Nutritional Diagnosis of the Mineral Elements in Tainong Mango Leaves during Flowering in Karst Areas

Abstract

The balance of the mineral nutrition in mango leaves during the flowering period affects the flowering of mango trees and fruit production. Because the soil in karst areas has a slow and unbalanced supply rate of nutrients, mango orchards in a karst area generally have a low yield. There are few studies on the fertilization of mango orchards in karst areas, especially on the diagnosis of leaf mineral nutrition. In this study, mango orchards in the typical karst areas of Guangxi province, one of the main mango-producing areas in China, were selected from the low-yielding and medium-yielding mango orchards. Surface soil samples and leaf samples from mango orchards in full bloom were collected to test for macronutrients and micronutrients. The Diagnosis and Recommendation Integrated System (DRIS) graphical method, the DRIS method, the Modified DRIS (M-DRIS), and the Deviation from Optimum Percentage (DOP) index diagnostic methods were applied to the leaves. The results showed that the DRIS graphical analysis yielded appropriate ratios of N, P, K, Mg, S, Fe, Mn, Cu with the corresponding three elements, Ca, Zn, and B, which can be used as reference diagnostic criteria. Based on the values of the DRIS diagnostic criteria for high-yielding orchards, the critical ranges of the suitable values of the mineral nutrients in the Tainong mango leaves during flowering were determined as N (14.87–17.27 g/kg), P (0.69–0.89 g/kg), K (4.45–6.90 g/kg), Ca (9.51–16.55 g/kg), Mg (1.44–2.20 g/kg), S (0.75–1.06 g/kg), Fe (0.10–0.13 g/kg), Mn (0.61–1.02 g/kg), Cu (5.41–8.89 mg/kg), Zn (7.91–18.95 mg/kg), and B (8.38–16.23 mg/kg). The results of the DRIS, M-DRIS, and DOP index methods were analyzed to determine the order of the fertilizer requirements for the low-yielding orchards: Mg > Fe > S > Zn > B > Cu > K > N > P > Mn > Ca, and for the medium-yielding orchards: Mg > Fe > B > Zn > S > Cu > N > Mn > K > P > Ca. The soil and leaf correlation analysis showed that the soil exchangeable Ca and effective Fe were significantly negatively correlated. Leaf Ca and Fe elements had a mutually antagonistic effect, leaf Mn-rich contents inhibited the uptake of the Mg and Fe elements, and low-yielding orchards had an excess of Mn and a deficiency of Mg. We found that there is lack of the Mg and Fe, a low content of the S and B, and an excess of the Ca and Mn in the mango orchards of the Baise karst area. We suggested that the DRIS graphical method is suitable for the diagnosis of three nutrient elements, and either the DRIS or M-DRIS index method can be chosen. The present research can be used for the precise fertilization of mango orchards in karst areas to improve the yield and quality of local mango orchards.

1. Introduction

The mango (Mangifera indica Linn.) is one of the choicest fruits in the tropical and subtropical areas of the world [1]. In 2020, China planted 3594 km² of mangoes with a total output of 3.31 million tons, making it the second largest mango producer in the world [2]. Baise mango production was 0.80 million tons in 2020, which is the highest mango production in China. The Tainong mango (Mangifera indica Tainong No. 1) is the main variety of mango in the Baise area of Guangxi, and 35.9% of the area consists of karst areas. Furthermore, there are about 3.44 million km² of karst areas in China, which is 15.6% of the karst areas in the world [3]. Therefore, there is an urgent need to diagnose the nutrition of mango trees quickly and accurately for the scientific fertilization management technology of mango orchards in karst areas.

The leaves of fruit trees are the most active and sensitive plant organs in terms of metabolic function and nutrient supply [4]. Thus, the leaves can represent the overall nutritional level of fruit trees more comprehensively, and the application of plant leaf mineral nutrition diagnosis is an effective means to study the nutritional status of fruit trees [5]. The flowering period is an important stage for mangoes as a nutritional and reproductive growth period, and fruit trees need to consume a lot of nutrients during the flowering period, as an insufficient supply of nutrients during this time will directly lead to a prolonged flowering period and reduced fruit set rate [6]. Due to the characteristics of the calcium-rich and alkaline soils in mango orchards in karst areas, on the one hand, high calcium soils in karst areas can improve organic matter sequestration capacity and soil fertility [7], and, on the other hand, the limestone soils in karst areas are mainly carbonate rocks with slow soil formation rates, shallow soils, insufficient nutrients, clayey and heavy textures, poor agglomerate structural properties, and low water and fertilizer retention capacity [8]. This reduces the effectiveness of soil elements such as P, Fe, and Al [9], making the rate of nutrient supply slow and unbalanced [10]; these problems may lead to a long-term imbalance in the various mineral nutrients that are required for fruit tree growth, resulting in malnutrition of the fruit trees and susceptibility to pests and diseases [5], which greatly affects the economic benefits of the orchards in karst areas.

Theoretical approaches to leaf nutrient diagnosis include the Law of Minimum Nutrients [11], Critical Value Approach [12], Diagnosis Standard Values [13], Diagnosis and Recommendation Integrated System (DRIS) [14], Improved DRIS Approach [15], Deviation from Optimum Percentage (DOP) [16], and Compositional Nutrient Diagnosis [17]. Researchers have conducted leaf mineral element nutrient diagnostic studies on apple (Malus domestica (Suckow) Borkh.) [18] and longan (Dimocarpus longan Lour.) [19] fruit trees, and have proposed the corresponding sampling times and sampling sites. The leaf DRIS nutrient diagnostics were also applied to obtain the fertilizer requirement order for the fruit trees. Additionally, various leaf nutrient diagnosis methods were applied successively, and after a comprehensive analysis of the diagnosis results, the researchers selected a more suitable nutrient diagnosis method for a certain orchard and obtained a more scientific state of soil mineral element abundance and increased yield potential for the orchard [20,21,22]. According to previous research, the developmental trend of leaf nutrition diagnosis is to combine the advantages and disadvantages of several diagnostic methods and carry out the diagnosis together to achieve the goal of a more accurate diagnosis of the fruit tree nutrition status [23,24,25,26]. The suitable period for leaf nutrition diagnosis of different mango varieties is the reproductive growth period, and the suitable diagnostic site is the first leaf growth after pruning. However, most of the studies mentioned above were conducted in non-karst areas, and there have been relatively few studies on the mineral nutrition diagnosis of mango orchards in karst mountain areas.

