Introduction

Fertilizers are used in crop production as they provide nutrients such as nitrogen, phosphorus and potassium that allow greater growth, development and production of these (^{Sedlacek et al., 2020}). Considering the use of efficient doses of fertilizers is vital for obtaining high yields. The balanced use of fertilizers and the reduction of production costs are objectives of modern agriculture (^{Yousaf et al., 2016}). The importance of a good diagnosis to develop adequate fertilizer recommendations promotes an increase in quality and productivity without deterioration of the environment. In addition, it is important to make efficient use of fertilizers to avoid unnecessary expenses and increases in production costs and to reduce environmental deterioration (^{Marschner, 2012}).

The application of nutrients through fertilization is a common agronomic practice in corn cultivation, so that a nutritional deficiency can reduce the yield by 10 to up to 30%, before the characteristic symptoms of the deficiency appear (^{Morejon et al., 2017}). Nutrient extraction is related to the nutritional harvest index, which is high for N and P, intermediate for S and very low for Ca and Mg (^{Fontanetto et al., 2006}). The diagnosis of the fertility and nutritional status of plants is based on the assumption that the growth rate of plants is affected by the concentration of nutrients present in the soil and in the dry or fresh matter of the shoot. In general, the nutritional status of the leaf tissue better reflects the balance state of the plant and determines which nutrients are deficient, sufficient or in excess (^{Marschner, 2012}).

Currently, there are several tools to determine the nutritional status of plants. Among them, the analysis of plants is efficient since the tissue is analyzed as a nutrient extractor. In this way, it is complemented by the chemical analysis of the soil and allows predicting nutritional disorders before visual symptoms appear (^{Prado et al., 2012}). Plant tissue analysis has the function of improving harvest yields and quality depending on the type of crop (^{Imakumbili et al., 2020}). Through this analysis, the nutrient needs and exports of the crop can be determined, nutritional deficiencies can be identified, nutritional status can be evaluated, the response to fertilizer application can be evaluated, and nutrient levels in various plant organs can be diagnosed.

The results are interpreted by comparing the concentration values of each element of the sample with the respective standard or a value considered optimal (^{Prado et al., 2012}). The application of fertilizers to crops should be carried out using scientific tools such as soil, water and plant tissue analyses with the aim of avoiding losses due to leaching, volatilization and denitrification of these inputs, which directly affect the environment, in addition to increasing production costs.

Materials and methods

The experiment was developed in the ‘El Ranchito’ experimental field, in lot X-11, belonging to the Chapingo Autonomous University, Texcoco de Mora, State of Mexico. A soil sampling was carried out prior to the establishment of the crop using the zigzag method. Fifteen subsamples were collected randomly, trying that they were representative of the land, then a composite sample was formed, which was sent to the laboratory of chemical analysis of soils for the determination of its fertility, using the methods established in the Official Mexican Standard NOM-021-SEMARNAT-2000 (^{SEMARNAT, 2022}). After obtaining the results of the soil fertility analysis, the optimal fertilization dose was estimated using the restitution method (^{Conde et al., 2018}).

The treatment design used was a 2x5 factorial treatment design. The first factor consisted of two varieties of corn (Estrella and Celeste). The second factor was composed of five fertilization doses (T₀: absolute control, T₁: producer dose, T₂: 0.5 of the optimal dose, T₃: optimal dose, T₄: 1+0.5 of the optimal dose). T₀ was not applied any type of fertilizer to the soil or the plant, T₁ consisted of applying the dose used by the producers of the region to the culture of corn. The optimal dose was estimated, as previously indicated, with the restitution method taking into account the results of the soil analysis and from this, the treatments T₂ and T₄ were generated. The restitution method was used to calculate the optimal dose of all nutrients.

The culture was developed under rainfed conditions and was provided with supplemental irrigations every 15 days. The treatments were arranged in a completely randomized block design with four repetitions each. The foliar sampling was carried out in each experimental unit at three months of development of the corn culture and consisted of collecting from 25 randomly selected plants leaves located opposite and under the cob, photosynthetically active, healthy, sunny, clean and without physical damage. The leaves were washed to remove impurities, dried on an oven with forced air at 70 °C to constant weight.

Subsequently, they were ground using a stainless-steel mill, 0.5 g of dry matter from each sample was weighed, which were transferred to a Kjeldahl flask and 4 ml of diacid mixture (H₂SO₄:HClO₄) in a ratio of 4:1 and 2 ml of H₂O₂ were added, and they were placed on a digestion plate at 230 °C for 6 h. The samples were then removed and left to cool (^{Jones, 2001}). Each digested sample was measured to 50 ml using a volumetric flask and transferred to a previously labeled plastic container. The final samples were stored in dark conditions and room temperature.

