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Article

Fertilizers and Microorganisms Promote Strawberry Growth, Yield, and Quality in Peru

by
Betsabe Leon Ttacca
1,*,
Ariana Jossety Peña Meneses
1,
Reyno Leonardo Chipana Manrique
1,
Manuel Alfredo Ñique Alvarez
1 and
César Oswaldo Arévalo-Hernández
2,3,*
1
Facultad de Ciencias Agrarias, Universidad Nacional de Cañete, Lima 15047, Peru
2
Facultad de Ingenieria y Ciencias, Universidad Nacional Autonoma de Alto Amazonas, Yurimaguas 22000, Peru
3
Instituto de Cultivos Tropicales, Tarapoto 16501, Peru
*
Authors to whom correspondence should be addressed.
AgriEngineering 2025, 7(11), 381; https://doi.org/10.3390/agriengineering7110381
Submission received: 15 September 2025 / Revised: 27 October 2025 / Accepted: 29 October 2025 / Published: 10 November 2025
(This article belongs to the Section Sustainable Bioresource and Bioprocess Engineering)
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Versions Notes

Abstract

The use of sustainable and efficient practices is important for high crop yields. This study aimed to determine the effects of microorganisms and fertilizers on the growth, yield, and fruit quality of two strawberry cultivars in Cañete, Peru. The experiment was set up in a randomized complete block design with a split-plot arrangement, where the main plots were the fertilizer doses (0, 50, 100, and 150%) and the subplots were arranged in a factorial scheme of 2 × 4, with two strawberry varieties, three microorganisms (Azospirillum brasilense, Rhizophagus spp., and Trichoderma sp.), and the control. Growth variables included the number of leaves, crowns, and flowers; petiole length and diameter; foliar area; number of fruits; and yield. Nutrient concentrations of nitrogen, phosphorus, potassium, calcium, and magnesium were determined. For fruit quality, the variables of pH, Brix grade, and acidity were measured. The results indicated that the Sabrina cultivar had higher growth and yield (+15%). All fertilizer doses promoted yield and firmness, especially the 50% dose. All microorganisms promoted growth, yield (+60%), and fruit quality, demonstrating their importance in improving fruit production in this crop in Peru.

1. Introduction

Peru is a highly diverse country in terms of biodiversity, which enables the production of different crops and affects yield. One of the main crops grown is strawberry (Fragaria x ananassa Duch.), which has shown sustained growth in the last decade (2014–2024). Recent data showed the production of 40,000 t of strawberries in 2024, with approximately 3800 ha dedicated to this crop [1]. Nearly 80% of the planted area was in the coastal region of Lima, specifically in the north, including Barranca, Huaral, Huacho, and Cañete [2]. This crop is a source of different vitamins, anthocyanins, and flavonoids and can reduce obesity, cardiovascular diseases, and cancer [3].
As the main production area of crops in the country is in desertic areas, irrigation is a strategic activity that can substantially increase yields. More than 80% of agricultural areas dedicated to strawberries are implemented with fertigation. The use of fertilizer via irrigation in coastal areas in Peru has many advantages, such as reduction in work labor and efficiency, and reduction in fertilizer use. However, some disadvantages include the high cost of implementation, salinization, and ground water depletion [4].
In general, fertilizer applications in Peru are normally driven by experience or common knowledge in the areas where the crop is planted. These practices often lead to high doses that can cause a decline in the overall soil quality for strawberry production. This is an issue for producers and the environment, as these doses can lead to soil salinization. Especially in the coastal area of Peru, salinization is the main driver of land degradation, with nearly 300,000 ha affected by this problem, with soils exceeding 2 dS/cm of electrical conductivity [5]. This problem is normally addressed by producers via soil leaching with high-quality water applied in the fields.
In the case of strawberries, nutrition is very important, as it is a highly demanding crop species due to its high yields, which in many cases can reach nearly 90 t. In this species, the nutrient demands are as follows: nitrogen (N) > potassium (K) > phosphorus (P) > calcium (Ca) > magnesium (Mg) > iron (Fe) > manganese (Mn) > boron (B) > zinc (Zn) [6]. However, these high demands can only be achieved with high fertilizer doses, which are inversely correlated with efficiency supply.
To mitigate this problem, some alternatives have been shown to improve nutrient acquisition and management, such as precision application, slow-release fertilizers, organic fertilizers, and biofertilizers [7]. The latter has received high attention in the last decade, as results seem promising in terms of promoting plant nutrient efficiency and overall health [8].
Different microorganisms have been used in agriculture, the most famous being N-fixing bacteria associated with Leguminosae [9]. Other symbiotic microorganisms, such as mycorrhiza fungi, have also received attention for their improvements of growth, nutrient acquisition, and disease control [10]. However, some non-symbiotic microorganisms, such as Azospirillum, have several benefits in plants, such as N fixation, phosphate solubilization, and mineral uptake [11]. Additionally, other species, such as Trichoderma, have been extensively studied for pest control but have also been shown to improve root growth [12].
Different microorganisms, such as Bacillus sp., Streptomyces sp., Pseudomonas, and arbuscular mycorrhizae fungi (AMF), have been used in strawberries to control different diseases and increase yields [13,14]. Additionally, microorganisms have been used to improve nutrient acquisition in this species [15,16], which can lead to lower fertilizer doses [15]. However, these effects are highly dependent on the microorganism species, their association with the environment, and where they are applied [13,16].
Considering the potential use of microorganisms and fertilizers in strawberry, this study had the following objectives: (i) determine the effect of microorganisms and fertilizers on the growth and development of two strawberry cultivars; (ii) assess the effects of microorganisms and fertilizers on the yield and quality of two strawberry cultivars; and (iii) determine the optimal dose with the most outstanding microorganisms under desert conditions.