Consequently, to diagnose the nutrition of mango trees quickly and accurately for mango orchards in karst areas, we selected Tainong mango orchards in the karst boulder mountain area of Baise, Guangxi as the research area and compared them with high-yielding mango orchards in non-karst areas. The DRIS nutritional diagnosis was carried out on the flowering leaves and compared to the Modified DRIS (M-DRIS) and DOP methods. The major objectives of this study are: (1) to develop a rapid and accurate nutritional diagnosis of mango trees in order to identify the current situation of the mineral element abundance and deficiency in the mango orchards in karst areas, (2) to provide data support and a scientific basis for the mineral nutritional diagnosis and rational fertilization of Tainong mango orchards in order to improve orchard yield and quality in karst areas.

2. Materials and Methods

2.1. Study Area

The study area is located in Tianyang County, Baise City, Guangxi Zhuang Autonomous Region, at an elevation 500 m above sea level, with sufficient light and abundant heat, an average annual temperature of 20 °C, and an average annual frost-free period of 352 d. The area has an average annual rainfall of 1100 mm; there are continuous rains in the summer and autumn seasons (from June to November). It is a southern subtropical monsoon climate and is one of the most suitable places for mango cultivation in China. The research sample site in the karst area is in a mango orchard of Wucun Town, Tianyang County, where the karst landform type is a peak that developed from a depression and the soil is mostly brown limestone soil (Figure 1). To better compare the characteristics of the soils and leaves in the mango orchard in the karst area, a Tainong mango orchard planted on red soil of the quaternary period in the non-karst area in Baiyu Town, Tianyang County, about 20 km from the survey area, was selected as a control.

2.2. Sampling and Analysis

In March 2021, the sample plots were selected according to the nutritional status, blooming, and decaying of the fruit trees in the different landscape types (depressions and non-depressions) of the low-yielding and medium-yielding orchards in the Tainong mango orchards in the karst area during the flowering period. Three parallel sample plots were set up for each type, with a total of 18 sample plots 10 × 10 m in size. Three high-yielding orchards (>70 kg/plant) were selected as controls in the non-karst area, and the average plant yield of each sample plot was divided into five low-yielding orchards (<30 kg/plant) and 13 medium-yielding orchards (30–60 kg/plant) over the last two years. All the sample plots were Tainong mango varieties, and the trees were about 8 years old. The fertilization period is normally occurs after the harvest (in autumn) and before flowering (in April). According to an interview with local farmers, the orchard had not been fertilized in March 2021 when the soil samples were collected. For financial and labor reasons, foliar fertilization was not used by the local farmers during the harvest, vegetative growth, and flowering periods of mango plants. The sampling was conducted to avoid the fertilization period, and the surface soil was sampled using the five-point method (Figure 2), with the sampling points selected in the center of the adjacent mango tree line to avoid the fertilization ditch, and 0–20 cm surface soil samples were collected. Then, leaf samples were collected from the sample plots by randomly selecting normal plants with basically the same growth, and taking a piece of the first (top) leaf from the east, south, west, and north in the middle and upper parts of the tree in four directions after pruning. A total of 60–80 pieces were collected as a mixed sample, and five batches were taken from each sample plot. The collected leaves were washed and wiped clean with ultra-high pure water, killed in an oven at 90 °C for 30 min, and then dried at a constant temperature of 75 °C. Then, the soil and leaf samples were determined by referring to the classic determination method [27].

2.3. Nutritional Diagnostic Analysis

2.3.1. Diagnosis and Recommendation Integrated System Diagnostic Parameters

The leaf DRIS diagnostic method can determine the optimal balance of the elemental ratios, and the closer the measured value of the elemental ratios is to the optimum value, the more balanced it is [28]. Based on the calculation principle of the DRIS method, the mean, standard deviation, coefficient of variation, and variance of the leaf nutrient element ratios were calculated for the high-yielding, medium-yielding, and low-yielding orchards by using the total of 110 ratio forms of N, P, K, Ca, Mg, S, Fe, Mn, Cu, Zn, and B, for any two selected element contents of the mango leaves in each location, and calculating the variance ratio for the low- to high-yielding orchards (VL/VH). The variance ratio for the medium- to high-yielding orchards (VM/VH) was also calculated, and an independent sample t-test was conducted on the ratios of the nutrient elements in the different high- and low-yielding orchards. Then, the ratio of the two elements with greater difference or variance was selected as the diagnostic parameter; for example, if the P/N variance ratio was greater than the N/P variance ratio, then P/N was selected as the diagnostic parameter.

2.3.2. Diagnosis and Recommendation Integrated System Graphical Solution Method

The DRIS graphical solution method is composed of three axes intersecting at a point with a pointing angle of 60° and two concentric circles passing through the intersection point. The radii of the inner and outer circles were 2/3 and 4/3 times the standard deviation of the high-yielding group, respectively. The three axes indicated the magnitude of the ratio of two to two of the three elements; the center of the circle was the best value of the nutrient ratio of the plant in the high-yielding group, and the inner circle was regarded as the nutrient equilibrium zone and was represented by “→”. Between the inner circle and the outer circle was the maximum or minimum of the nutrients expressed by “↗” and “↘”, respectively, and outside the outer circle was the excess or lack of nutrients expressed by “↑” and “↓”, respectively [29]. The DRIS graphical method can only be used to demonstrate three nutrient elements and their proportional relationships at a time.

2.3.3. Diagnosis and Recommendation Integrated System Index Method

The DRIS index indicates the intensity of the crop demand for a nutrient. The DRIS index diagnostic method can not only determine the nutrient abundance and deficiency status of the leaves, the order of the fertilizer demand, and the maximum nutrient limitation, but it can also diagnose the nutrient balance and potential nutrient deficiency, which is an important technical tool to guide scientific fertilization [30]. In this study, 11 elements, N, P, K, Ca, Mg, S, Fe, Mn, Cu, Zn, and B, in the leaves of the medium- and low-yielding mango orchards were selected for DRIS nutrient diagnosis, and the content of any two nutrients in the low yielding orchards was expressed as X and Y. X/Y was the ratio of the content of any two given elements. In the high-yielding orchards, x/y was the ratio of any two given nutrients; the degree of deviation of X/Y from x/y was expressed by the partial function f(X/Y), and the X index of a given element in the low-yielding orchard was calculated as follows:

X index = [f(X/A) + f(X/B) + … − f(J/X) − f(K/X)]/n
where f (X/Y) = [(X/Y)/(x/y) − 1] × 1000/C.V X/Y > x/y
f(X/Y) = [1 − (x/y)/(X/Y)] × 1000/C.V X/Y < x/y

(1)

where C.V is the coefficient of variation of x/y; A, B,… J, and K are the other 10 nutrients except for X, and n is the number of partial functions involved in the calculation of the X index; in terms of the partial functions involved in the calculation of the X index, X in the numerator partial function is positive, X in the denominator partial function is negative, and the DRIS index algebraic sum is zero. The sum of the absolute values of the DRIS (or M-DRIS) indices of all the elements of a diagnosed sample is called the Nutrient Imbalance Index (NII), expressed as NII (NII = Σ|X|/n); the larger its value, the more unbalanced the fruit tree nutrition.

