Compositional Nutrient Diagnosis Norms Research Articles

Nutritional Diagnosis of Potato Crops Using the Multivariate Method

The compositional nutrient diagnosis (CND) method considers the multiple relationships among nutrients and has been proposed to evaluate the nutritional status of plants in place of the univariate and bivariate methods. As it is mathematically based and considers the interactions among all nutrients at the same time, it avoids the errors and trends observed in the calculations of other methods estimating nutritional status, enabling a greater relationship with productivity. The objective of this study was to obtain the CND norms for high-yielding populations of potato crops. For this, 587 samples were used from 21 experimental areas in the state of São Paulo, Brazil to correlate the leaf nutrient contents and the yields of potato crops. Crops with yields higher than 48,993.24 kg ha−1 were considered to have high yields, and the Mahalanobis distance separated the balanced samples from the nutritionally unbalanced ones. Thus, the CND-ilr method generated the norms and classified the 587 samples as nutritionally balanced with a high yield (5% of the total), nutritionally unbalanced with a low yield (92%), nutritionally unbalanced with a high yield (0.3%), or nutritionally balanced with a low yield (2.7%), with accuracy, sensitivity, specificity, NPV, and PPV scores of 96.9, 97.1, 93.6, 64.4, and 99.6%, respectively.

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.

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.

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.

Compositional Nutrient Diagnosis (CND) Norms and Indices for Potato (Solanum tuberosum L.)

A survey was conducted in potato fields for collection of leaf samples to establish nutrient concentration yield data bank. The data bank was used for developing multivariate compositional nutrient diagnosis (CND) norms for assessing the nutritional status of selected centres of potato growing fields. The mean N, P and K concentrations were 2.09, 0.25 and 4.16 %, respectively. The mean Ca (1.11%) concentration was twice higher compared to Mg (0.63 %) concentration. The mean values of Zn, Cu, Fe, Mn and B were 43.69, 31.24, 986.71, 192.76 and 59.98 ppm, respectively. The CND norms for V N, V P and V K were 3.04, 0.94 and 3.73, respectively. The norm for Ca (V Ca =2.45) and Mg (V Mg =1.78) were much narrower compared to the absolute nutrient concentration. The norm for V Zn , V Cu , V Fe , V Mn and V B were -3.24, -3.60, -0.23, -1.98 and -2.89 respectively. The multivariate CND norms developed for ten nutrients proved to be an important tool for diagnosis of nutrient imbalance in potato. The nutrient indices developed indicated that Zn was the most common yield-limiting nutrient. The CND norms and the indices developed can be used for identifying the hidden hunger of various nutrients in potato for evolving nutrient management strategies.

Compositional Nutrient Diagnosis (CND) Norms and Indices for Potato (Solanum tuberosum L.)

A survey was conducted in potato fields for collection of leaf samples to establish nutrient concentration yield data bank. The data bank was used for developing multivariate compositional nutrient diagnosis (CND) norms for assessing the nutritional status of selected centres of potato growing fields. The mean N, P and K concentrations were 2.09, 0.25 and 4.16 %, respectively. The mean Ca (1.11%) concentration was twice higher compared to Mg (0.63 %) concentration. The mean values of Zn, Cu, Fe, Mn and B were 43.69, 31.24, 986.71, 192.76 and 59.98 ppm, respectively. The CND norms for V N, V P and V K were 3.04, 0.94 and 3.73, respectively. The norm for Ca (V Ca =2.45) and Mg (V Mg =1.78) were much narrower compared to the absolute nutrient concentration. The norm for V Zn , V Cu , V Fe , V Mn and V B were -3.24, -3.60, -0.23, -1.98 and -2.89 respectively. The multivariate CND norms developed for ten nutrients proved to be an important tool for diagnosis of nutrient imbalance in potato. The nutrient indices developed indicated that Zn was the most common yield-limiting nutrient. The CND norms and the indices developed can be used for identifying the hidden hunger of various nutrients in potato for evolving nutrient management strategies.