2. Materials and Methods

2.1. Localization

This experiment was performed from March 2024 to December 2024 at San Juan Farm, Herbay Alto, Cañete (13°7′34″ S, 76°19′45″ W). The area has a mean temperature of 21.5 °C, a minimum temperature of 17°C, and a maximum temperature of 27 °C. It has a mean annual precipitation of 11.4 mm. This climate is classified as Bwh (desert hot climate) according to the Koppen classification [17].

2.2. Strawberry Cultivars

For the experiment, two strawberry cultivars were used: Sabrina and San Andreas. These cultivars are characterized by their use in the field. San Andreas, which was developed by the University of California, has high yields and is considered day-neutral [18]. Sabrina is a day-neutral cultivar characterized by its productivity and pest resistance. The plants were obtained from a certified nursery, guaranteeing their disease-free status and high health quality.

2.3. Soil Characteristics

Soil was sampled at a depth of 0.0–0.15 m, and a composite sample was prepared from 10 cores. Plants were sampled. For soil analysis, the procedures specified by [19] were used, and the variables determined were pH, electrical conductivity (EC), organic matter (OM) content, Ca content, Mg content, K content, sodium (Na) content, cation exchange capacity (CEC), P content, and texture (sand, silt, and clay).
The soil analysis identified a loam sandy soil (bulk density of 1.6 g/cm3), with a pH of 7.73, EC of 3.33 dS/m, OM content of 1.21%, available P content of 83.3 mg/kg, CEC of 12.83 cmol+/kg, Ca content of 10.88 cmol+/kg, Mg content of 1.41 cmol+/kg, K content of 0.32 cmol+/kg, Na content of 0.22 cmol+/kg, soil available K content of 62.56 mg/kg, sulfur content of 13.69 mg/kg, and B content of 0.56 mg/kg.

2.4. Experimental Design

The experimental area consisted of 1200 m2, with a total of 2688 plants in each main plot of 400 m2. The experimental design (Figure 1) was a randomized complete block design (RCBD) with a split-plot arrangement: 4 plots and 8 subplots in a factorial arrangement of 2 × 4, and three repetitions. Each repetition consisted of 27 experimental units (plants). The 4 plots consisted of 4 doses of fertilizers applied via fertigation (0, 50, 100, and 150% of the base fertilizer dose). The base fertilizer dose consisted of 220 N—98 P2O5—205 K2O, which was calculated for an estimated production of 60 Mg/ha. The subplots were for the two strawberry cultivars (Sabrina and San Andreas cultivars) with three types of microorganisms (Trichoderma sp., Azospirillum brasilense, and Rhizophagus sp.) and the control without microorganisms. Therefore, the main plots were for the fertilizer doses and the subplots for the interaction of cultivar × microorganism.

2.5. Pre-Plant Practices and Strawberry Agronomic Management

The area was first cleaned of the residues from the previous crop, and heavy irrigation was performed for 48 h with leaching salts. The water used for leaching had a pH of 7.65, EC of 0.42 dS/m, chlorine (Cl) content of 27.3 mg/L, and B content of 0.20 mg/L.
After 10 days, 10 t/ha of poultry manure (2.3% N, 3.3% P2O5, and 2.5% K2O) was added uniformly to the field. With the aid of a tractor, manure was mixed, and soil was plowed. Gypsum was then uniformly applied at a rate of 250 kg/ha to reduce salts and the toxic effects of Na. Plastic beds and irrigation lines were installed, and a nematicide (MOCAP) was applied at a rate of 15 kg/ha to avoid nematode attacks due to the high Meloidogyne sp. population in the field. All treatments received the same amendments and pre-plant practices. This study did not account for treatment without these products.
Holes were made in the plastic beds, and the seedlings were transplanted at the ideal age for cultivation (40 days, 4–6 real leaves). The seedlings were planted at 0.3 m × 0.3 m in staggered rows.
For irrigation, the previously described water was used, with a total of 6000 m3 per hectare in the crop cycle.

2.6. Application of Microorganisms

For Azospirillum brasilense, the product NITROBAC TRIPLE (107 CFU/mL) from the Silvestre Company was used at a rate of 206 CFU per plant. For mycorrhiza fungi, the product MICOTAB (50 spores/g) with a mixture of Rhizophagus sp., Acaulospora sp., Entrophospora sp., and Gigaspora sp. was applied at a rate of 20 g per plant. For Trichoderma, the product TRICHOTAB (1.7 × 1010 conidia/g) was applied at a rate of 0.25 g per plant. Both the mycorrhiza fungi and Trichoderma sp. were obtained from the company TAB SAC. All microorganisms were applied near the roots of the seedings at different rates depending on the manufacturers’ specifications.