2.3.4. Modified Diagnosis and Recommendation Integrated System and Deviation from Optimum Percentage Index Methods

The M-DRIS index method is the introduction of the dry matter (DM) term in the DRIS equilibrium formula, and the main reason is that dry matter accounts for more than 90% of dry matter weight, whereas the mineral elements are less than 10%. Moreover, dry matter is the product of photosynthesis and thus the addition of DM can result in more diagnostic information. The M-DRIS and DRIS diagnostic methods of parameter selection are the same. The parameters include the ratio of each nutrient to DM, such as N/DM, P/DM, etc. Therefore, when calculating the M-DRIS index of a nutrient X, f(X/DM) is involved in the calculation, the DM index is calculated by referring to the calculation method of Equation (1), and the algebraic sum of all the M-DRIS indices is zero.

The DOP index method is the “deviation from the appropriate value percent method”, and although its reflection of the interaction between the elements is not as good as the DRIS method, it has the advantage of being a simple calculation method that is easy to promote. The algebraic sum of the DOP index is not necessarily zero, and the DOP index calculation formula is as follows:

DOPx = [(Cx × 100)/Cm] − 100

(2)

where DOPx is a given nutrient element diagnostic index for the leaves, Cx is the content of a mineral element in the leaves, and Cm is the content of the appropriate value of the element of the high-yielding orchard. NBIm (NBIm = Σ|DOPx|/n) is used to express the nutrient imbalance index, where n is the number of diagnosed mineral elements. When |DOPx| ≤ NBIm indicates normal content, DOPx < 0 and |DOPx| > NBIm indicate an element deficiency in the leaves, and DOPx > 0 and |DOPx| > NBIm indicate an element excess in the leaves.

2.4. Data Statistics and Analysis

The t-test for independent samples and Pearson correlation analysis were performed on the data using SPSS 24.0 (IBM SPSS Corp., Chicago, IL, USA), the correlation plots were drawn using R language and sampling schematics, and the DRIS diagnostic maps were drawn using CorelDraw 2019 (Corel Corporation, Ottawa, ON, Canada).

3. Results

3.1. Analysis of the Soil and Mango Leaf Physicochemical Properties in the Tainong Orchards

Comparing the physical and chemical properties of the soils in the high-, medium-, and low-yielding orchards (

Table 1. The soil physicochemical properties of the mango orchards with different yields.

Soil Physicochemical Properties	Low-Yield Orchards	Mid-Yield Orchards	High-Yield Orchards
pH	5.85 ± 0.79 a	6.02 ± 0.73 a	4.78 ± 0.08 b
Soil organic matter (g/kg)	26.26 ± 4.02 a	29.66 ± 6.00 a	20.50 ± 3.00 b
Alkali-hydrolyzable nitrogen (mg/kg)	115.00 ± 4.80 a	125.46 ± 17.02 a	40.83 ± 18.46 b
Available potassium (mg/kg)	102.60 ± 17.57 a	117.62 ± 41.24 a	37.77 ± 22.73 b
Exchangeable calcium (g/kg)	3.22 ± 1.95 a	3.80 ± 2.11 a	0.29 ± 0.06 b
Exchangeable magnesium (g/kg)	0.13 ± 0.03 a	0.14 ± 0.03 a	0.04 ± 0.00 b
Effective sulfur (mg/kg)	13.87 ± 10.38 a	14.95 ± 9.13 a	12.97 ± 3.13 a
Effective iron (mg/kg)	49.96 ± 16.14 b	44.60 ± 17.5 b	108.40 ± 84.83 a
Effective manganese (mg/kg)	132.18 ± 31.54 a	107.63 ± 43.79 a	3.58 ± 1.80 b
Effective copper (mg/kg)	1.77 ± 0.37 a	1.66 ± 0.57 a	0.91 ± 0.39 b
Effective zinc (mg/kg)	1.49 ± 0.41 a	1.41 ± 0.80 a	0.90 ± 0.61 a
Effective boron (mg/kg)	0.16 ± 0.05 a	0.19 ± 0.05 a	0.08 ± 0.04 b

Lowercase letters ^a and ^b in the same column indicate significant differences (p < 0.05).

), it was found that the soils in the medium- and low-yielding orchards in the karst areas had higher element contents than those in high-yielding orchards, except for the effective Fe content which was significantly lower than in the high-yielding orchards in non-karst areas. This indicates that the soils in the karst areas were richer in mineral nutrients, but there was an imbalance between excess and lacking elements. The results of the DRIS, M-DRIS, and DOP index methods were combined with the DRIS graphical method and Tainong’s suitable critical range to analyze the fertilizer requirements for the low- and medium-yielding mango orchards. Those for the low-yielding orchards were Mg > Fe > S > Zn > B > Cu > K > N > P > Mn > Ca, and those for the medium-yielding orchards were Mg > Fe > B > Zn > S > Cu > N > Mn > K > P > Ca. Additionally, it was found that Ca in the leaves of the medium- and low-yielding orchards was in serious excess, which is related to the fact that karst ecosystems are influenced by the Ca-rich geological background of the carbonate rocks and the plants absorb much higher calcium content than the plants in non-karst areas. This was followed by the degree of excess in Mn, which was greater in the low-yielding than that in the medium-yielding orchards. Thus, the main deficiencies in the leaves of the medium- and low-yielding orchards were in Mg and Fe, and small deficiencies were detected for S and B. These excess or deficient elements were the focus of this study.

The correlation analysis between the effective states of the soils in the medium- and low-yielding orchards (p < 0.05) as shown in Figure 3, determined that the soil pH, exchangeable Ca, and effective Fe were significantly negatively correlated with each other. The leaf Ca was significantly negatively correlated with Fe, indicating that the calcium-rich and alkaline soil conditions in the karst areas inhibit the uptake of Fe by plants to a certain extent.

In this study, the soil water and soil effective Mn contents were high in the low-yielding orchards, and the soil water content was normal and low in the medium-yielding orchards. Furthermore, the soil effective Mn was negatively correlated and greater than all the other elements except the effective Cu, Zn, and Fe, and the contents of the leaf Mn in the medium- and low-yielding orchards were higher than the diagnostic suitable range, while the leaf Mn, Mg, and Fe were negatively correlated. This indicates that the high content of the soil effective Mn inhibited the uptake of the other elements by the leaves to some extent, and it was inferred that the yield reduction in the mango orchards was related to the excess of soil and leaf Mn. The soil effective S and B contents of the medium- and low-yielding mango orchards in the study area were at very deficient levels with reference to the second national soil census nutrient grading standard, which is the direct cause of the S and B deficiency in the fruit trees.

