Compositional Nutrient Diagnosis Research Articles

Efficient detection of nutrient deficiencies and development of corrections in avocado through the Compositional Nutrient Diagnosis (CND)

Mexico is the main producer of avocado (Persea americana Mill.), contributing 31% of the world supply, which provides the country with an annual income of more than 2 billion dollars. The increase in national production is the result of a larger cultivated area, and not an increase in yields. In the State of Mexico, Mexico around 10 thousand hectares are cultivated with avocado trees, although 77% of the producers do not have specialized technical advice that offers reliable information on crop nutrition. This lack of advice and technical support detracts from volume and quality of production. The objective of this research was to carry out the nutritional diagnosis of an avocado orchard in Tejupilco, State of Mexico, Mexico, through the Compositional Nutrient Diagnosis (CND), and to generate specific fertilization recommendations for the study area, for which leaf and soil analyses were carried out. Each nutrient determined in the leaf analysis (N, P, K, Ca, Mg, S, Fe, Mn, Zn, Cu, and B) was compared with its optimal concentration according to literature. The CND yielded relative deficiency or excess indices that determined the order of nutritional limitation. Zn, B, S, and K deficiencies were detected in all sampled areas, while P, Mn, and Cu were deficient only in some areas. N, Ca, Mg, and Fe did not show nutritional limitation. Recommendations were formulated to address each of the nutritional deficiencies and the problem of sodicity revealed by the soil analysis. This is the first work in which the CND is used to assess the nutritional situation of avocado orchards in the world.

Diagnosis of nutrient imbalance and interactions in wheat and faba bean in Kharga Oasis, Egypt

Imbalanced nutrition has a major impact on crop productivity, particularly in hyper-arid environments, and precise interpretation is essential for designing appropriate nutrient management strategies. Compositional nutrient diagnosis (CND) was used to identify nutritional imbalances of multiple nutrients (N, P, K, Ca, Mg, Fe, Mn, Zn, and Cu) in wheat and faba bean cultivated in Kharga Oasis, Egypt. Significant nutrient interactions were also assessed using principal component analysis. Due to large differences in water and soil characteristics, wheat and faba bean yields from the surveyed area varied greatly, ranging from 2118 to 8211 and 1373 to 4962 kg ha-1, respectively. The CND indexes for the low-yield subpopulation of wheat were negative for P, Ca, and Zn, with average values of -0.82, -2.66, and -1.26, but positive for K, Mg, Fe, and Mn with average values of 4.80, 4.92, 1.70, and 0.57, respectively. In faba bean, N, P, Ca, and Zn were negative, with average values of -1.73, -0.67, -8.19, and -1.41, but K, Mg, Fe, Mn, and Cu were positive with average values of 2.62, 0.50, 1.32, 1.10, and 0.40, respectively. Synergistic interactions P-Zn and Mg-Fe, as well as antagonistic interactions P-Mg, P-Fe, Zn-Fe, Zn-Mg, Ca-Cu, N-Mn, Mn-Cu, and P-Ca, were evident from the principal component analysis of the data. This investigation reveals that the decline in crop yields in the study area is due to nutritional imbalance induced by a deficiency of Ca, Zn, and P and a surplus of Mg, K, Fe, and Mn, in addition to nutrient antagonism.

Accuracy of DRIS and CND methods and nutrient sufficiency ranges for soybean crops in the Northeast of Brazil

This study aimed to evaluate the nutrition of commercial soybean crops in an agricultural frontier region using the diagnosis and recommendation integrated system (DRIS) and compositional nutrient diagnosis (CND) methods, as well as identify sufficiency ranges. The study was performed by collecting leaf samples (third trifoliate leaf without petiole) at flowering from commercial soybean crops in the states of Piauí and Maranhão, Brazil, and evaluating the crop yield by analyzing macro- and micronutrients in the plant tissue of 98 samples. The DRIS and CND methods were applied based on the cataloged data, followed by the generation of norms, analysis of relationships between yield and nutrients (selecting high-yield crops by the cumulative function of the data), generation of sufficiency ranges, and comparison of methods. The relationships obtained by the DRIS and CND indices with the yield and nutrients were significant, indicating that both methods can be employed for the evaluation of leaf nutrients in soybean. The sufficiency ranges from the DRIS and CND methods presented superior nutrient ranges in relation to the values proposed in the literature for macronutrients, except for nitrogen, and greater range amplitudes for micronutrients.