2.7. Agronomic Measurements

For growth variables, the number of leaves, crowns, and flowers; petiole length (cm) and diameter (cm); and foliar area (cm2) were measured in the field. These variables were all measured at the flowering stage of the plant. In the case of the foliar area, leaf samples were collected, and with the length and width data, the formulae specified by [20] were used.
For yield variables, the number of fruits and fresh weight (g) were measured every 4 days. A total of 39 harvests (Figure 2) were performed from 22 July to 6 December 2024 (5 months). For yield, it was calculated by the sum of the fresh weight (g) of each treatment during the crop cycle. After considering the size of each treatment, the results were extrapolated and transformed into Mg/ha.

2.8. Plant Sampling and Chemical Analysis

Plant samples of fully expanded leaves were taken at the flowering stage, with 20 leaves for each treatment in each block. For plant analysis, N, P, K, Ca, and Mg were measured with the procedures described by [21] and are summarized as follows: N was determined using the Kjeldahl method. The other nutrients were first digested in HNO3. P was then determined using the molybdate–vanadate at 880 nm using a UV-Vis spectrophotometer. The K, Ca, and Mg contents were determined using Atomic Absorption Spectrophotometry (AAS) Varian Spectra 50B.

2.9. Fruit Quality and Nutrition Assessment

For fruit quality, the variables of pH, Brix grade, and acidity were measured in fruit juice. For pH, a potentiometer was used, with direct measurement of the fruit juice. For the Brix grade, a refractometer was used to express the total soluble solids content. For acidity, titration with 1 M NaOH was performed until it reached pH 7.0, and this was expressed in terms of citric acid. The firmness and circumference were measured directly in fruit. Firmness (N) was calculated with a Wagner FT series fruit tester in gf, and circumference (mm) with a metric tape.

2.10. Statistical Analysis

Descriptive statistics (mean and standard deviation) were performed for all variables. Analysis of variance (ANOVA) was calculated for all variables. Residual diagnostics were carried out graphically with the R base package 4.4.0 [22]. In the case that the variables did not meet the ANOVA assumptions, Box–Cox transformation was used. For the mixed model structure, the ‘lme4’ package [23] was used. The fixed terms were fertilizer doses, cultivars, and microorganisms, and the random terms were the blocks. The main plot error was associated with fertilizer doses and subplot error with the interaction of cultivar × microorganism.
Additionally, when significant differences for simple effects were found, the Scott–Knott post hoc test [24] was used at 0.05. For regression analysis, to obtain the optimum dose, means from each cultivar and dose were used and adjusted to a quadratic fit. The first derivative of the equation was calculated, and the result was multiplied by 90% to obtain the optimum dose. All statistical analyses were performed and graphics were generated in R [22].

3. Results

3.1. Effects on Agronomic Variables

The mean values of agronomic variables (number of leaves, crowns, and flowers; petiole length and diameter; and foliar area) are presented in Table 1, and ANOVA tables are presented in Table S1. For the cultivars, significant differences (p ≤ 0.05) were observed for most variables, with the exception of petiole diameter and number of fruits. Sabrina had higher mean values for the number of leaves (49.32), foliar area (108.9 cm2), number of crowns (2.18), number of flowers (1.83), petiole length (17.50 cm), petiole diameter (2.49 cm), and crown diameter (33.79 cm), while for stolons, San Andreas presented a higher mean value (0.16). Additionally, Sabrina presented a higher mean yield, with 66.6 Mg/ha compared to San Andreas with 56.6 Mg/ha.
For fertilizer doses, no significant differences (p > 0.05) were observed, except for foliar area, number of crowns and flowers, and yield. In the case of the first two variables, increasing fertilizer promoted a higher number of crowns and flowers. For foliar area and yield, the 50 and 100% fertilizer doses obtained higher mean values without significant differences (p > 0.05) between doses. The maximum mean was obtained with 50% fertilizer for foliar area (121.7 cm2) and 100% for yield, with 67.8 Mg/ha.
For the microorganisms, significant differences (p ≤ 0.05) were only observed for the number of leaves, foliar area, number of flowers, crown diameter, and yield. In the case of the number of leaves, Azospirillum presented the highest mean of 47.58, while for foliar area, Rhizophagus sp. resulted in the highest mean (112.7 cm2); however, no significant differences were observed between the different microorganism treatments. For the number of flowers, Trichoderma promoted a higher mean value of 1.94. For crown diameter, mycorrhiza (Rhizophagus sp.) was observed with the highest mean (33.15 cm) but with no significant differences between the applied microorganisms. For yield, no significant differences were observed among Azospirillum (66.1 Mg/ha), Trichoderma (65.2 Mg/ha), and Rhizophagus sp. (67.2 Mg/ha), and all were superior to the no-microorganism-applied treatment (40.9 Mg/ha).
Since this study aimed to determine the optimum fertilizer dose, a regression analysis was performed using yield and fertilizer doses based on means across microorganism treatments (Figure 3). A quadratic equation was obtained, and the maximum value (first derivate) was 83.2 and 92.1% of the base fertilizer dose for Sabrina and San Andreas, respectively. Using 90% of the maximum dose as the “optimum”, the fertilizer requirements for the Sabrina and San Andreas cultivars were 74.88 and 82.9%, respectively. These values represent doses of 164.7 kg/ha of N, 73.4 kg/ha of P2O5, and 153.5 kg/ha of K2O for Sabrina, and for San Andreas, they represent doses of 182.4 kg/ha of N, 81.2 kg/ha of P2O5, and 170.0 kg/ha of K2O, making the Sabrina cultivar more efficient in terms of fertilizer use.