3.2. Analysis of the Nutritional Diagnostic Parameters of Tainong Leaves

There were significant statistical differences (p < 0.05) or highly significant statistical differences (p < 0.001); P/Mg and S/Fe had highly significant differences in the high- and low-yielding orchards, while N/S and Ca/Cu had highly significant differences in the high- and medium-yielding orchards. Thus, the diagnostic parameters with statistically significant differences in the nutrient elements may be the factors affecting the yield of the mango orchards (

Table 2. The statistics of the Diagnosis and Recommendation Integrated System diagnostic parameters of Tainong mangoes.

Nutrient Forms	Low-Yield Orchards		Medium-Yield Orchards		High-Yield Orchards		Ratio of Variance
	(n = 25)		(n = 65)		(n = 15)
	Mean ± SD	CV (%)	Mean ± SD	CV (%)	Mean ± SD	CV (%)	VL/VH	VM/VH
N	18.17 ± 1.68 a	9.25	16.85 ± 1.08 ab	6.43	16.07 ± 0.90 b	5.6	3.48	1.45
P	0.99 ± 0.12 a	12.59	1.02 ± 0.25 a	24.78	0.79 ± 0.08 a	9.56	2.73	11.11 *
K	6.38 ± 0.61 ab	9.56	6.89 ± 0.81 a	11.73	5.67 ± 0.92 b	16.16	0.44	0.78
Ca	24.00 ± 2.11 a	8.78	23.71 ± 2.59 a	10.94	13.03 ± 2.64 b	20.26	0.64 **	0.96 **
Mg	1.13 ± 0.16 b	14.03	1.21 ± 0.18 b	14.7	1.82 ± 0.73 a	39.79	0.05	0.06
S	0.91 ± 0.10 a	11.07	0.81 ± 0.05 a	6.03	0.90 ± 0.12 a	13.07	0.73	0.17
Fe	0.09 ± 0.01 b	8.48	0.09 ± 0.01 b	12.48	0.11 ± 0.01 a	10.19	0.43 *	0.92 **
Mn	1.48 ± 0.88 a	59.3	1.07 ± 0.45 a	42.18	0.82 ± 0.16 a	19.02	31.92	8.51
Cu	7.25 ± 2.15 a	29.71	5.77 ± 2.28 a	39.57	7.15 ± 3.32 a	46.38	0.42	0.47
Zn	13.08 ± 2.81 a	21.48	11.88 ± 1.66 a	13.98	13.43 ± 4.14 a	30.82	0.46	0.16
B	11.24 ± 2.17 a	19.32	10.81 ± 2.25 a	20.79	12.29 ± 7.52 a	61.15	0.08	0.09
P/N	0.05 ± 0.00 a	4.47	0.06 ± 0.01 a	0.23	0.05 ± 0.00 a	4.97	0.99 *	32.37 *
K/N	0.35 ± 0.01 a	2.67	0.41 ± 0.06 a	0.13	0.35 ± 0.07 a	19.66	0.02	0.63
Ca/N	1.32 ± 0.07 a	4.94	1.41 ± 0.10 a	0.07	0.81 ± 0.12 b	14.94	0.29 **	0.71 **
N/Mg	16.29 ± 1.67 a	10.25	14.14 ± 1.92 a	13.56	9.53 ± 2.69 b	28.29	0.38 **	0.51 **
N/S	19.99 ± 1.09 a	5.47	20.84 ± 0.99 a	4.77	17.93 ± 1.50 b	8.36	0.53	0.44 **
N/Fe	203.31 ± 15.38 a	7.57	192.37 ± 27.85 a	14.48	142.54 ± 12.90 b	9.05	1.42 **	4.66 *
Mn/N	0.09 ± 0.06 a	66.27	0.06 ± 0.03 a	0.42	0.05 ± 0.01 a	22.99	22.94	5.21
Cu/N	0.40 ± 0.10 a	25.11	0.34 ± 0.12 a	0.36	0.44 ± 0.19 a	42.49	0.28	0.44
N/Zn	1.44 ± 0.34 a	23.93	1.45 ± 0.28 a	19.14	1.26 ± 0.29 a	23.23	1.4	0.91
N/B	1.68 ± 0.46 a	27.56	1.64 ± 0.47 a	28.66	1.65 ± 0.89 a	54.28	0.27	0.28
P/K	0.15 ± 0.01 a	3.24	0.15 ± 0.03 a	18	0.14 ± 0.03 a	19.51	0.03	0.91
Ca/P	24.40 ± 2.20 a	9.04	24.38 ± 5.64 a	0.23	16.39 ± 1.74 b	10.59	1.61 **	10.56 *
P/Mg	0.89 ± 0.10 a	11.54	0.86 ± 0.30 a	34.78	0.46 ± 0.12 b	25.72	0.73 **	6.32
P/S	1.09 ± 0.04 a	3.86	1.26 ± 0.34 a	26.66	0.88 ± 0.03 a	3.46	1.9 **	122.72 **
P/Fe	11.05 ± 0.90 a	8.15	11.63 ± 3.43 a	29.47	6.98 ± 0.42 b	6	4.61 **	66.83 **
Mn/P	1.60 ± 1.13 a	70.66	1.11 ± 0.53 a	0.48	1.05 ± 0.30 a	28.17	14.52	3.22
P/Cu	0.14 ± 0.03 a	19.89	0.20 ± 0.09 a	43.18	0.13 ± 0.06 a	47.58	0.21	2
P/Zn	0.08 ± 0.02 a	23.51	0.09 ± 0.02 a	24.39	0.06 ± 0.01 a	19.16	2.46	3.23
P/B	0.09 ± 0.03 a	31.23	0.10 ± 0.04 a	42.72	0.08 ± 0.04 a	49.45	0.54	1.2
Ca/K	3.77 ± 0.26 a	6.85	3.49 ± 0.61 a	0.17	2.35 ± 0.68 b	29.01	0.14 *	0.79 *
K/Mg	5.73 ± 0.70 a	12.26	5.87 ± 1.54 a	26.15	3.46 ± 1.41 b	40.74	0.25 *	1.18 *
K/S	7.02 ± 0.27 ab	3.81	8.55 ± 1.25 a	14.61	6.37 ± 1.34 b	20.98	0.04	0.88 *
K/Fe	71.36 ± 4.63 a	6.5	78.27 ± 11.81 a	15.09	50.17 ± 7.02 b	13.98	0.44 **	2.84 **
Mn/K	0.24 ± 0.17 a	68.3	0.16 ± 0.08 a	0.52	0.15 ± 0.04 a	26.71	18	4.69
K/Cu	0.92 ± 0.20 a	21.81	1.34 ± 0.44 a	33.09	0.94 ± 0.47 a	50.19	0.18	0.88
K/Zn	0.50 ± 0.11 a	22.14	0.59 ± 0.10 a	16.52	0.45 ± 0.15 a	33.05	0.56	0.43
K/B	0.59 ± 0.17 a	28.18	0.67 ± 0.19 a	28.03	0.59 ± 0.32 a	53.63	0.28	0.35
Ca/Mg	21.56 ± 2.64 a	12.25	19.87 ± 2.96 a	14.88	7.49 ± 1.38 b	18.42	3.66 **	4.59 **
Ca/S	26.49 ± 2.65 a	10.02	29.33 ± 2.91 a	9.91	14.36 ± 1.02 b	7.07	6.83 **	8.2 **
Ca/Fe	269.35 ± 29.60 a	10.99	270.38 ± 43.87 a	16.22	114.56 ± 15.60 b	13.62	3.6 **	7.9 **
Ca/Mn	21.61 ± 13.27 a	61.4	26.88 ± 14.15 a	52.66	16.70 ± 6.13 a	36.72	4.68	5.33
Ca/Cu	3.52 ± 0.99 ab	28.08	4.48 ± 1.17 a	26.03	2.05 ± 0.78 b	38.26	1.59	2.21 **
Zn/Ca	0.55 ± 0.15 b	26.75	0.51 ± 0.11 b	0.22	1.02 ± 0.10 a	10.32	1.98 **	1.11 **
Ca/B	2.21 ± 0.53 a	24.18	2.32 ± 0.71 a	30.54	1.26 ± 0.51 b	40.64	1.09	1.91*
S/Mg	0.82 ± 0.10 a	11.74	0.68 ± 0.09 ab	0.13	0.53 ± 0.12 b	23.32	0.61 *	0.48 *
Fe/Mg	0.08 ± 0.01 a	12.91	0.08 ± 0.02 a	0.22	0.07 ± 0.02 a	29.44	0.28	0.68
Mn/Mg	1.38 ± 0.87 a	63.35	0.86 ± 0.31 ab	0.35	0.51 ± 0.23 b	46.08	14.02	1.73
Cu/Mg	6.45 ± 1.63 a	25.32	4.76 ± 1.63 ab	0.34	3.93 ± 1.33 b	33.9	1.51	1.49
Mg/Zn	0.09 ± 0.02 b	27.65	0.10 ± 0.02 ab	23.28	0.13 ± 0.01 a	10.08	3.39 *	3.24
B/Mg	10.30 ± 3.16 a	30.67	9.23 ± 2.78 a	0.3	6.42 ± 1.81 a	28.18	3.05	2.37
S/Fe	10.17 ± 0.45 a	4.46	9.23 ± 1.32 ab	14.27	7.96 ± 0.60 b	7.49	0.58 **	4.89
Mn/S	1.72 ± 1.19 a	69.28	1.33 ± 0.58 a	0.43	0.93 ± 0.29 a	31.46	16.52	3.87
Cu/S	7.84 ± 1.55 a	19.71	7.07 ± 2.51 a	0.36	7.70 ± 2.80 a	36.33	0.31	0.8
S/Zn	0.07 ± 0.01 a	20.34	0.07 ± 0.01 a	19.23	0.07 ± 0.01 a	16.07	1.71	1.44
S/B	0.08 ± 0.03 a	30.75	0.08 ± 0.02 a	26.69	0.09 ± 0.04 a	46.5	0.39	0.25
Mn/Fe	17.09 ± 11.27 a	65.94	12.40 ± 6.03 a	0.49	7.36 ± 2.23 a	30.3	25.58	7.33
Cu/Fe	79.90 ± 16.95 a	21.21	65.67 ± 27.90 a	0.42	61.59 ± 24.46 a	39.71	0.48	1.3
Zn/Fe	146.06 ± 29.69 a	20.33	135.49 ± 26.14 a	0.19	117.61 ± 28.79 a	24.48	1.06	0.82
B/Fe	127.65 ± 33.94 a	26.59	122.14 ± 24.92 a	0.2	105.73 ± 58.58 a	55.4	0.34	0.18
Mn/Cu	0.24 ± 0.21 a	86.6	0.21 ± 0.13 a	60.46	0.15 ± 0.11 a	74.99	3.63	1.3
Mn/Zn	0.12 ± 0.09 a	73.67	0.09 ± 0.04 a	39.06	0.07 ± 0.03 a	44.45	8.9	1.45
Mn/B	0.13 ± 0.05 a	42.32	0.11 ± 0.06 a	52.34	0.09 ± 0.07 a	74.11	0.61	0.67
Cu/Zn	0.56 ± 0.14 a	25.03	0.52 ± 0.30 a	57.47	0.52 ± 0.15 a	28.16	0.92	4.18
Cu/B	0.69 ± 0.34 a	48.89	0.56 ± 0.28 a	50.19	0.61 ± 0.12 a	20.03	7.55	5.31
B/Zn	0.90 ± 0.29 a	32.46	0.92 ± 0.19 a	0.2	0.86 ± 0.28 a	32.12	1.11	0.45

