Effect of biostimulants combined with fertilization on yield and nutritional value of wheat crops

Abstract

Background: Bread wheat (Triticum aestivum) is one of the most widely cultivated crops globally; it is nutritionally demanding and may be responsible for soil exhaustion, requiring adequate fertilization to maintain high yields and grain quality. Targeted supplementation of macro- and micronutrients can also be used for the agronomic biofortification of the grains. However, excessive chemical fertilizers can harm the environment and human health, and more sustainable options are therefore required. This work proposes alternative strategies to chemical fertilization, including applying organic fertilizers, biostimulants, and low-impact agronomical practices like foliar spraying, to achieve high yields and enrichment in cationic nutrients calcium, magnesium, and potassium.

Experimental plan: The study investigates the impact of different fertilization strategies on wheat yield and nutrient composition using two wheat genotypes characterized by different nitrogen (N) grain content. The plants were grown in pots and underwent differential root fertilization with 50 kg ha^-1 N at the tillering stage, comparing mineral and organic products. At heading, foliar treatments (25 kg ha^-1 N) were applied, comparing a traditional urea supplementation with a combination of biostimulants from organic wastes and calcium, magnesium and potassium nitrates. The plants were analyzed for their health and the expression of genes for nutrient homeostasis during growth, and for yield and grain quality at harvesting.

Results: The two alternative fertilization approaches positively impacted plant health and yield in both cultivars. Root fertilization accounted for most of the total variance, affecting both early and late-stage yield components; the organic fertilizer produced results comparable to those of the mineral one. Furthermore, the foliar application of base cations and biostimulants led to beneficial changes in nutrient homeostasis and grain mineral content, although the increase in calcium, magnesium and potassium was moderate and genotype-specific.

Conclusions: This work identifies organic amendments, foliar spraying and biostimulants as alternative and sustainable strategies that can be as effective as chemical fertilization in improving wheat plant health, yield and grain composition. On the other hand, supplementing with cation nutrients at heading showed minimal biofortification benefits. The study emphasizes the importance of considering genotype-specific needs to optimize nutrient uptake and yield across different wheat cultivars.

Keywords: Biostimulants; Foliar fertilization; Nutritional value; Wheat.

Fig. 1

Experimental plan. Schematic representation of the experimental thesis applied in this work. Root fertilization approaches, applied at tillering, are reported in columns and foliar treatments, performed at heading, in rows. The untreated control (UTC) received no nutrient supplementation

Fig. 2

Analysis of wheat health and development after root fertilization. Chlorophyll measurements were performed six weeks after root fertilization, on three biological replicates (three pots) for each treatment type; five leaves were pooled from different plants for each biological replicate. The number of productive tillers was evaluated at harvesting on 18 biological replicates. A Total chlorophyll content (biological replicates = 3). B Chlorophyll a/b ratio (biological replicates = 3). C Number of productive tillers, measured as spikes per plant at harvesting (biological replicates = 18). Different letters above the histograms indicate statistical significance, evaluated by two-way ANOVA followed by a post hoc Tukey’s multiple comparison test (P < 0.05)

Fig. 3

Expression analysis of nitrogen and phosphorus transporters after root fertilization. Real-time RT-PCR analysis of TaNPF5.20 and TaPHT1;6, indicative of N and P nutritional status, respectively, measured in leaves six weeks after root fertilization (biological replicates = 3). Different letters above the histograms indicate statistical significance, evaluated by two-way ANOVA followed by a post hoc Tukey’s multiple comparison test (P < 0.05)

Fig. 4

PCA analysis of yield data after root and foliar fertilization. Left side: wheat cultivar Rebelde; right side: wheat cultivar Bagou. Upper figures: PCA loadings for the three main yield parameters with late onset, i.e., seeds per spike, thousand kernel weight (TKW) and total yield. Middle graphs: sample distribution with respect to the two main principal components (PC1 and PC2); samples are marked with different colors according to their corresponding root treatment. Lower tables: proportion of variance for each principal component

Fig. 5

Analysis of wheat yield after root and foliar fertilization. Yield per hectare in Rebelde and Bagou, measured at harvesting of ripe heads (biological replicates = 3). Different letters above the histograms indicate statistical significance, evaluated by two-way ANOVA followed by a post hoc Tukey’s multiple comparison test (P < 0.05)

Fig. 6

Elemental composition of wheat grain upon foliar fertilization. Concentrations of the most significant macronutrients in Rebelde (left) and Bagou (right) grain, measured on ripe grains after harvesting by energy-dispersive X-ray fluorescence (EDXRF) spectrometry (n = 3). A Ca, B K, C Mg, D Cl, E S, F P. Different letters above the histograms indicate statistical significance, evaluated by two-way ANOVA followed by a post hoc Tukey’s multiple comparison test (P < 0.05)

Fig. 7

Expression analysis of cation transporters after foliar fertilization. Real-time RT-PCR analysis of TaACA4, TaMGT1 and TaHAK18, considered for Ca, Mg and K respectively, measured one week after foliar fertilization in flag leaves (biological replicates = 3). The analysis was performed in the MIN(N + P) root fertilization background as the one showing the biggest differences between foliar treatments when considering the health and yield parameters. Different letters above the histograms indicate statistical significance, evaluated by two-way ANOVA followed by a post hoc Tukey’s multiple comparison test (P < 0.05)