3.2. Effects on Nutrient Concentrations

For nutrient concentrations, ANOVA tables are presented in Table S2. N and Mg only presented an interaction effect between cultivar and microorganism. However, for P, K, and Ca contents, there were triple interactions between all tested effects. As visualization and interpretation may be compromised, the presentation of the results in Table 2 corresponds to the single effect of each treatment for each response variable. For the assessed cultivars, significant differences (p ≤ 0.05) were observed for N, P, and K. San Andreas presented a higher mean nutrient concentration for these elements, with 2.95% for N, 0.46% for P, and 1.98% for K. For the doses, significant differences (p ≤ 0.05) were only observed for P, Ca, and Mg, and a dose of 50% obtained a higher mean value of 0.45% for P, 0.97% for Ca, and 0.39% for Mg. Microorganisms resulted in significant differences (p ≤ 0.05) for N, K, and Ca. In most cases (with the exception of Ca), the control had the highest mean concentration of these elements compared to the other treatments. The lower mean concentration for N (2.87%) was obtained with Trichoderma, while for K (1.87%) and Ca (0.88%), it was obtained with Rhizophagus sp. In general, a lower concentration may indicate a higher nutrient efficiency. These results indicate that microorganisms may increase plant nutrient efficiency capabilities (NUE), as the yield was higher in all microorganism treatments.

3.3. Effects on Fruit Quality

The mean concentrations for each factor (cultivar, fertilizer dose, and microorganisms) for pH, acidity, Brix grade, and firmness are presented in Table 3, and ANOVA tables are presented in Table S3. For pH and acidity, no significant differences (p > 0.05) were observed between cultivars, fertilizer doses, or microorganisms. For Brix grade and firmness, significant differences were reported for fertilizer doses and microorganisms. In addition, for Brix grade, in the case of the fertilizer doses, the highest grade was observed in the absence of fertilizer application (7.31°). In the case of microorganisms, the highest was observed for Azospirillum brasilense, with 7.25°. For firmness, the dose of 50% obtained the highest value of 437 gf, and the lowest was observed in the absence of fertilizer. In the case of microorganisms, the highest value (397 gf) was observed in the absence of microorganisms, and the lowest value (374 gf) was observed with Trichoderma. For fruit size (circumference and height), significant differences were observed for fertilizer doses and cultivars (height only), with Sabrina obtaining a higher height. The fertilizer dose of 50% resulted in a greater circumference (26.4 mm) and height (36.9 mm).

4. Discussion

4.1. Strawberry Growth and Yield

The differences between strawberry cultivars Sabrina and San Andreas represented their different characteristics. However, the better performance of Sabrina in terms of the agronomic characteristics indicates its better adaptation to Cañete valley. Fertilizers did not affect agronomic characteristics, with the exception of yield, which can be directly linked to higher fertilizer doses. As nutrition demands vary between cultivars, sites, and amendment types, their relationship to yield can be attributed to several factors [25]. However, some studies have found that the correct use of fertilizers can improve general growth and the beneficial microorganism population in this crop [26,27]. As shown in this study, higher differences between treatments and the control were observed for microorganism application (Table 1). Several studies have expressed the importance and additive effect of different microorganisms in strawberry [8,14,15]. However, previous work in Peru in a different valley (Huaral) has also shown positive effects of Bacillus subtilis, Rhizofagus intraradices, Trichoderma, and Pseudomonas putida, with outstanding results for yield and growth in the San Andreas cultivar [28,29]. Studies in other countries, including in arid environments in Chile and Spain [13,30] and mountain climates in Brazil [27], Colombia [31], and Mexico [32], have also shown improvement in these variables. The literature confirms the results obtained in the present work. This greater yield in comparison to the treatment without microorganisms may be related to anatomical modifications in roots, as observed in maize [33]. The additional literature suggests changes in leaf anatomical traits that may enhance photosynthesis, such as a thicker palisade parenchyma [34]. This modification promotes better water relations in the plant [35]. The latter is of special interest in arid climates, such as Cañete valley, especially under moderate-soil-salinity conditions, which can limit yield production. Previous work has shown the effects of microorganisms on plants under soil salinity stress [36]. Microorganisms increase soil nutrient availability and produce osmoprotectants (mannitol, inositol, trehalose, glycine proline, and betaine) [37], which can further increase growth and yield in strawberry plants.