*. Significantly different at the 0.05 level, **. Significantly different at the 0.001 level. Lowercase letters ^a and ^b in the same column indicate significant differences up to a significant level (p < 0.05). (Elements Cu, Zn, and B are in mg/kg and the rest of elements are in g/kg).

).

3.3. Diagnosis Using the Diagnosis and Recommendation Integrated System Graphical Method

The eleven nutrient elements of the mango leaves in this study were divided into four groups for the graphical method diagnosis (Figure 4), and for the convenience of the calculation the N, P, K, Ca, Mg, S, Fe, and Mn units were g/kg, while the Cu, Zn, and B units were mg/kg.

The three elements of N, P, and K were selected as the important ratio parameters as P/N, K/N, and P/K, and the three ratio averages of 0.049, 0.355, and 0.142 were used as the center of each circle, respectively. Then, 2/3 times the standard deviation was used as the inner orchard radius, corresponding to the inner orchard radii of 0.002, 0.047, and 0.018, respectively; and 4/3 times the standard deviation was used as the outer circle radius, corresponding to the outer circle radii of 0.003, 0.093, and 0.037, respectively. Using P/N as an example, in terms of the P/N ratio range: 0.047–0.051, the contents of P and N were balanced; 0.051–0.052, the P content was high and the N content was low; 0.047–0.046, the N content was high and the P content was low; >0.052, there was an excess of P and a lack of N; and <0.046, there was an excess of N and a lack of P. This shows that the smaller the P/N, the greater the excess in N and lack in P. Moreover, the larger the P/N, the greater the lack of N and excess P. Similarly, the proportional relationship between P/K and K/N could be determined. The graphical method showed that the optimal ratio ranges of the N, P, and K element contents were P/N = 0.049 ± 0.02; P/K = 0.142 ± 0.018; and K/N = 0.355 ± 0.047.