Relationships between the incidence of fire blight in apple orchards and plant nutritional imbalance indices

ABSTRACT Fire blight disease is a major threat to the apple orchards in various regions of the world. The multivariate compositional nutrient diagnosis (CND) was considered to evaluate the effect of plant nutrient imbalance in development of fire blight in ‘golden delicious’ apple orchards in Fars province, Iran. To establish CND norms and the fire blight severity index, 81 commercial orchards were used. The CND reference norms (V*x) for a low fire blight severity subpopulation were calculated as V*N = 2.813 ± 0.186, V*P = 0.297 ± 0.147, V*K = 2.660 ± 0.149, V*Ca = 2.442 ± 0.218, V*Mg = 1.188 ± 0.061, V*S = 0.595 ± 0.399, V*Fe = −0.952 ± 0.212, V*Mn = −3.132 ± 0.195, V*Zn = −4.040 ± 0.366, V*Cu = −5.032 ± 0.177, V*B = −3.361 ± 0.120, V*Rd = 6.521 ± 0.128. According to the calculated leaf nutrient indices based on the CND reference norms and principal component analysis (PCA), leaf Ca, S, B and Zn deficiency and leaf K and P excess significantly correlated with the enhancement of fire blight severity index (FBSI). The reduction of global nutrient imbalance index (CND-r2) to below 20.38 decreases the severity of fire blight in ‘golden delicious’ apple orchards.

Do macro-nutrient balanced compositions in a subspace of the ionome of Opuntia ficus-indica (L.) Miller maximize fruiting?

The current state of knowledge on Opuntia ficus-indica nutrient requirements has important limitations. Macro-nutrient mean concentrations proposed as standards do not consider balances between (or among) elements, and the available compositional nutrient diagnosis norms are not supported by orthogonal references easy to estimate. We hypothesize that O. ficus-indica plants pose macro-nutrient requirements in terms of balanced compositions for producing fruits. The isometric log-ratios allowed us to test that O. ficus-indica variety ‘Rojo Pelón’ plants maximize fruit yield under the basis of true-negative (T-N) or macro-nutrient-balanced compositions in their 1-year-old cladodes. These T-N compositions can be estimated in a straightforward manner using two optimal delimiters, that is, the Mahalanobis distance across the involved isometric log-ratios linked with the highest value of Class Sum of Squares, and a target yield previously defined. When used as a target, these balanced compositions allowed us to identify that true-positive compositions were characterized by P deficiencies and N luxurious consumptions. Novel techniques to perform suitable recommendations based on correct diagnosis interpretation should be developed to address objectively the needed change to enhance the nutrient status of true-positive imbalanced compositions.

Compositional nutrient diagnosis and associated yield predictions in maize: A case study in the northern Guinea savanna of Nigeria