4.2. Strawberry Nutrition

In terms of nutrition, major differences were observed in different cultivars and in the effects of microorganisms. As the differences between these cultivars are expected due to genetic differences, focus will be placed on the effects of microorganisms. All microorganisms had a significant effect on most nutrients, with the exception of Mg. For N, major processes in the N cycle are dominated by microorganisms. In particular, N-fixing microorganisms constitute a N input in agricultural and ecological systems worldwide [38]. However, free N-fixing bacteria, such as Azospirilium, can also play a crucial role in N acquisition because many plants are associated with these bacteria, including strawberry [11,39]. This association can improve the soil biota, as these bacteria can be passed on to new generations via stolons [40]. Many microorganisms can improve N acquisition, including those of the Azospirilium genus [41], mycorrhiza [42], and Trichoderma [43]. Both mycorrhiza and Trichoderma may modify root anatomy, which can enhance nutrient exploration and acquisition [38]. For K, all microorganism treatments improved NUE for this nutrient compared to the control. In general, microorganisms tend to improve Ca and K acquisition for strawberry, as has been observed in this study for Azospirillum brasilense and as previously reported elsewhere for Trichoderma [44], mycorrhiza [14], and Azospirilium [45]. These nutrients (Ca and K) are related to abiotic and biotic stress signaling in plants [46,47]. Therefore, microorganisms can be an important tool for improving stress tolerance in strawberry, as was previously observed [48].

4.3. Strawberry Quality

Fertilization reduced the Brix grade, which was related to a higher biomass in comparison to the control without fertilizer. Other experiences with different cultivars have also shown this effect, especially for N doses [49,50], with little effect of K or P doses [50]. For microorganisms, only mycorrhiza reduced soluble sugars (Brix grade), which may be related to C consumption by this fungus, since it can receive 6% from the plant [51]. However, reports on this topic are diverse and indicate similar [42,52], higher [53], or lower [13] soluble sugars compared to the present study. In the case of firmness, all microorganisms induced lower values in relation to the control, which has also been reported elsewhere [13]. These effects may be related to the ripening role of these microorganisms in this species, as has been shown previously [54]. Additionally, in tomato (Solanum lycopersicon), Kosakonia radicincitans accelerated fruit ripening due to the activation of the jasmonic acid pathway, which stimulates fruit ripening and, consequently, reduces fruit firmness [55].

5. Conclusions

Strawberry is an important crop worldwide and this study explored the effect of cultivars, fertilizer doses, and microorganisms related to crop growth, yield, and quality in Peru. The study demonstrated that the Sabrina cultivar had better performance in terms of growth and yield in comparison to San Andreas. All fertilizer doses promoted yield and fruit quality in comparison to the control. All microorganisms influenced growth, yield, and fruit quality characteristics, demonstrating their importance in improving fruit production in this crop. Finally, the study showed that microorganisms can enhance nutrient use efficiency in strawberry plants and reduce fertilizer doses without compromising yield or quality, which can contribute to sustainable crop production and decrease the risk of salinization caused by fertigation under arid conditions.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/agriengineering7110381/s1, Table S1: ANOVA Table for agronomical variables with p-value for each source of variation, simple effects and interactions for the split-plot experiment with different fertilizer doses, microorganisms and cultivars in Strawberry in Cañete, Peru. Bold numbers indicate significant differences; Table S2: ANOVA Table for nutritional variables with p-value for each source of variation, simple effects and interactions for the split-plot experiment with different fertilizer doses, microorganisms and cultivars in Strawberry in Cañete, Peru. Bold numbers indicate significant differences; Table S3: ANOVA Table for quality of fruit variables with p-value for each source of variation, simple effects and interactions for the split-plot experiment with different fertilizer doses, microorganisms and cultivars in Strawberry in Cañete, Peru. Bold numbers indicate significant differences.

Author Contributions

Conceptualization, B.L.T., M.A.Ñ.A. and C.O.A.-H.; Data curation, R.L.C.M. and C.O.A.-H.; Investigation, A.J.P.M. and R.L.C.M.; Methodology, B.L.T., M.A.Ñ.A. and C.O.A.-H.; Resources, B.L.T.; Supervision, A.J.P.M. and M.A.Ñ.A.; Validation, R.L.C.M.; Visualization, C.O.A.-H.; Writing—original draft, B.L.T. and C.O.A.-H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Research Project N°06: “Optimización del uso de agroquímicos en la producción de fresa con la incorporación de microorganismos benéficos para el control de enfermedades fungosas, mejora del rendimiento y calidad del fruto” from Universidad of Cañete.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are not publicly available due to restrictions related to confidentiality and proprietary information.

Acknowledgments

The authors would like to thank the Universidad of Cañete for infrastructure and logistics.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
ANOVAAnalysis of Variance
RCBDRandomized Complete Block Design
SEStandard Error