Nutrient Sufficiency Ranges in Mango Using Boundary-Line Approach and Compositional Nutrient Diagnosis Norms in El-Salhiya, Egypt

ABSTRACTNutrient sufficiency ranges are useful for diagnosing and correcting plant nutritional status in order to optimize yield and protect the environment. This study was conducted to determine nutrient sufficiency ranges for nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), iron (Fe), manganese (Mn), zinc (Zn), and copper (Cu) in mango trees grown in El-Salhiya, Egypt, through boundary-line approach (BLA) and compositional nutrient diagnosis (CND) technique. For this purpose, foliar samples from 310 mango trees were collected during two successive years from the study area and fruit yields were recorded. The nutrient sufficiency ranges generated by BLA were 0.744–1.430% for N, 0.074–0.142% for P, 0.543–1.045% for K, 1.366–2.653% for Ca, 0.155–0.305% for Mg, 389–1148 ppm for Fe, 23.1–60.5 ppm for Mn, 28.4–56.3 ppm for Zn, and 2.37–12.10 ppm for Cu. The CND-derived nutrient sufficiency ranges were 0.917–1.215% for N, 0.066–0.106% for P, 0.585–0.943% for K, 1.003–2.077% for Ca, 0.112–0.378% for Mg, 277.5–849.2 ppm for Fe, 27.9–82.4 ppm for Mn, 29.2–44.6 ppm for Zn, and 2.42–11.37 ppm for Cu. The optimum nutrient concentrations generated from BLA were in general comparable to those obtained using CND technique. Only Ca and Fe optimum concentrations showed poor match. Seven significant nutrient interactions were strongly evidenced through principal component analysis of the computed CND indexes. The positive interaction was P-K, while the negative interactions were P-Mg, K-Mg, Ca-Zn, P-Fe, K-Fe, and Zn-Cu.

Multivariate interpretation of the foliar chemical composition of essential nutrients in mango under Peninsular India

The nutrient concentration vs yield performance data bank was established for Alphonso mango grownin Peninsular India to develop multivariate diagnostic norms with high diagnostic sensitivity. Well performingorchards in Ramanagara, Srinivaspur, Chittoor, Krishnagiri, Vengurla and Ratnagiri regions were intensivelysurveyed to develop the data bank. The diagnostic norms for N, P, K, Ca, Mg, S, Fe, Mn, Zn, Cu, b and Mo weredeveloped by using compositional nutrient diagnosis (CND) technique. The interactions among different nutrients were elucidated by principal component analysis (PCA). It was evident that wide variation in plant nutrientconcentration exists in different geographic locations. The mean N concentration showed wide variations from1.03% to 2.87%, P from 0.09 to 0.33% and that of K from 0.78 to 1.35% depending upon the geographic location. Among the micronutrients, Zn concentration showed variation from 14.01 to 24.97 mg kg−1 and b from 3.50 to 16.63 mg kg−1. The CND norms showed higher diagnostic precision compared to the bivariate techniques. Theapplication of PCA indicated that as many as eight nutrient elements were found integrated with first principal component in many locations. Involvement of several nutrients in a single principal component indicated thatit was not possible to diagnose nutrient imbalance of any particular nutrient in isolation in mango and multinutrient involvement on governing yield potential. The extent to which a particular nutrient interacting with other nutrients was a function of nutrient in question and geographic location. The nutrient interaction observed fordifferent locations in general mimicked nutrient behaviour reported earlier. There is a need for integration of the all nutrients for diagnosis of nutrient imbalance in high performing fruit crop like mango.

Role of Nutrient Imbalance on Yellow Leaf Disease in Smallholder Arecanut Systems on a Laterite Soil in India

ABSTRACTOn-farm trials in India investigated the role of nutrient imbalance on yellow leaf disease (YLD) in arecanut on a laterite soil using compositional nutrient diagnosis (CND) approach. Soil fertility status was imbalanced with high organic carbon status and low phosphorus (P) and potassium (K). The CND norms indicated that the order of nutrient demand was changed with nutrient application. Interventions increased yield by 50% during 2007–2010. The correlations indicated positive effect of nitrogen (N) and K and negative effect of manganese (Mn) on yield. The CND indices for NPK were important discriminators between yellowed and apparently healthy populations both in 2007 and 2010. Linear regressions between leaf nutrient concentrations and CND indices were significant for P, K, iron (Fe), Mn, and copper (Cu) (R2 = 0.44–0.53). Results suggest that the predisposing factor for YLD might be nutrient imbalance in the soil leading to deficit of major nutrients in plant.