AbstractDeveloping optimal strategies for nutrient management of soils and crops at a larger scale requires an understanding of nutrient limitations and imbalances. The availability of extensive data (n = 1,781) from 2‐yr nutrient omission trials in the most suitable agroecological zone for maize (Zea mays L.) in Nigeria (i.e., the northern Guinea savanna) provides an opportunity to assess nutrient limitations and imbalances using the concept of multi‐ratio compositional nutrient diagnosis (CND). We also compared and contrasted the use of linear regression models and bootstrap forest machine learning to predict maize yield based on nutrient concentration in ear leaves. The results showed that 35% of the experimental plots had low yields due to nutrient imbalances (hereafter referred to as low yield imbalanced [LYI]). These experimental plots were dominated by control plots (without any nutrients applied), plots without N fertilization, and plots without P fertilization. Using the control plot as the ultimate indicator of nutrient imbalance, the significantly limiting nutrients in order of decreasing frequency of deficiency were N, P, S, Ca > Cu, and B. Both linear regression and bootstrap forest machine learning models fairly predicted maize grain yield based on nutrient concentration in ear leaves only in the LYI group and when examining all data with an independent validation dataset. These results suggest that nutrient management strategies, especially through the site‐specific management approach, should consider S, Ca, Cu, and B in addition to the existing nutrients N, P, and K to improve nutrient balance and maize yield in the study area.

Efficiency of critical level and compositional nutrient diagnosis methods to evaluate boron nutritional status in soybean

Efficiency of critical level and compositional nutrient diagnosis methods to evaluate boron nutritional status in soybean

The relation between compositional nutrient diagnosis indices and susceptibility of Valencia orange to citrus decline

The citrus decline is a major threat to citrus production in the southern region of Iran. This study aimed to determine the relationship between the leaf nutrient indices and the citrus decline severity index in Valencia orange (Citrus sinensis L. Osbeck) orchards. The multivariate compositional nutrient diagnosis (CND) was considered to evaluate the relation between nutrient indices and susceptibility of 235 commercial Valencia orange to citrus decline severity index. The CND reference norms for d = 11 leaf nutrients in a low-citrus decline severity subpopulation of ‘Valencia’ orange was determined as V*N = 2.967 ± 0.127, V*P = 0.288 ± 0.156, V*K = 2.795 ± 0.125, V*Ca = 2.600 ± 0.269, V*Mg = 1.331 ± 0.095, V*S = 0.930 ± 0.226, V*Fe = −1.459 ± 0.292, V*Mn = −3.695 ± 0.285, V*Zn = −4.035 ± 0.249, V*Cu = −5.111 ± 0.220, V*B = −3.219 ± 0.177, and V*Rd = 6.609 ± 0.116. These norms were used to determine the nutrient indices in the high-citrus decline severity subpopulation of ‘Valencia’ orange orchards. According to the principal component analysis and nutrient indices, the deficiency of leaf Ca, B, S, and Mg concentration and excess of P, N, Mn, K, and Cu had a significant correlation with the increment of citrus decline severity index. The balanced nutrition management based on these CND norms could reduce the severity of the citrus decline in Valencia orange orchards.

Applying the compositional nutrient diagnosis (CND) to pomegranate (Punica granatum cv. ‘Rabab’) under saline and calcareous soil condition

To establish the multivariate compositional nutrient diagnosis (CND) standards, and the nutrient sufficiency range in ‘Rabab’ cultivar pomegranate, the leaf nutrient concentrations and yields of 196 commercial orchards were determined. The orchard’s nutritional status was calculated and evaluated through the CND method and their compatible principal component analysis (PCA). The CND references norms were calculated as V*N = 2.587 ± 0.103, V*P = 0.124 ± 0.206, V*K = 2.232 ± 0.105, V*Ca = 3.086 ± 0.165, V*Mg = 1.367 ± 0.108, V*S = 1.357 ± 0.137, V*Fe = −1.410 ± 0.324, V*Mn = −3.165 ± 0.221, V*Zn = −4.499 ± 0.192, V*Cu = −5.265 ± 0.225, V*B = −2.884 ± 0.100, V*Rd = 6.470 ± 0.075. The corresponding optimum concentration values of nutrients were N = 1.888 ± 0.210, P = 0.164 ± 0.032, K = 1.322 ± 0.163, Ca = 3.511 ± 0.230, Mg = 0.630 ± 0.115, S = 0.649 ± 0.051 in percent and Fe = 333.588 ± 87.009, Mn = 62.647 ± 14.413, Zn = 15.471 ± 3.105, Cu = 8.118 ± 2.288, B = 89.529 ± 5.125 in mg kg−1. According to PCA analysis S, B, Fe and Cu, in the high yielding subpopulation and Ca, B, S and Mg in the low yielding subpopulation had the highest influence on the increment of fruit yield in ‘Rabab’ pomegranate orchards especially under saline and calcareous soil condition.