References

  1. Dirección General de Estadística—MIDAGRI. Seguimiento y Evaluación de Políticas. In Boletin estadistico Mensual: El Agro en Cifras. Diciembre 2024; MIDAGRI: Lima, Perú, 2025; p. 166. [Google Scholar]
  2. Fischer, G.; Miranda, D.; Magnitskiy, S.; Balaguera-López, H.E.; Molano, Z. (Eds.) Avances en el Cultivo de las Berries en el Trópico; Sociedad Colombiana de Ciencias Hortícolas: Bogotá, Colombia, 2021; ISBN 978-958-59886-1-3. [Google Scholar]
  3. Basu, A.; Nguyen, A.; Betts, N.M.; Lyons, T.J. Strawberry As a Functional Food: An Evidence-Based Review. Crit. Rev. Food Sci. Nutr. 2014, 54, 790–806. [Google Scholar] [CrossRef]
  4. Skaggs, R.K. Predicting Drip Irrigation Use and Adoption in a Desert Region. Agric. Water Manag. 2001, 51, 125–142. [Google Scholar] [CrossRef]
  5. Gamboa, N.R.; Marchese, A.B.; Tavares Corrêa, C.H. Salinization in Peruvian North Coast Soils: Case Study in San Pedro de Lloc. In Saline and Alkaline Soils in Latin America: Natural Resources, Management and Productive Alternatives; Taleisnik, E., Lavado, R.S., Eds.; Springer International Publishing: Cham, Switzerland, 2021; pp. 141–159. ISBN 978-3-030-52592-7. [Google Scholar]
  6. Nestby, R.; Lieten, F.; Pivot, D.; Raynal Lacroix, C.; Tagliavini, M. Influence of Mineral Nutrients on Strawberry Fruit Quality and Their Accumulation in Plant Organs. Int. J. Fruit Sci. 2005, 5, 139–156. [Google Scholar] [CrossRef]
  7. Bindraban, P.S.; Dimkpa, C.; Nagarajan, L.; Roy, A.; Rabbinge, R. Revisiting Fertilisers and Fertilisation Strategies for Improved Nutrient Uptake by Plants. Biol. Fertil. Soils 2015, 51, 897–911. [Google Scholar] [CrossRef]
  8. Tomić, J.; Pešaković, M.; Milivojević, J.; Karaklajić-Stajić, Ž. How to Improve Strawberry Productivity, Nutrients Composition, and Beneficial Rhizosphere Microflora by Biofertilization and Mineral Fertilization? J. Plant Nutr. 2018, 41, 2009–2021. [Google Scholar] [CrossRef]
  9. Bhattacharjee, R.B.; Singh, A.; Mukhopadhyay, S.N. Use of Nitrogen-Fixing Bacteria as Biofertiliser for Non-Legumes: Prospects and Challenges. Appl. Microbiol. Biotechnol. 2008, 80, 199–209. [Google Scholar] [CrossRef] [PubMed]
  10. Lin, G.; McCormack, M.L.; Guo, D. Arbuscular Mycorrhizal Fungal Effects on Plant Competition and Community Structure. J. Ecol. 2015, 103, 1224–1232. [Google Scholar] [CrossRef]
  11. Cassán, F.; Coniglio, A.; López, G.; Molina, R.; Nievas, S.; de Carlan, C.L.N.; Donadio, F.; Torres, D.; Rosas, S.; Pedrosa, F.O.; et al. Everything You Must Know about Azospirillum and Its Impact on Agriculture and Beyond. Biol. Fertil. Soils 2020, 56, 461–479. [Google Scholar] [CrossRef]
  12. Vinale, F.; Sivasithamparam, K. Beneficial Effects of Trichoderma Secondary Metabolites on Crops. Phytother. Res. 2020, 34, 2835–2842. [Google Scholar] [CrossRef]
  13. Drobek, M.; Cybulska, J.; Gałązka, A.; Feledyn-Szewczyk, B.; Marzec-Grządziel, A.; Sas-Paszt, L.; Gryta, A.; Trzciński, P.; Zdunek, A.; Frąc, M. The Use of Interactions Between Microorganisms in Strawberry Cultivation (Fragaria x Ananassa Duch.). Front. Plant Sci. 2021, 12, 780099. [Google Scholar] [CrossRef]
  14. Todeschini, V.; AitLahmidi, N.; Mazzucco, E.; Marsano, F.; Gosetti, F.; Robotti, E.; Bona, E.; Massa, N.; Bonneau, L.; Marengo, E.; et al. Impact of Beneficial Microorganisms on Strawberry Growth, Fruit Production, Nutritional Quality, and Volatilome. Front. Plant Sci. 2018, 9, 1611. [Google Scholar] [CrossRef]
  15. Bona, E.; Lingua, G.; Manassero, P.; Cantamessa, S.; Marsano, F.; Todeschini, V.; Copetta, A.; D’Agostino, G.; Massa, N.; Avidano, L.; et al. AM Fungi and PGP Pseudomonads Increase Flowering, Fruit Production, and Vitamin Content in Strawberry Grown at Low Nitrogen and Phosphorus Levels. Mycorrhiza 2015, 25, 181–193. [Google Scholar] [CrossRef] [PubMed]
  16. Gryndler, M.; Vosátka, M.; Hrŝelová, H.; Catská, V.; Chvátalová, I.; Jansa, J. Effect of Dual Inoculation with Arbuscular Mycorrhizal Fungi and Bacteria on Growth and Mineral Nutrition of Strawberry. J. Plant Nutr. 2002, 25, 1341–1358. [Google Scholar] [CrossRef]
