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.

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Agriculture in the 21st Century must be performed considering sustainability criteria to mitigate the effects of climate change. For this, adequate fertilization is necessary for avoiding the excess application of fertilizers, which could contaminate the environment. For the efficient management of fertilization, it is necessary to know the optimum levels of each nutrient for each specie and type of environment. The most common method is to interpret foliar analyses results with traditional tools such as the Range of Normality (RN) or through more precise and complex techniques, such as the Diagnosis and Recommendation Integrated System (DRIS), or the Compositional Nutrient Diagnosis (CND). However, for almonds, little information is available on the nutritional requirements of the different varieties, and those cultivated in rainfed vs irrigated lands are not differentiated. In the present work, 384 samples from each of four almond varieties (Prunus dulcis, Mill.) Desmayo, Ramillete, Marcona and Tuono, grown in rainfed or irrigated lands (a total of 1,536 samples) were analyzed, corresponding to sampling every two weeks between the months of June and September, both months included, for a period of two consecutive years. The main objective of the work was to establish RN, DRIS and CND standards for the interpretation of the nutritional analysis of these four almond varieties grown under different watering regimes. With the data from mineral analysis, through the application of different mathematical and statistical models, the RN, DRIS, and CND standards were obtained, with the conclusion that the optimal period for sampling this crop was in the month of July. These standards could be useful for developing algorithms that could be utilized to develop decision support systems (DSS) that interpret the foliar analyses more precisely as compared to the simple RN, and which manage, based on this information, the fertilization of the crops.

Nitrogen fertilization is key to improve crop yield. However, due to the harmful environmental effects of fertilizers, farmers and governments are searching agronomic practices that provide nutrients to the crops with minimal environmental impact, as for example the use of nitrification inhibitors. These compounds act on ammonium reducing its oxidation to nitrate, and soil´s nitrogen remains longer in the form of ammonium helping prevent nitrate lixiviation. The objective of the experiment was to evaluate the effect of a new nitrification inhibitor (DMPSA) in almond trees. We studied the effect of three solutions on vegetative growth, nutrition, and physiology on Alvijor almond plants irrigated with one of three possible study solutions i) 3:1 nitrate:ammonium rate solution ii) 1:1 nitrate:ammonium rate solution, or iii) 1:1 nitrate:ammonium rate solution plus a nitrification inhibitor (3,4-dimethylpyrazolesuccinic acid). Plants were grown in a greenhouse in calcareous and alkaline soil from the Spanish Levante area. Macro and micronutrients were determined from drainage samples collected throughout the experiment. At the end of the experiment, gaseous exchange and chlorophyll fluorescence parameters were measured and plants harvested to analyse morphological characteristics (leaf, stem and root fresh and dry weight, aerial part rate, and trunk diameter) and N, P, K, Ca, and Mg content in the leaves. We found higher levels of ammonium and lower nitrates in the roots and higher vegetative growth with the irrigation solution containing the nitrification inhibitor in comparison with treatment solutions 1:1 and 3:1. The drainage showed that NI reduces the level of nitrates in the leachate, limiting its discharge to the subsoil. In conclusion, the nutrient solution with the nitrification inhibitor has a positive impact on Alvijor almond plants and the environment.