Nutritional Diagnosis for Apple by DRIS, CND and DOP

This study derived and compared norms for apple, using the Diagnosis and Recommendation Integrated System (DRIS), Compositional Nutrient Diagnosis (CND) and deviation form optimum percentage (DOP) diagnose methods in the Weibei Loess Plateau, Shaanxi Province, China. A total of 68 leaf samples were collected from apple trees grown in Huangshan soils. The nutritional status was diagnosed by the DRIS, CND and DOP methods. The CND norms expressed as row-centered log ratios (mean±standard deviation) for d = 5 nutrients for the high-yield subpopulation (producing more than 46.67 t/ha) were: V_N*= 0.998±0.066, V_p* = -1.499±0.124, V_K* = -0.189±0.283, V_Ca* = 0.217±0.213, V_Mg* = -1.035±0.267, V_R5* = 1.508±0.144. The optimum ranges for leaf nutrient concentrations were: N = 27.23±1.79 g/kg, P = 2.26±0.32 g/kg, K = 8.63±2.50 g/kg, Ca = 12.73±2.66 g/kg, Mg = 3.71±1.12 g/kg, R₅ = 45.44±3.95 g/kg. The regression relating CND to DRIS and DOP indices were significant linear. There was a multinomial regression equation between CND r² and DRIS NBI, also between CND r² and ∑DOP. This study showed that the differences in CND, DRIS and DOP approaches did not lead to large differences in identified deficiencies. So, CND may in practice still be the preferred approach since multivariate methods could be further explored to assess nutrient status in plants, but people can choose any approach they want use since they had the similar evaluation result.

Nutrient imbalance and yield limiting factors of low input East African highland banana (Musa spp. AAA-EA) cropping systems

Low yields of East African highland bananas (Musa spp. AAA-EA) are often attributed to poor and declining soil fertility, which outweighs other biophysical factors and management practices. We investigated the influence of planting density on nutrient mass fractions and nutrient imbalance indices in bananas under small-scale, low-input systems using the compositional nutrient diagnosis (CND) approach. Boundary line functions were developed to identify yield limiting factors and quantify their contribution to the yield gap. Soil, plant, yield and water data were collected in plant density experiments conducted in three contrasting agro-ecological sites of Rwanda (i.e. Kibungo low rainfall with medium soil fertility, Rubona high rainfall but low soil fertility and Ruhengeri high rainfall with high soil fertility). Effects of site×cultivar and site×density on bunch yield were significant (p<0.05). Annual yields (tha−1yr−1) ranged from 6.1 to 9.2 at Kibungo, 9.5 to 21.5 at Rubona and 7.0 to 25.0 at Ruhengeri. Similar trends were registered for the above ground dry matter yield. CND indices showed that K, Mg and P were the most deficient elements in areas with low inherent soil fertility (Kibungo and Rubona). The yield gap analysis also confirmed that K was the most limiting factor, contributing to a predicted yield gap of 55.3% at Kibungo while P and Mg collectively contributed to a 35% yield gap at Rubona. An increase in plant density resulted in an increase in average yield gap from 45.6 to 70.2% at Kibungo, whilst the average yield gap decreased significantly with increases in plant density from 47.5 to 30.2% at Rubona and 76.6 to 53.7% at Ruhengeri. The study confirmed that soil fertility is a more limiting factor than water, but both CND norms and boundary line analysis showed that predicted yield gaps seem to be higher for plant density than soil fertility. Therefore, plant density management is an entry point to optimize yield of East African highland bananas.