  17. Cui, D.; Liang, S.; Wang, D. Observed and Projected Changes in Global Climate Zones Based on Köppen Climate Classification. WIREs Clim. Change 2021, 12, e701. [Google Scholar] [CrossRef]
  18. Richardson, M.L.; Arlotta, C.G.; Lewers, K.S. Yield and Nutrients of Six Cultivars of Strawberries Grown in Five Urban Cropping Systems. Sci. Hortic. 2022, 294, 110775. [Google Scholar] [CrossRef]
  19. Anderson, J.M.; Ingram, J.S.I. Tropical Soil Biology and Fertility: A Handbook of Methods; CAB International: Wallingford, UK, 1993; Volume 78, ISBN 0-85198-821-0. [Google Scholar]
  20. Demirsoy, H.; Demirsoy, L.; Öztürk, A. Improved Model for the Non-Destructive Estimation of Strawberry Leaf Area. Fruits 2005, 60, 69–73. [Google Scholar] [CrossRef]
  21. EMBRAPA. Manual de Análises Químicas de Solos, Plantas e Fertilizantes; Embrapa: Brasília, Brazil, 2009; ISBN 978-85-7383-430-7. [Google Scholar]
  22. R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2021; Available online: http://www.R-project.org/ (accessed on 10 September 2025).
  23. Bates, D.; Maechler, M.; Bolker, B.; Walker, S. Lme4: Linear Mixed-Effects Models Using “Eigen” and S4, version 1.1-37; R Foundation for Statistical Computing: Vienna, Austria, 2003. [Google Scholar]
  24. Faria, J.C.; Jelihovschi, E.G.; Allaman, I.B. ScottKnott: The ScottKnott Clustering Algorithm, version 1.3-3; R Foundation for Statistical Computing: Vienna, Austria, 2009. [Google Scholar]
  25. Li, Q.; Zhang, D.; Song, Z.; Ren, L.; Jin, X.; Fang, W.; Yan, D.; Li, Y.; Wang, Q.; Cao, A. Organic Fertilizer Activates Soil Beneficial Microorganisms to Promote Strawberry Growth and Soil Health after Fumigation. Environ. Pollut. 2022, 295, 118653. [Google Scholar] [CrossRef] [PubMed]
  26. Bai, X.; Liu, K.; Ning, T.; Deng, C.; Wang, L.; Li, D.; Wang, T.; Li, J. Effects of Multiple N, P, and K Fertilizer Combinations on Strawberry Growth and the Microbial Community. PLoS ONE 2023, 18, e0293088. [Google Scholar] [CrossRef] [PubMed]
  27. de Andrade, F.M.; de Assis Pereira, T.; Souza, T.P.; Guimarães, P.H.S.; Martins, A.D.; Schwan, R.F.; Pasqual, M.; Dória, J. Beneficial Effects of Inoculation of Growth-Promoting Bacteria in Strawberry. Microbiol. Res. 2019, 223, 120–128. [Google Scholar] [CrossRef] [PubMed]
  28. Huasasquiche, L.; Alejandro, L.; Ccori, T.; Cántaro-Segura, H.; Samaniego, T.; Quispe, K.; Solórzano, R. Bacillus Subtilis and Rhizophagus Intraradices Improve Vegetative Growth, Yield, and Fruit Quality of Fragaria × Ananassa Var. San Andreas. Microorganisms 2024, 12, 1816. [Google Scholar] [CrossRef]
  29. Huasasquiche, L.; Ccori, T.; Alejandro, L.; Cántaro-Segura, H.; Samaniego, T.; Solórzano, R. Interaction between Trichoderma Sp., Pseudomonas Putida, and Two Organic Amendments on the Yield and Quality of Strawberries (Fragaria x Annanasa Cv. San Andreas) in the Huaral Region, Peru. Appl. Microbiol. 2024, 4, 1110–1123. [Google Scholar] [CrossRef]
  30. Pérez-Moncada, U.A.; Santander, C.; Ruiz, A.; Vidal, C.; Santos, C.; Cornejo, P. Design of Microbial Consortia Based on Arbuscular Mycorrhizal Fungi, Yeasts, and Bacteria to Improve the Biochemical, Nutritional, and Physiological Status of Strawberry Plants Growing under Water Deficits. Plants 2024, 13, 1556. [Google Scholar] [CrossRef]
  31. Flórez-Hernández, E.A.; Montes-Ciro, E.; Hurtado-Salazar, A.; Aristizábal, J.C.; Ceballos-Aguirre, N.; Flórez-Hernández, E.A.; Montes-Ciro, E.; Hurtado-Salazar, A.; Aristizábal, J.C.; Ceballos-Aguirre, N. Technical-Economic Evaluation of Bacterial Consortia in Strawberry Cultivation across Two Production Systems. Rev. Colomb. Cienc. Hortícolas 2023, 17, e16506. [Google Scholar] [CrossRef]