The important ratio parameters among the Ca, Mg, and S elements were Ca/Mg, Ca/S, and S/Mg. The circle centers of the three ratio parameters were 7.489, 14.356, and 0.527, and the radii of the inner and outer circles of Ca/Mg were 0.920 and 1.840, respectively; the radii of the inner and outer circles of Ca/S were 0.677 and 1.354, respectively; and the radii of the inner and outer circles of S/Mg were 0.082 and 0.164, respectively. When the coordinates were extended outward from the center of the circle, the degree of imbalance between the elements gradually increased, the area between the inner and outer circles was slightly imbalanced, the area outside the outer circle was significantly imbalanced, and the final suitable range for the ratio was given as Ca/Mg = 7.489 ± 0.920; Ca/S = 14.356 ± 0.677; and S/Mg = 0.527 ± 0.082.

The important ratio parameters among Fe, Mn, and Cu were Mn/Fe, Cu/Fe, and Mn/Cu, and the circle centers of the three ratio parameters were 7.356, 61.594, and 0.147, respectively; the inner and outer circle radii of Mn/Fe were 1.486 and 2.971, respectively; the inner and outer circle radii of Cu/Fe were 16.307 and 32.614, respectively; the inner and outer circle radii of Mn/Cu were 0.074 and 0.147, respectively; and the suitable ranges were Mn/Fe = 7.356 ± 1.486; Cu/Fe = 61.594 ± 16.307; and Mn/Cu = 0.147 ± 0.074.

Zn and B were selected for the DRIS graphical diagnosis together with their ratios with significant differences including Ca. The important ratio parameters between the three elements were Zn/Ca, Ca/B, and B/Zn, and the circle centers of the three ratio parameters were 1.017, 1.259, and 0.861, respectively. The inner and outer circle radii of Zn/Ca were 0.070 and 0.140, those of Ca/B were 0.341 and 0.682, and those of B/Zn were 0.184 and 0.369, respectively. Additionally, the suitable ranges of the proportions were Zn/Ca = 1.107 ± 0.07; Ca/B = 1.259 ± 0.341; and B/Zn = 0.861 ± 0.184.

3.4. Diagnosis and Recommendation Integrated System Diagnostic Index and Fertilizer Requirement Order

Among the 55 ratio parameters screened, only six of the low-yielding orchards had negative deviations from the high-yielding orchards, and only seven of the medium-yielding orchards had negative deviations, while the rest were positive (

Table 3. The statistics of the Diagnosis and Recommendation Integrated System of the extent of deviation in the high-yielding orchards of Tainong mangoes.

f (X/Y)	Deviation Degree		f (X/Y)	Deviation Degree
	Low-Yield Orchards	Medium-Yield Orchards		Low-Yield Orchards	Medium-Yield Orchards
f (P/N)	21.59	45.42	f (Ca/S)	119.50	147.49
f (K/N)	−0.53	7.91	f (Ca/Fe)	99.19	99.86
f (Ca/N)	42.75	49.63	f (Ca/Mn)	8.01	16.61
f (N/Mg)	25.09	17.12	f (Ca/Cu)	18.77	31.01
f (N/S)	13.73	19.43	f (Zn/Ca)	−81.77	−96.21
f (N/Fe)	47.12	38.63	f (Ca/B)	18.57	20.70
f (Mn/N)	28.78	10.51	f (S/Mg)	23.59	12.33
f (Cu/N)	−2.60	−6.87	f (Fe/Mg)	6.73	4.07
f (N/Zn)	6.38	6.74	f (Mn/Mg)	37.41	15.40
f (N/B)	0.39	−0.04	f (Cu/Mg)	18.96	6.30
f (P/K)	4.70	1.83	f (Mg/Zn)	−48.45	−28.05
f (Ca/P)	46.15	46.06	f (B/Mg)	21.47	15.56
f (P/Mg)	35.25	33.42	f (S/Fe)	37.05	21.31
f (P/S)	68.25	126.42	f (Mn/S)	26.89	13.61
f (P/Fe)	96.98	110.90	f (Cu/S)	0.50	−2.48
f (Mn/P)	18.44	1.92	f (S/Zn)	2.06	0.20
f (P/Cu)	2.25	11.75	f (S/B)	−1.21	−3.01
f (P/Zn)	14.50	21.51	f (Mn/Fe)	43.69	22.62
f (P/B)	3.23	5.37	f (Cu/Fe)	7.48	1.67
f (Ca/K)	20.91	16.86	f (Zn/Fe)	9.88	6.21
f (K/Mg)	16.09	17.09	f (B/Fe)	3.74	2.80
f (K/S)	4.85	16.35	f (Mn/Cu)	8.67	5.50
f (K/Fe)	30.21	40.06	f (Mn/Zn)	18.01	8.29
f (Mn/K)	24.69	4.14	f (Mn/B)	5.01	2.13
f (K/Cu)	−0.32	8.44	f (Cu/Zn)	2.78	0.07
f (K/Zn)	3.61	9.36	f (Cu/B)	6.27	−4.38
f (K/B)	0.05	2.49	f (B/Zn)	1.27	2.05
f (Ca/Mg)	102.00	89.69	-	-	-

). This is due to the relative excess of most of the elements and the relative deficiency of a few elements; for example, the partial functions of Ca and the other elements were all positive and had large values, indicating that the Ca content was in excess relative to the other elements. Additionally, the partial function of Mg/Zn was negative, indicating a serious deficiency of Mg relative to Zn. From the DRIS index values (Table 3), it can be seen that the larger the absolute value of the negative deviation the more lacking the element, and the larger the positive deviation the greater the excess in the element. In general, the middle- and low-yielding orchards were diagnosed with lacking the elements Fe, Mg, S, Zn, and B, and the elements in excess were Ca, P, K, and Mn. Moreover, the order of the elements that were lacking or in excess was slightly different: the middle-yielding orchards lacked Cu and N, the middle- and low-yielding orchards had Ca in excess, and the low-yielding orchards had Mn in excess that was greater than that of the middle-yielding orchards. Furthermore, the DRIS diagnostic index was ranked in the order of fertilizer needs for the middle- and low-yielding orchards.