Determining the compositional nutrient diagnosis (CND) norms and main nutrient interactions in “Valencia” orange orchards on calcareous soils

To establish compositional nutrient diagnosis (CND) standards, in “Valencia” orange orchards (Citrus sinensis L. Osbeck), the leaf nutrient concentrations and yields of 234 commercial orchards were determined. The orchards nutritional status was evaluated through the compatible principal component analysis (PCA). The CND reference norms were calculated as V*N = 2.766 ± 0.167, V*P = 0.093 ± 0.199, V*K = 2.574 ± 0.097, V*Ca = 2.970 ± 0.217, V*Mg = 1.415 ± 0.116, V*S = 1.250 ± 0.200, V*Fe = −1.503 ± 0.212, V*Mn = −3.626 ± 0.327, V*Zn = −4.096 ± 0.431, V*Cu = −5.231 ± 0.166, V*B = −2.979 ± 0.187, V*Rd = 6.368 ± 0.074. The corresponding optimum concentration values of nutrients were N = 2.504 ± 0.348, P = 0.175 ± 0.040, K = 2.059 ± 0.227, Ca = 3.101 ± 0.664, Mg = 0.646 ± 0.071, S = 0.554 ± 0.108 in percent and Fe = 355.929 ± 80.601, Mn = 44.071 ± 14.409, Zn = 28.500 ± 12.126, Cu = 8.500 ± 1.698, B = 80.429 ± 14.516 in mg kg−1. According to PCA analysis the lower production in the “Valencia” orange orchards was mainly due to lower leaf concentration of S, Ca, B and Mg and a higher leaf concentration of K, Zn, Cu and Mn, respectively. Also, increment of leaf N and P in the high yielding subpopulation and leaf Fe in the low yielding subpopulation had significant effects on the increasing of fruit yield, especially under saline and calcareous soil conditions.

Foliar nutrient diagnosis norms for litchi (Litchi chinensis Sonn. cv. Feizixiao) in South China

Foliar nutrient diagnosis is a potent tool for nutrient management in crops. Litchi (Litchi chinensis Sonn.) plantation in China dominates the worldwide litchi cultivation, and Feizixiao is the most widely cultivated species in China. Herein, 538 leaf samples were collected at fruit swelling stage and the terminal shoot maturing stage during 2016–2017, and the fruit yields of all the sampled trees were recorded. The suitability of four nutrient diagnosis methods including critical value approach (CVA), sufficiency range approach (SRA), modified diagnosis and recommendation integrated system (M-DRIS), and compositional nutrient diagnosis (CND) in Feizixiao were compared. Only a few of foliar nutrients could be diagnosed by CVA. Similar evaluations were achieved by both M-DRIS and CND, but the diagnosis accuracy highly varied with the severity of nutrient deficiency or abundance and the diagnosis year. Finally, SRA was accepted to establish the diagnosis norms due to its stable assessments for all nutrients. The optimal foliar nutrient range for Feizixiao is recommended as N 16.7–19.2, P 1.06–1.25, K 5.1–6.7, Ca 7.7–11.0, Mg 2.5–3.7 and S 1.51–1.81 g kg−1, and Zn 19.6–32.6 and B 11.5–19.2 mg kg−1 at the fruit swelling stage , and N 19.7–22.0, P 1.69–1.95, K 10.8–12.7, Ca 3.0–4.1, Mg 2.5–2.9 and S 1.38–1.57 g kg−1, and Zn 15.0–18.9 and B 10.8–16.8 mg kg−1 at the terminal shoot maturing stage.