In the digestate, the total N concentration was determined by the Kjeldahl method. P was measured through the vanadate-molybdate method, and the readings were made on an ultraviolet light spectrophotometer at 420 nm. K and Na were determined with a flame emission spectrophotometer (flame meter) and Ca, Mg, Fe, Cu and Zn with an atomic absorption spectrophotometer. B was determined by the azomethine-H method and the readings were made on an ultraviolet light spectrophotometer at 620 nm (^{Jones, 2001}).

Foliar diagnosis. For the interpretation of the nutritional status of the plant, the following methods were used: ^{Kenworthy balance index (Kenworthy, 1967}), diagnosis and recommendation integrated system, ^{Lucena (2002}), and optimal percentage deviation (^{Montañés et al., 1991}). To carry out the diagnosis with each method, optimal reference values for corn culture were sought. Kenworthy balance index operations were calculated using the following formulas. If X < S, then:P= (X ⁄S)*100. I= (100-P )*(V ⁄100). B= P+I. If X>S then P= (X ⁄S)*100. I= (P-100)*(V ⁄100). B= P-I Where: X= is the concentration value of a nutrient in the sample; S= is the concentration value of a nutrient in the reference standard; P= is the percentage of the standard; V= is the coefficient of variation; I= is the influence of variation and B= is the equilibrium index.

Decision criteria for Kenworthy BI: scarcity= 17-50; below normal= 50-83; normal= 83-117; above normal= 117-150; excess= 150-183. For the DRIS calculation, the nutritional ratios were established based on the data of the foliar analysis, N/P, N/K, N/Ca, Mg/N, K/P, Ca/P, Mg/P, Ca/P, Mg/K, Mg/Ca, etc. (^{Lucena, 2002}), and the following equations were used: If

2.) if

CV= is the coefficient of variation of the corresponding standard.

The indices were calculated using the following equation:

4). Where: A,B,C,D,E and N symbolize nutrients and z represents the functions involved in the calculation. The function (equation 4) is (+) if element A is numerator and (-) if it is denominator. The sum of the positive and negative indices must be zero so that there is a balance between the nutrients of the sample analyzed. Negative indices mean deficiency and positive indices indicate sufficiency or relative excesses. The most negative is the most deficient and those that follow indicate the order of nutrient requirements.

The percentage optimum deviation index was calculated by applying the following relationship:

1). Where: C= is the foliar concentration (in percentage of dry matter) of the element in the sample analyzed; Cref= is the optimum of the same element (percentage of dry matter) defined under the same conditions in which the problem sample was taken and logically, for the same crop. The sign of the DOP for a given element will be negative in the case of a deficit and positive in the case of an excess. When the sample content coincides with the reference optimum, the DOP will be equal to zero (Montañés et al., 1991).

Results and discussion

The presentation began with the results of fertility, showing the diagnosis of the nutritional status of the soil. Subsequently, the results of the nutritional status of the leaf tissue of the culture were shown, making the nutritional diagnosis by means of the following methods: indices of ^{Kenworthy balance (1961}), optimal percentage deviation (^{Montañés et al., 1991}), and the diagnosis and recommendation integrated system (^{Beaufils, 1973}). The tables showed the nutritional concentrations, the balance index of each nutrient and the order of nutritional requirement, highlighting the deficiencies, sufficiencies and excesses for each treatment.

Conclusions

The diagnosis determined the soil as clayey, with neutral pH, very low in Cu, low in Fe and Mn, medium in N, Zn and CEC, high in organic matter and very high in P, K, Ca, Mg and B. The three foliar interpretation methodologies determined different deficiencies and ONRs, in the same variety and between treatments. However, in the three methodologies it was found that the nutrients N and Zn were the most deficient, while Ca and B were present at high levels. For the celeste variety, the three methodologies coincided in determining N, Mg, Mn, and Zn as deficient. While in the estrella variety, N and Zn were diagnosed as deficient, while the other elements did not coincide.

The diagnostic methods Kenworthy balance and DOP indices agreed that N, Mg, Mn, and Zn were the most deficient in the celeste variety, while in the estrella variety, N, Mn, Zn, and Cu were diagnosed as the most deficient.

Foliar diagnosis using Kenworthy balance and DOP indices had a positive correlation between the high concentration of Ca and B in the soil in both corn varieties, while Mn and Cu were low in soil and foliage. While the elements P, K Ca, Mg and Zn had no correlation since in the soil they were medium and high and in the foliage they were different. For the DRIS diagnosis, medium or sufficient to high levels of Ca, Mg and B were determined both in the soil and in the plant. Finally, the concentration of Cu in the soil and plant was low, while that of B was high.