.7 ± 0.9 e
9012.5 ± 1.2 d13.4 ± 1.2 d14.5 ± 1.3 d14.6 ± 2.2 d
12015.78 ± 1.1 c16.1 ± 1.1 c17.7 ± 1.2 c18.6 ± 2.2 c
15017.4 ± 1.7 b18.2 ± 1.6 b18.9 ± 1.4 c22.9 ± 2.6 b
18019.0 ± 2.8 a20.9 ± 2.1 a22.3 ± 2.7 b23.8 ± 3.1 b
21019.8 ± 2.4 a21.1 ± 2.2 a24.8 ± 2.8 a26.8 ± 3.2 a
24020.5 ± 2.0 a22.0 ± 2.3 a25.9 ± 2.2 a27.3 ± 3.3 a
pP0.002
pY0.010
pPY0.005
Table 2. The effect of P doses on the degree of P saturation (% DPS) during 2018–2021. Means (±SE, n= 4) denoted by different letters indicate significant difference according to Duncan’s test at p < 0.05. p is p value of the ANOVA test. P = phosphorus doses, Y = year, and PY = interaction of P and Y.
Table 2. The effect of P doses on the degree of P saturation (% DPS) during 2018–2021. Means (±SE, n= 4) denoted by different letters indicate significant difference according to Duncan’s test at p < 0.05. p is p value of the ANOVA test. P = phosphorus doses, Y = year, and PY = interaction of P and Y.
P Doses (g Tree−1)2018201920202021
03.9 ± 0.3 h3.6 ± 0.4 h3.4 ± 0.7 g3.3 ± 0.6 g
307.3 ± 0.8 g6.6 ± 0.6 g6.5 ± 0.7 f6.3 ± 0.6 f
609.7 ± 1.2 f9.3 ± 0.8 f9.2 ± 1.3 e9.1 ± 0.8 e
9016.7 ± 1.3 e17.1 ± 1.4 e18.9 ± 2.4 d19.0 ± 1.3 d
12019.0 ± 1.2 d19.6 ± 1.3 d19.9 ± 1.3 d20.7 ± 1.2 d
15022.3 ± 1.8 c22.8 ± 1.7 c23.1 ± 2.4 c23.5 ± 2.6 c
18026.0 ± 2.9 b27.2 ± 2.3 b28.0 ± 2.8 b28.9 ± 2.2 b
21026.3 ± 2.8 b26.8 ± 2.3 b27.2 ± 2.8 b28.2 ± 2.3 b
24028.3 ± 2.2 a29.9 ± 2.2 a31.5 ± 2.4 a32.5 ± 2.1 a
pP0.009
pY0.019
pPY0.006
Table 3. The effect of P doses on mango growth. Means (±SE, n = 16) denoted by different letters indicate significant difference according to Duncan’s test at p < 0.05. p is p value of the ANOVA test.
Table 3. The effect of P doses on mango growth. Means (±SE, n = 16) denoted by different letters indicate significant difference according to Duncan’s test at p < 0.05. p is p value of the ANOVA test.
P Doses
(g Tree−1)
ChlorophyllShoot Length (cm)Number of Leaves/ShootLeaf Area (cm)
Beginning of flowering stage035 ± 2 c50 ± 4c41 ± 3 b48 ± 3 c
3040 ± 2 b62 ± 9 b44 ± 2 b60 ± 5 b
6039 ± 2 b64 ± 8 b43 ± 2 b62 ± 4 b
9044 ± 3 a70 ± 6 a50 ± 4 a68 ± 4 ab
12045 ± 2 a73 ± 6 a52 ± 2 a73 ± 5 a
15045 ± 2 a72 ± 7 a53 ± 5 a72 ± 3 a
18044 ± 2 a75 ± 6 a54 ± 3 a75 ± 4 a
21046 ± 2 a74 ± 8 a53 ± 5 a76 ± 6 a
24047 ± 3 a75 ± 7 a54 ± 4 a77 ± 8 a
p0.0100.0080.0160.003
Full blooming stage033 ± 2 c52 ± 3 c43 ± 4 b58 ± 3 c
3038 ± 2 b64 ± 5 b45 ± 5 b72 ± 6 b
6040 ± 2 b66 ± 5 b46 ± 3 b73 ± 7 b
9046 ± 3 a73 ± 3 a52 ± 4 a76 ± 8 b
12045 ± 2 a75 ± 4 a54 ± 2 a84 ± 8 a
15044 ± 2 a76 ± 6 a55 ± 5 a84 ± 8 a
18046 ± 2 a76 ± 5 a56 ± 3 a86 ± 7 a
21046 ± 2 a77 ± 4 a55 ± 4 a84 ± 6 a
24046 ± 3 a78 ± 5 a56 ± 6 a85 ± 7 a
p0.0130.0110.0050.004
Beginning of fruiting stage033 ± 2 c56 ± 5 c44 ± 2 b63 ± 4 c
3040 ± 2 b70 ± 6 b46 ± 3 b80 ± 5 b
6039 ± 2 b72 ± 7 b46 ± 3 b82 ± 3 b
9046 ± 3 a79 ± 4 a55 ± 6 a84 ± 5 b
12044 ± 2 a80 ± 5 a54 ± 5 a95 ± 8 a
15045 ± 2 a82 ± 6 a56 ± 4 a93 ± 9 a
18043 ± 2 a83 ± 3 a57 ± 4 a95 ± 9 a
21046 ± 2 a85 ± 7 a56 ± 5 a96 ± 8 a
24044 ± 3 a84 ± 8 a56 ± 6 a94 ± 9 a
p0.0120.0180.0020.007
Table 4. The correlation between fruit yield of mango and some agronomic traits. The correlation analysis between fruit yield and agronomic traits was run based on the data of the four years. *, ** significant at p < 0.05 and p < 0.01. Number of samples is 144.