NORMS FOR MULTIVARIATE DIAGNOSIS OF NUTRIENT IMBALANCE IN ARABICA AND ROBUSTA COFFEE IN THE EAST AFRICAN HIGHLANDS

SUMMARYPoor soil fertility is a constraint to coffee production. Targeting fertiliser recommendations to nutrient deficiencies can contribute to improved crop response to fertiliser. This study aimed to derive and compare the Compositional Nutrient Diagnosis (CND) and Diagnosis and Recommendation Integrated System (DRIS) norms for Arabica and Robusta, and to investigate nutrient interactions using data derived from 164 plots. The high-yield sub-populations of Arabica had significantly (p &lt; 0.01) higher P (0.23 vs. 0.14) and K (2.87 vs. 2.04), and lower N (2.96 vs. 3.61), Ca (0.99 vs. 1.50) and Mg (0.40 vs. 0.23) than those of Robusta. With respect to the CND norms, Arabica had significantly (p &lt; 0.001) higher P and K, and lower N, Ca and Mg means of row-centered log ratios than Robusta. The relationship between the CND and DRIS indices had coefficient of determination (R2) = 0.75–0.99 for both coffee types. The relationship between nutrient imbalance indices for CND and DRIS had R2 of 0.95 (Arabica) and 0.76 (Robusta). Both coffee types had negative N–Ca, P–Mg and K–Mg interactions. Arabica had positive N–Mg and K–Ca interactions and Robusta had positive N–K, P–K and Ca–Mg interactions and negative N–P, N–Mg, P–Ca and K–Ca interactions. The study concludes, there is a need for cultivar-specific norms, but such norms developed under one set of conditions may not be applicable under different conditions. The study also concludes that both CND and DRIS can be used to determine nutrient imbalances, and fertiliser requirements could be cultivar-specific.

CND AND PCA APPROACHES FOR MULTIVARIATE DIAGNOSIS OF NUTRIENT IMBALANCE IN PAPAYA (CARICA PAPAYA L.)

A survey was conducted in commercial papaya growing orchards for collection of petiole samples to establish nutrient concentrations vs. yield data bank. The data bank was used for developing multivariate compositional nutrient diagnosis (CND) norms for assessing the nutritional status of various orchards. The mean N, P and K concentrations were 1.14, 0.198 and 2.32% respectively. The mean Ca (2.95%) concentration was thrice higher compared to Mg (1.03%) concentration. The mean values of Fe, Mn, Zn and Cu were 139, 76, 56 and 8 ppm respectively. The CND norms for V N , V P and V K were 1.956, 0.16 and 2.59 respectively. The norm for Ca (V Ca 2.86) and Mg (V Mg 1.83) were much narrower compared to the absolute nutrient concentration. The norms for V Fe, V Mn , V Zn and V Cu were -3.273, -3.55, -4.21, and -5.23 respectively. The multivariate CND norms developed for ten nutrients proved to be an important tool for diagnosis of nutrient imbalance in papaya. However, large variations in absolute nutrient concentrations necessitated the application of PCA (principal component analysis), which explained the interaction among different nutrients. The PCA performed on log-transformed data extracted four significant PCs namely (P - K - Ca + Mg + Fe + Mn + Zn ), (N + P + Fe - Zn - R + ), (Mg + S - Cu + ) and (N + Cu + ), which explained nearly 66.33% variance. The interaction between P and K on one hand and Ca, Mg, Fe Mn and Zn on the other hand was evident in PC1. N and P together exhibited greater antagonistic effect with Fe and Zn as shown in PC2. Mg and S showed the tendency to buildup in opposite direction as indicated in PC3. Nitrogen relationship with Cu was isolated in PC4. The relationship extracted by PCA was helpful in understanding the mutual association among different nutrients. The nutrient indices developed indicated that Zn was the most common yield-limiting nutrient. The CND norms and the indices developed can be used for identifying the hidden hunger of various nutrients in papaya for evolving nutrient management strategies.

COMPARACIÓN ENTRE NORMAS DNC Y ESTÁNDARES NUTRIMENTALES DE LA TÉCNICA DE CURVA LÍMITE: CASO Opuntia ficus-indica L.

It is a need to know optimum concentrations and/or optimum ranges of nutrients useful for correct diagnosis and improvements of nutrient status of cultivated plants. Recognizing the need to develop correct nutritional standards, it is convenient to improve or to ensure the reliability of those already determined. Having in mind that aim, boundary-line approach standards were developed taking into account data acquired from a field experiment to study the effects of three fertilization treatments on yield of Opuntia ficus-indica L. The developed boundary-line approach standards were compared with already developed compositional nutrient diagnosis norms for N, P, K, Ca, and Mg concentrations in one-year old cladodes, and cladodes fresh matter as yield in order to define correct nutrient standards. The developed boundary-line approach optimum nutrient concentrations (associated to estimated maximum yield) for Opuntia ficus-indica L. are: N = 1.42 %, P = 0.38 %, K = 4.55 %, Ca = 2.83 % and Mg = 1.41 %. Results suggest that boundary-line approach estimated standards could be trustful and that lower and upper concentrations of the boundary-line approach sufficiency nutrient ranges could be also reliable as well as those for compositional nutrient diagnosis norms.