3.5. Modified Diagnosis and Recommendation Integrated System and Deviation from Optimum Percentage Diagnostic Indices and Fertilizer Requirement Order

To test the scientificity of the diagnostic results of the DRIS index method, the M-DRIS and DOP indices were used to diagnose the middle- and low-yielding orchards. For the diagnostic results and fertilizer requirements of the medium- and low-yielding orchards, the implications of the DRIS, M-DRIS, and DOP indices were the same: a greater negative value indicated that the plant had a greater demand for the element, a greater positive value indicated that the plant had an excess of the element, and the closer it was to zero the more balanced the elements. The M-DRIS method diagnosed the elements that were lacking in the low-yielding orchard as Fe, Mg, and S, and the elements in excess as Zn, B, Cu, K, N, P, Mn, and Ca; the elements lacking in the middle-yielding orchard were Fe, S, Mg, Zn, and Cu, and the elements in excess were N, B, Mn, K, P, and Ca. The DOP diagnostic index was directly calculated, and the diagnostic results were somewhat different from those of the DRIS and M-DRIS methods. The elements deficient in the DOP index method for the low-yielding orchards were Mg, Fe, Cu, B, Zn, and S, and the elements in excess were N, K, P, Mn, and Ca; the elements deficient in the medium-yielding orchards were Mg, Fe, B, and Zn, and the elements in excess were S, Cu, K, N, P, Mn, and Ca. The most deficient element in the diagnosis of the medium- and low-yielding orchards was the Mg element, followed by the Fe element, which is opposite to the diagnosis of the DRIS and M-DRIS methods. The diagnostic index and fertilizer requirement order are shown in

Table 4. The diagnostic index and fertilizer requirement order for Tainong mangoes.

Orchard Yields	Index	Nutritional Elements
		N	P	K	Ca	Mg	S	Fe	Mn	Cu	Zn	B	DM
Low-yield Orchards	DRIS index	0.24	18.26	0.37	55.76	−33.50	−17.22	−36.86	20.34	0.40	−7.21	−0.58
	order of fertilizer requirement	Fe > Mg > S > Zn > B > N > K > Cu > P > Mn > Ca
	M-DRIS index	2.23	18.94	1	54.42	−31.89	−15.62	−35.93	22.36	0.38	−6.65	−0.68	−8.56
	order of fertilizer requirement	Fe > Mg > S > DM > Zn > B > Cu > K > N > P > Mn > Ca
	DOP index	4.85	28.55	21.37	81.93	−33.58	−10.36	−21.57	31.56	−19.32	−11.59	−12.02
	order of fertilizer requirement	Mg > Fe > Cu > B > Zn > S > N > K > P > Mn > Ca
Medium-yield orchards	DRIS index	−2.55	30.94	7.89	61.41	−23.90	−28.98	−34.00	6.74	−6.24	−11.02	−0.29
	order of fertilizer requirement	Fe > S > Mg > Zn > Cu > N > B > Mn > K > P > Ca
	M-DRIS index	−1.54	30.81	8.37	59.49	−22.89	−27.16	−33.36	7.63	−6.14	−10.41	−0.47	−4.33
	order of fertilizer requirement	Fe > S > Mg > Zn > Cu > DM > N > B > Mn > K > P > Ca
	DOP index	13.07	25.32	12.5	84.14	−38.3	0.99	−21.03	81.22	1.33	−2.67	−8.54
	order of fertilizer requirement	Mg > Fe > B > Zn > S > Cu > K > N > P > Mn > Ca

DRIS: Diagnosis and Recommendation Integrated System (DRIS) graphical method; M-DRIS: the Modified DRIS; DOP: Deviation from Optimum Percentage.

.

3.6. Nutrient Element Correlation Analysis and Diagnostic Critical Grading of the Mango Leaves

In this study, a correlation analysis of the nutrient element contents of the leaves of all the mango orchards was performed (Figure 5). The results showed that there were highly significant positive correlations between N and Ca, S, and P; K and S; and Cu, Zn, and B. Then, P and Ca and Mg and S, Fe, and B were significantly positively correlated, and K and Mg, Ca, and Fe were significantly negatively correlated. Meanwhile, K was negatively correlated with all the other elements except for P and Ca, Ca was negatively correlated with Mg, S, Zn, and B, and Mn was negatively correlated with all the elements except B.

The critical standard for the Tainong mango was determined by the different relationships between the mean and standard deviation of each element in the high-yielding orchard, and the diagnostic critical range of N, P, K, Ca, S, Fe, and Mn in the high-yielding orchard was obtained. The diagnostic range of the Mg, Cu, and B elements was too large due to the large coefficient of variation and the direct determination of the diagnostic range, so an exploratory analysis test was conducted on the nutritional elements of Mg, Cu, and B in the leaves, and the results obeyed the normal distribution. Then, the probability grading method was used to correct their content values and determine the nutritional diagnostic content grading of the Tainong mango leaves (

Table 5. The Tainong mango diagnostic critical grading.

Nutritional Elements	Serious Lack	Lack	Balance	Excess	Serious Excess
N (g/kg)	<13.67	13.67~14.87	14.87~17.27	17.27~18.47	>18.47
P (g/kg)	<0.59	0.59~0.69	0.69~0.89	0.89~0.99	>0.99
K (g/kg)	<3.23	3.3~4.45	4.45~6.90	6.9~8.12	>8.12
Ca (g/kg)	<5.99	5.99~9.51	9.51~16.55	16.55~20.08	>20.08
Mg (g/kg)	<0.89	0.89~1.44	1.44~2.20	2.20~2.75	>2.75
S (g/kg)	<0.59	0.59~0.75	0.75~1.06	1.06~1.22	>1.22
Fe (g/kg)	<0.08	0.08~0.10	0.10~0.13	0.13~0.14	>0.14
Mn (g/kg)	<0.40	0.4~0.61	0.61~1.02	1.02~1.23	>1.23
Cu (mg/kg)	<2.9	2.9~5.41	5.41~8.89	8.89~11.4	>11.4
Zn (mg/kg)	<2.39	2.39~7.91	7.91~18.95	18.95~24.47	>24.47
B (mg/kg)	<2.66	2.26~8.35	8.38~16.23	16.23~21.82	>21.92

).

4. Discussion

According to the principle of the plant nutrient balance, when the contents of each element and the ratio between the elements in the plant reach the optimum value, the productivity of the plant may reach the optimal state [5]. Based on this principle, the leaf mineral nutrition DRIS graphical method is very comprehensive in terms of showing the interrelationship of the three elements ratio. Therefore, this study compared the three elements DRIS graphical method for N, P, and K and found that the ratio of the demand for these three elements varied greatly between the different orchards [31,32]. Few studies have applied the DRIS graphical method to the nutritional diagnosis of mango leaves. Thus, for mango orchard yield, the study developed a criterion to judge the suitability of the ratio of the corresponding nutritional elements in Tainong leaves. Since the DRIS graphical method can only show the proportional relationship of three elements at a time, it is not suitable for analyzing the relationship between multiple elements.