Leaf reference values for ‘Pérola’ pineapple quality using compositional nutrient diagnosis

The leaf reference values for pineapple available in the literature were obtained using bivariate methods that aim to reach maximum yield; however, plant nutrition also influences the fruit quality. This study aimed to generate reference values for the ‘Pérola’ pineapple grown in the Paraíba State using compositional nutrient diagnosis (CND) in order to maximize fruit yield and quality. The study used data of fruit weight, soluble solids (SS), titratable acidity (TA), SS/TA ratio, and leaf concentrations of N, P, K, S, Ca, Mg, Cu, Fe, Zn, Mn, and B of the pineapple cultivar ‘Pérola’ originated from fertilization trials. The treatments consisted of the combination of two matrices: the modified Pan Puebla III matrix and the Baconian matrix, which assessed the variation in the levels of N, P, K, and S and the variation in the levels of liming and micronutrients, respectively, totaling 30 treatments in a randomized block design with 90 plots and three replications per experiment. The CND method was used to obtain reference values. There were differences in the mean nutrient concentrations between the high and low-quality populations; however, there was no difference between the nutrient concentrations that promoted the highest fruit weight and those that promoted the highest quality index. The sufficiency ranges for ‘Pérola’ pineapple obtained by CND methodology aiming at the quality index and yield were: N:10.9–14.2; P:1.2–1.6; K: 35.6–42.8; S: 1.0–1.5; Ca: 2.3–3.7; Mg: 1.5–2.2 g kg−1; Cu: 1.1–3.1; Fe: 30.4–52.6; Zn: 4.0–8.5; Mn: 129.2–175.9; and B: 18.8–27.4 mg kg−1.

Nutritional diagnosis and spatial variability of leaf nutrients in teak field in the Eastern Amazon

The objective of this work was to perform the nutritional diagnosis on teak using the compositional nutrient diagnosis (CND) and spatial variability. The methods were applied to 155 georeferenced points in a commercial teak plot seven years after planting located in the city of Capitão Poço, state of Pará, Brazil. This work analyzed leaf N, P, K, Ca, Mg, S, B as well as the diameter at breast height (DBH) and total height. Values of the nutrient were also compared with reference values previously established for the teak. The frequency order of elements regarding deficiency for CND was K > S > B > P > N > Mg > Ca, while the reference values showed K > S > N > P > B > Ca > Mg. The CND showed that around 60 sample points were deficient in K and S, while the reference showed 155 points with a deficiency class for both nutrients. Spatial dependence allowed to elaborate variability maps except for the S, which showed nugget effect. The maps visually related the areas with more P (over 1.6 g kg−1), B (over 19.62 mg Kg−1) and particularly, leaf N (over 19.7 g kg−1) to the highest DBH and total height. Nutritional diagnoses overlapped in pointing out K and S as the elements with the highest frequency of deficiency and the variability maps were accurate in showing the need to adjust nutritional levels for the teak development, with emphasis on the N, P and B.

Estimation of Diagnosis and Recommendation Integrated System (DRIS), Compositional Nutrient Diagnosis (CND) and Range of Normality (RN) Norms for Mineral Diagnosis of Almonds Trees in Spain