Table 4. The correlation between fruit yield of mango and some agronomic traits. The correlation analysis between fruit yield and agronomic traits was run based on the data of the four years. *, ** significant at p < 0.05 and p < 0.01. Number of samples is 144.
Growth StageAgronomic TraitsEquationR2r
Beginning of flowering stageChlorophylly = 1.256X − 12.460.940.86 **
Leaves areay = 0.075X + 6.4980.730.77 **
Shoot lengthy = 0.012X + 5.8670.700.83 **
Leave numbery = 0.257X + 7.8780.950.92 **
P in bladesy = 2.082X + 8.9120.770.65 *
P in petiolesy = 0.086X+ 0.3550.940.82 **
Full blooming stageChlorophylly = 1.156X − 1.9630.840.79 **
Leaves areay = 0.003X + 5.8750.270.19
Shoot lengthy = 0.092X + 3.2570.690.62 *
Leave numbery = 0.008X + 4.8960.480.35
P in bladesy = 0.004X + 2.8620.390.48
P in petiolesy = 0.152X + 5.2370.820.76 **
Beginning of fruiting stageChlorophylly = 1.112X − 2.4960.730.82 *
Leaves areay = 0.056X + 15.270.330.39
Shoot lengthy = 0.098X + 5.6720.580.45
Leave numbery = 0.037X + 6.9200.350.27
P in bladesy = 0.297X + 4.8350.490.32
P in petiolesy = 0.372X + 4.5690.330.54
Table 5. The relationship between mango yield, soil P and petiole-P fitted by the linear-linear, quadratic, and exponential models under four years (2018–2021). *, ** significant at p < 0.05 and p < 0.01. Number of samples is 144.
Table 5. The relationship between mango yield, soil P and petiole-P fitted by the linear-linear, quadratic, and exponential models under four years (2018–2021). *, ** significant at p < 0.05 and p < 0.01. Number of samples is 144.
FormulaR2Critical p Value (mg kg−1)
Soil available Plinear-linearY = 0.0592 + 0.1405X − 0.0070X2 + 0.0001X30.89 **11.43
QuadraticY = 0.2374 + 0.0844X − 0.002X20.88 **10.43
ExponentialY = 1.0075 (1 − e−0.1889X)0.89 **11.85
P in plant petioleslinear-linearY = 0.0360 + 0.4005 − 0.0467X2 + 0.0011X30.67 *3.39
QuadraticY = 0.0722 + 0.3620X − 0.00348X20.67 *2.34
ExponentialY = 1.1170 (1 − exp−0.4648X)0.66 *3.53
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Wang, J.; Elbagory, M.; He, Y.; Zhang, X.; Hui, Y.; Eissa, M.A.; Ding, Z.; El-Nahrawy, S.; Omara, A.E.-D.; Zoghdan, M.G.; et al. Modeling of P-Loss Risk and Nutrition for Mango (Mangifera indica L.) in Sandy Calcareous Soils: A 4-Years Field Trial for Sustainable P Management. Horticulturae 2022, 8, 1064. https://doi.org/10.3390/horticulturae8111064

AMA Style

Wang J, Elbagory M, He Y, Zhang X, Hui Y, Eissa MA, Ding Z, El-Nahrawy S, Omara AE-D, Zoghdan MG, et al. Modeling of P-Loss Risk and Nutrition for Mango (Mangifera indica L.) in Sandy Calcareous Soils: A 4-Years Field Trial for Sustainable P Management. Horticulturae. 2022; 8(11):1064. https://doi.org/10.3390/horticulturae8111064

Chicago/Turabian Style

Wang, Jiyue, Mohssen Elbagory, Yingdui He, Xu Zhang, Yongyong Hui, Mamdouh A. Eissa, Zheli Ding, Sahar El-Nahrawy, Alaa El-Dein Omara, Medhat G. Zoghdan, and et al. 2022. "Modeling of P-Loss Risk and Nutrition for Mango (Mangifera indica L.) in Sandy Calcareous Soils: A 4-Years Field Trial for Sustainable P Management" Horticulturae 8, no. 11: 1064. https://doi.org/10.3390/horticulturae8111064

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