The partial functions calculated using the DRIS index method for the medium- and low-yielding orchards indicated that the limiting factor was the deficiency of a few elements, but the vast majority of the elements were sufficiently present. The diagnostic critical range of the Tainong leaves in this study was compared to other varieties of mangoes in terms of the diagnostic suitable values as shown in Table 5. It was found that the content of the nutrient elements in the leaves of the different kinds of mangoes mostly followed the order of Ca > N > K > Mg > S > P > Mn > Fe > B > Zn > Cu. This may be related to the period of sampling. When comparing the leaf nutritional diagnostic suitable range of this study to that of the Hainan Tainong mango at the flowering stage, the contents of Ca, S, and B in the Tainong leaves were lower than those of the Hainan Tainong leaves [33]. The suitable range for Fe in the Tainong leaves in this study was higher. When comparing the suitable range of the different varieties of mango leaves, there were different degrees of differences, such as in the suitable range of S in the mango leaves of Guangxi Guire No. 82 [34], K in the mango leaves of Yunnan Palayinda [35], and B in the mango leaves of Sichuan Keitt [36] (which was the highest) (

Table 6. The appropriate values for leaf nutrient diagnosis during the reproductive growth period of different varieties of mangoes in different regions.

Nutritional Elements	Tainong	Tainong	Guire 82	Palayinda	Kaite
	This Study	Hainan [33]	Guangxi [34]	Yunnan [35]	Sichuan [36]
N (g/kg)	14.87~17.27	16.11~18.51	13.97~16.4	11.92~15.92	14.19~18.23
P (g/kg)	0.69~0.89	0.97~1.26	0.93~1.16	0.81~1.17	0.90~1.15
K (g/kg)	4.45~6.90	2.25~6.53	5.71~8.21	6.55~9.48	6.47~8.08
Ca (g/kg)	9.51~16.55	19.03~28.87	19.43~28.57	13.00~18.76	14.68~24.10
Mg (g/kg)	1.44~2.20	1.6~2.33	1.55~2.05	1.71~2.09	1.38~1.57
S (g/kg)	0.75~1.06	1.35~1.69	1.21~1.82	1.18~1.45	1.44~1.72
Fe (mg/kg)	100.0~130.0	20.05~67.76	41.77~95.95	52.87~81.7	67.94~84.92
Mn (mg/kg)	610.0~1020.0	939.19~1232.52	339.36~797.72	50.22~1140.68	121.89~520.02
Cu (mg/kg)	5.41~8.89	2.85~7.40	6.99~10.4	6.79~12.29	3.57~7.69
Zn (mg/kg)	7.91~18.95	11.92~20.67	7.89~15.72	10.41~16.13	10.82~16.06
B (mg/kg)	8.38~16.23	20.55~42.52	18.96~28.17	13.87~22.13	19.21~50.49

).

By comparing the results of the DRIS, M-DRIS, and DOP methods in the study, it was found that the diagnostic results of the DRIS and M-DRIS methods were close to each other and slightly different from the diagnostic results of the DOP method. The results reflected the advantages of the DRIS and M-DRIS methods in diagnosing the relative content of two elements, while the DOP method was more suitable for the diagnosis of one element since its separate calculation is not affected by other elements. For example, when determining the order of the fertilizer requirements for Mg and Fe in the medium- and low-yielding orchards, combined with the suitable diagnostic range of the two elements in Table 4, it was concluded that the demand for Mg in the medium- and low-yielding orchards was greater than that for Fe. This was more compatible with the diagnostic results of the DOP method. The results suggest that either method can be chosen, when applying the DRIS and M-DRIS index methods for plant nutrition diagnosis in the future.

The imbalance indices of DRIS and M-DRIS for the medium- and low-yielding orchards were expressed by NII, and the DOP method was expressed by NBI_m [37]. The DRIS method calculated an NII index of 17.34 for the low-yielding orchards and 19.45 for the medium-yielding orchards. The M-DRIS method calculated an NII index of 18.06 and 19.33 for the low- and medium-yielding orchards, respectively. The results of the two methods were similar for the medium-yielding orchards. On the other hand, the degree of imbalance was higher for the low-yielding orchards, and this result was different from the significant negative correlation between the fruit tree yield and NII that was found by Davee [38] and Parent [39]. This indicates that for orchards with a relatively close degree of imbalance, the diagnostic results of the DRIS and M-DRIS methods may contain some errors, and exposes the shortcomings of the DRIS method in diagnosing relatively lower or higher levels of poor diagnostic effects [18]. Furthermore, the DOP method calculated the NBIm value as 26.28 for the low-yielding orchards, which were greater than 25.15 for the medium-yielding orchards, which indicates a higher degree of imbalance in the low-yielding orchards. The result is better supported since the sizes of the NBI_m index in the high-yielding brown loam orchards and low-yielding brown soil orchards were consistent with the NII results [40].

When applying the leaf mineral nutrient diagnosis in the karst area, the study suggested the appropriate diagnostic site should be selected at the appropriate diagnostic period, and a combination of multiple diagnostic methods can yield more scientific and accurate diagnostic results, for better orchard fertilization recommendations. Consequently, the DRIS graphical method is suitable for the diagnosis of three nutrient elements, and since the DRIS and M-DRIS index method diagnostic results were similar, either can be chosen. The order of the fertilizer requirements for the middle- and low-yielding orchards of Tainong mangoes in the karst area was relative, and the actual supplementation of the nutrient elements still needs to be verified by fine fertilization. Thus, nutrient diagnosis requires a combination of methods to obtain a more reliable result.

5. Conclusions

After applying various leaf nutrient diagnostic methods to Tainong mango orchards, the study suggested that the DRIS graphical and M-DRIS methods are the most suitable for the rapid and accurate nutritional diagnosis of mango trees in the mango orchards in karst areas. The DRIS diagnostic standard value for the high-yielding orchards was suggested to assess the suitable critical range for the Tainong mango diagnosis in the karst areas.

Based on a correlation analysis of the soil effective state and leaves, the reason for the difference in the yield between medium- and low-yielding orchards was probably closely related to the lack of Mg and excess of Mn. The deficiency of Mg and Fe, the low contents of S and B, and the excess of Ca and Mn were common in the mango orchards in the typical karst areas of Baise. The study can be used for the precise fertilization of mango orchards to improve the yield and quality of mango orchards in karst areas.