To ensure good fertilization, it is necessary to know the optimum nutrient levels for each crop. The most common method for obtaining this information for almond trees is to perform a foliar analysis coupled with the use of interpretive tools such as the traditional range of normality. However, currently, there are other, more sophisticated methods such as the DRIS (Diagnosis and Recommendation Integrated System) and the CND (Compositional Nutrient Diagnosis) which take into account the relationship between nutrients. However, little information is available with respect to these methods in the case of almond trees. In the present work, 288 samples of three contrasting varieties of almond were analyzed—Ferraduel, Ferragnes, and Garrigues (Prunus dulcis, Mill.)—corresponding to bi-weekly sampling between the months of May and September. Leaf analysis data, run with different mathematical and statistical models, lead to knowledge of the optimum period for harvesting samples and the determination of the ranges of normality and norms of DRIS and CND for the Ferraduel, Ferragnes, and Garrigues varieties. Data gained from the leaf nutrient content reported that the best season to harvest and interpret leaf samples was July. In addition, Ferraduel and Ferragnes had higher N, P, and K (2.22, 0.14, and 1.04 mg Kg−1 dw, respectively) than Garrigues (2.00, 0.09. 0.67 mg Kg−1 dw). The norms obtained with the leaf mineral data showed similar values between the Ferraduel and Ferragnes varieties but different values for Garrigues variety. Therefore, Garriges had the highest N/P, N/K, P/K, and P × Mg norms in the DRIS method and the highest VN and VCa norms in the CND method.

Nutritional Status Assessment of Pistachio Orchards in Qazvin Plain, Iran

ABSTRACT Plant analysis is used to optimize the fertilizer applications and diagnosis of the plant nutrition disorders. In the present study, the standard norms for pistachio orchards have been calculated and compared using two methods of Compositional Nutrient Diagnosis (CND) and Deviation from Optimum Percentage (DOP) in Qazvin Plain (Iran). The composite leaf samples were taken from 200 pistachio orchards during three years (2017–2019) and concentrations of Manganese (Mn), Zinc (Zn), Iron (Fe), Magnesium (Mg), Calcium (Ca), Potassium (K), Phosphorus (P), Nitrogen (N), Boron (B), and Copper (Cu) were measured, along with recording the orchards’ yield. The results of CND method showed that the most frequency percentage of the nutrients deficiency was respectively belonged to Mn, Mg, and P in the orchards. Same results were obtained in DOP method. The priority of the nutrient’s deficiency in DOP method was as follows: Mn > Mg > P > K> Ca. In general, it is concluded that Mn, Mg, and P are the most limiting nutrients, are which due to being calcareous, high K content and low organic matter content of the soil, these deficiencies are justified. Therefore, it is recommended to use organic matters, P, Mg, and Mn to improve the yield of pistachio orchards.

Compositional Nutrient Diagnosis (CND) Standards for Opuntia ficus-indica (L.) Miller 'Rojo Pelón' Fruiting

In this study, the aim was to develop the compositional nutrient diagnosis (CND) norms for Opuntia ficus indica variety 'Rojo Pelón’ fruiting. Statistical analyses involved a dataset of fruit yield and macro-nutrient concentrations of 228 1-year old cladodes from healthy plants. A cutoff yield (1,166.67 g cladode-1) between the low- and high-yield subpopulations was determined after examining six cumulative variance ratio functions related to yield per 1-year old cladode. Means and standard deviations of row-centered log-ratios of five nutrients (N, P, K, Ca, and Mg) and a filling value Rd, which includes all nutrients not chemically analyzed. Estimated preliminary CND norms (mean ± standard deviation of the row-centered log-ratios) are: = ?1.114 ± 0.219, = ?2.194 ±0.076, = 0.163 ± 0.259, = ?0.708 ± 0.157, = 0.401 ± 0.100, and = 3.452 ± 0.095. These CND standards are associated with the following 1-year old fruiting cladode mean concentrations: N=0.958%, P=0.318%, K=3.507%, Ca=4.228%, and Mg=1.448%. Then, the order of macro-nutrient requirements is as follows: Ca>K>Mg>N>P.