Compositional nutrient diagnosis of corn using the Mahalanobis distance as nutrient imbalance index

Compositional nutrient diagnosis (CND) provides a plant nutrient imbalance index (CND - r2) with assumed χ2 distribution. The Mahalanobis distance D2, which detects outliers in compositional data sets, has a χ2 distribution. The objective of this paper was to compare D2 and CND – r2 nutrient imbalance indexes in corn (Zea mays L.). We measured grain yield as well as N, P, K, Ca, Mg, Cu, Fe, Mn, and Zn concentrations in the ear leaf at silk stage for 210 calibration sites in the St. Lawrence Lowlands [2300–2700 corn thermal units (CTU)] as well as 30 phosphorus (2300–2700 CTU; 10 sites) and 10 nitrogen (1900–2100 CTU; one site) replicated fertilizer treatments for validation. We derived CND norms as mean, standard deviation, and the inverse covariance matrix of centred log ratios (clr) for high yielding specimens (≥9.0 Mg grain ha–1 at 150 g H2O kg–1 moisture content) in the 2300–2700 CTU zone. Using χ2 = 17 (P &lt; 0.05) with nine degrees of freedom (i.e., nine nutrients) as a rejection criterion for outliers and a yield threshold of 8.6 Mg ha–1 after Cate-Nelson partitioning between low- and high-yielders in the P validation data set, D2 misclassified two specimens compared with nine for CND –r2. The D2 classification was not significantly different from a χ2 classification (P &gt; 0.05), but the CND – r2 classification differed significantly from χ2 or D2 (P &lt; 0.001). A threshold value for nutrient imbalance could thus be derived probabilistically for conducting D2 diagnosis, while the CND – r2 nutrient imbalance threshold must be calibrated using fertilizer trials. In the proposed CND –D2 procedure, D2 is first computed to classify the specimen as possible outlier. Thereafter, nutrient indices are ranked in their order of limitation. The D2 norms appeared less effective in the 1900–2100 CTU zone. Key words: Nutrient balance, simplex closure, variance-covariance matrix, χ2 distribution, grain corn, nitrogen and phosphorus fertilization

Compositional Nutrient Diagnosis Norms (CND) for Guava (Psidium guajava L.)

Multivariate nutrient diagnostic norms were developed for guava using compositional nutrient diagnosis (CND) through leaf nutrient concentration vs. yield data bank. CND norms for N (VN), P (VP) and K (VK) were 2.48, 0.23 and 2.13, respectively. Norms for N and K were much higher compared to P, indicating higher requirement of these two nutrients. CND norms are multivariate norms that consider all elements, including unmeasured factors and, therefore, has higher diagnostic sensitivity. Among micronutrients, Fe requirement was much higher than all other nutrients. Interaction among different nutrients was explained by principal component analysis conducted on log-transformed data which produced four significant PCs, explaining about 73.66% of the variance. The four Eigen values added up to 8.1 denoting the four significant PCs. The first PC was positively correlated with P, Zn and R (residue, which is a reflection of dry matter accumulation in the plant) and negatively correlated with Ca, Mg, S and Fe, indicating that P and Zn behaved in one direction and the other elements in opposite direction. In the second PC, antagonistic effect of N, Fe with P and Cu was evident. In PC3, P and Mg were negatively correlated with Mn and Cu. In PC4, N and S showed their behaviour in the same direction. Diagnostic norms developed were used for identification of yield-limiting nutrients in low-yielding orchards. Thus, diagnostic norms and nutrient interactions help evolve nutrient management strategies for guava to realize higher yields and better quality.

Preliminary compositional nutrient diagnosis norms in Aloe vera L. grown on calcareous soil in an arid environment

This study calculated the compositional nutrient diagnosis norms of Aloe vera L., and also identified significant nutrient interactions of this crop growing in an irrigated calcareous desert soil. The soil showed high heterogeneity within its chemical properties. For statistical analysis, 64 foliar composite samples from healthy plants were used. Preliminary compositional nutrient diagnosis norms were developed using a cumulative variance ratio function and the chi-square distribution function. Means and standard deviations are given of row-centered log ratios V X of five nutrients (N, P, K, Ca, and Mg) and a filling value R, which included all nutrients not chemically analysed. Preliminary compositional nutrient diagnosis norms are: V N * = − 1.033 ± 0.105 , V P * = − 2.617 ± 0.142 , V K * = − 0.041 ± 0.201 , V Ca * = 0.692 ± 0.168 , V Mg * = − 0.7 ± 0.128 , and V R 5 * = 3.699 ± 0.104 . These compositional nutrient diagnosis norms for fresh matter, providing more than 136.67 t ha −1, are associated with the following foliar concentrations: 8.13 g N kg −1, 1.68 g P kg −1, 22.39 g K kg −1, 45.42 g Ca kg −1, and 11.33 g Mg kg −1. Through the principal component analysis of the CND indexes, the positive interactions P–K and Ca–Mg, and the negative interactions P–Ca, P–Mg, K–Ca, K–Mg, and N– R were identified. By using Pearson correlations, the same interactions were identified plus the following: negative P– R and K– R, and positive Ca– R and Mg– R. Estimated t- and F-values and their corresponding probability levels indicated that N/ R antagonism, Ca/ R and Mg/ R synergisms, and nutrients N, Ca and R were the factors discriminating high- from low-yielding subpopulations.

Preliminary compositional nutrient diagnosis norms for cowpea (Vigna unguiculata (L.) Walp.) grown on desert calcareous soil

This study calculated the compositional nutrient diagnosis (CND) norms of cowpea (Vigna unguiculata (L.) Walp.), as well as identified significant nutrient interactions of this crop growing in an irrigated calcareous desert soil. Three genotypes were distributed in rows in a 2-ha field. The soil showed high heterogeneity in its chemical properties. For statistical analysis, 86 foliar composite samples from healthy plants were used. Preliminary CND norms were developed using a cumulative variance ratio function and the χ2 distribution function. Means and standard deviations of row-centered log ratios V X of five nutrients (N, P, K, Ca, and Mg) and a filling value R, which included all nutrients not chemically analyzed. Preliminary CND norms are: V N * =0.174±0.095, V P * =−2.172±0.234, V K * =−0.007±0.267, V Ca * =−0.022±0.146, V Mg * =−1.710±0.132, and V R 5 * =3.728±0.084. These CND norms are associated with dry bean yields higher than 1.88 t ha−1, and are associated with the following foliar concentrations: 26.2 g N kg−1, 2.5 g P kg−1, 22.9 g K kg−1, 21.6 g Ca kg−1, and 4 g Mg kg−1. Cowpea plants growing in desert calcareous soils took up lower amounts of N, P, and K than those considered as optimum in a previous report. Six interactions were strongly indicated for cowpea through principal component analyses: positive for Ca–Mg, and negative for N–Ca, N–Mg, Ca–P, Mg–P, and K–P. Furthermore, two interactions were identified using simple correlations, negative N–P and positive K–Ca.

Multivariate diagnosis of nutrient imbalance in banana

A data bank was established through field experimentation and survey of cropping enterprises for Robusta and Ney Poovan cultivars of banana. The cultivar differences were assessed by discriminant analysis. The two cultivars differed only for potassium (K) and calcium (Ca). Common multivariate compositional nutrient diagnosis (CND) norms were derived for routine diagnostic purposes using the data bank. Further, the principle component analysis (PCA) was used to extract the correlation structure among the nutrient elements in the high yielding population. The PCA conducted on log-transformed data provided three significant PCs and accounted for about 60% of the variance. The inverse relationship between nitrogen (N), phosphorus (P), and K on one hand and Ca and magnesium (Mg) on the other was highlighted in PC (N+P+Ca−Mg−), which explained about 23.6% of the variance. Elucidean distance (“d”) computed from PCs provided nutrient element imbalance index for the crop. The diagnosis of overall nutrient imbalance in banana was made comparing the leaf nutrient concentrations with the CND norms. The imbalance of nutrients as reflected in “d” value was more with seven split applications of N and K compared to four split applications. The CND indices were instrumental in diagnosis treatment dependent P and zinc (Zn) imbalance in banana.