Soybean Seed Analysis as a Nutritional Diagnostic Tool

ABSTRACT Our study examined whether the nutrient content analysis of soybean seed could be used to assess the plant nutritional status, generating results as or more accurate than those obtained by leaf analysis. We hypothesized that soybean nutritional assessment could be carried out using seeds as a reference. Nutritional diagnosis in soybean leaves and seeds was assessed using the Mathematical Chance (MCh), Diagnosis and Recommendation Integrated System (DRIS), and Compositional Nutrient Diagnosis (CND) methods. Results showed that optimal nutrient levels in soybean leaves and seeds estimated by DRIS and CND were equal or close to the average content in the reference population, while slightly different values were obtained by MCh method. Nutrient average contents were larger for soybean seeds than for leaves for nitrogen, phosphorus, sulfur, and zinc; and lower for potassium, calcium, magnesium, boron, copper, iron, and manganese. The ranges of optimum levels obtained for seed nutrient content showed normality in results for the three studied methods (MCh, DRIS, and CND). This indicates that using seeds as a diagnostic tissue for assessing soybean nutritional status is promising. Optimal nutrients levels in soybean seeds estimated mainly by the CND and DRIS methods could help to monitor soybean nutritional status.

Compositional Nutrient Diagnosis (CND) Applied to Grapevines Grown in Subtropical Climate Region

Soil analysis is used to estimate nutrient availability, but nutrient concentrations are not always related to yield in most fruit plants, including grapevines. Thus, additional multivariate mathematical models, such as the compositional nutrient diagnosis (CND), which takes into account leaves nutrient concentration, and yield, can contribute to estimating critical levels or sufficiency bands of elements, as well as to detect deficiency and/or excess of nutrients. The aim of the present study was to establish CND standards, and the critical level and sufficiency band of nutrients, in the grapevine Vitis vinifera L., grown in a subtropical climate region. Leaves were collected in 81 vineyards in the Campanha Gaúcha do Rio Grande do Sul region, Southern Brazil, and analyzed for macro- and micro-nutrient concentration. The yield of each vineyard was assessed. Grapevine nutritional status was calculated through the CND method. CND-r2 indices were effective in establishing the nutritional status of grapevines for macro- and micro-nutrients as sub-optimal, excessive, or balanced. The CND methodology established the critical level and sufficiency bands of nutrients more accurately than the current recommendations for grapevines. Multi-nutrient associations were more effective than the single nutrient determination in defining the threshold of a given nutrient that can reduce grapevine yield.

Evaluation of Nutritional Status of Lime Orchards in Hormozgan Province of Iran using Compositional Nutrient Diagnosis Method

Evaluation of Nutritional Status of Lime Orchards in Hormozgan Province of Iran using Compositional Nutrient Diagnosis Method

Nutrient Diagnosis Norms for Date Palm (Phoenix dactylifera L.) in Tunisian Oases

Several studies have pointed out the promising use of nutritional diagnosis methods for the determination of optimum nutrient contents in plant tissues. The present investigation was carried out in different oases in Southern Tunisia to determine reference values for the interpretation of leaf analyses of date palm (Phoenix dactylifera) Deglet Nour cultivar with the Critical Value Approach (CVA) and the Compositional Nutrient Diagnosis (CND). A database (n = 100) of yield and mineral concentrations taken from date palm leaflets in October, at the maturity stage of dates, was used. The yield cut-off between low-yield and high-yield subpopulations, selected from cumulative variance ratio functions across survey data, was 76 kg palm−1 and the global nutrient imbalance index (CNDr2) was 10.06. Critical CND nutrient indices were found to be symmetrical around zero as follows: (1.59; +1.59) for IN, (−0.44, +0.44) for IP, (−0.63, +0.63) for IK, (−0.94, +0.94) for ICa, (−1.05, +1.05) for IMg, (−0.80, +0.80) for IFe, (−0.74, +0.74) for ICu, (−0.80, +0.80) for IB, (−0.93, +0.93) for IZn, (−1.04, +1.04) for IMn, and (−1.03, +1.03) for the residual value. Compared to CND, the CVA approach shows weak detection of the nutrients that cause nutritional imbalance. CND indices revealed, except for N, the presence of nutrient imbalances and the necessity to correct the mineral nutrition of date palm in the Kebeli oases.