  32. Cruz, S.M.-D.L.; González-Fuentes, J.A.; Robledo-Olivo, A.; Mendoza-Villarreal, R.; Hernández-Pérez, A.; Dávila-Medina, M.D.; Alvarado-Camarillo, D. Humic Substances and Rhizobacteria Enhance the Yield, Physiology and Quality of Strawberries. Not. Bot. Horti Agrobot. Cluj-Napoca 2022, 50, 12578. [Google Scholar] [CrossRef]
  33. Calzavara, A.K.; Paiva, P.H.G.; Gabriel, L.C.; Oliveira, A.L.M.; Milani, K.; Oliveira, H.C.; Bianchini, E.; Pimenta, J.A.; de Oliveira, M.C.N.; Dias-Pereira, J.; et al. Associative Bacteria Influence Maize (Zea mays L.) Growth, Physiology and Root Anatomy under Different Nitrogen Levels. Plant Biol. 2018, 20, 870–878. [Google Scholar] [CrossRef]
  34. Paradiso, R.; Arena, C.; De Micco, V.; Giordano, M.; Aronne, G.; De Pascale, S. Changes in Leaf Anatomical Traits Enhanced Photosynthetic Activity of Soybean Grown in Hydroponics with Plant Growth-Promoting Microorganisms. Front. Plant Sci. 2017, 8, 674. [Google Scholar] [CrossRef] [PubMed]
  35. Guerfel, M.; Baccouri, O.; Boujnah, D.; Chaïbi, W.; Zarrouk, M. Impacts of Water Stress on Gas Exchange, Water Relations, Chlorophyll Content and Leaf Structure in the Two Main Tunisian Olive (Olea europaea L.) Cultivars. Sci. Hortic. 2009, 119, 257–263. [Google Scholar] [CrossRef]
  36. Acharya, B.R.; Gill, S.P.; Kaundal, A.; Sandhu, D. Strategies for Combating Plant Salinity Stress: The Potential of Plant Growth-Promoting Microorganisms. Front. Plant Sci. 2024, 15, 1406913. [Google Scholar] [CrossRef]
  37. Van Zelm, E.; Zhang, Y.; Testerink, C. Salt Tolerance Mechanisms of Plants. Annu. Rev. Plant Biol. 2020, 71, 403–433. [Google Scholar] [CrossRef]
  38. Xiong, Q.; Hu, J.; Wei, H.; Zhang, H.; Zhu, J. Relationship between Plant Roots, Rhizosphere Microorganisms, and Nitrogen and Its Special Focus on Rice. Agriculture 2021, 11, 234. [Google Scholar] [CrossRef]
  39. Dellagi, A.; Quillere, I.; Hirel, B. Beneficial Soil-Borne Bacteria and Fungi: A Promising Way to Improve Plant Nitrogen Acquisition. J. Exp. Bot. 2020, 71, 4469–4479. [Google Scholar] [CrossRef]
  40. Guerrero-Molina, M.F.; Winik, B.C.; Pedraza, R.O. More than Rhizosphere Colonization of Strawberry Plants by Azospirillum brasilense. Appl. Soil Ecol. 2012, 61, 205–212. [Google Scholar] [CrossRef]
  41. Naqqash, T.; Malik, K.A.; Imran, A.; Hameed, S.; Shahid, M.; Hanif, M.K.; Majeed, A.; Iqbal, M.J.; Qaisrani, M.M.; van Elsas, J.D. Inoculation with Azospirillum spp. Acts as the Liming Source for Improving Growth and Nitrogen Use Efficiency of Potato. Front. Plant Sci. 2022, 13, 929114. [Google Scholar] [CrossRef]
  42. Castellanos-Morales, V.; Villegas-Moreno, J.; Vierheilig, H.; Cárdenas-Navarro, R. Nitrogen Availability Drives the Effect of Glomus Intraradices on the Growth of Strawberry (Fragaria x Ananassa Duch.) Plants. J. Sci. Food Agric. 2012, 92, 2260–2264. [Google Scholar] [CrossRef] [PubMed]
  43. Singh, B.N.; Dwivedi, P.; Sarma, B.K.; Singh, G.S.; Singh, H.B. Trichoderma Asperellum T42 Reprograms Tobacco for Enhanced Nitrogen Utilization Efficiency and Plant Growth When Fed with N Nutrients. Front. Plant Sci. 2018, 9, 163. [Google Scholar] [CrossRef] [PubMed]
  44. Lombardi, N.; Caira, S.; Troise, A.D.; Scaloni, A.; Vitaglione, P.; Vinale, F.; Marra, R.; Salzano, A.M.; Lorito, M.; Woo, S.L. Trichoderma Applications on Strawberry Plants Modulate the Physiological Processes Positively Affecting Fruit Production and Quality. Front. Microbiol. 2020, 11, 1364. [Google Scholar] [CrossRef]
  45. Paliwoda, D.; Mikiciuk, G.; Chudecka, J.; Tomaszewicz, T.; Miller, T.; Mikiciuk, M.; Kisiel, A.; Sas-Paszt, L. Effects of Inoculation with Plant Growth-Promoting Rhizobacteria on Chemical Composition of the Substrate and Nutrient Content in Strawberry Plants Growing in Different Water Conditions. Agriculture 2024, 14, 46. [Google Scholar] [CrossRef]
  46. Ghosh, S.; Bheri, M.; Bisht, D.; Pandey, G.K. Calcium Signaling and Transport Machinery: Potential for Development of Stress Tolerance in Plants. Curr. Plant Biol. 2022, 29, 100235. [Google Scholar] [CrossRef]
  47. Sardans, J.; Peñuelas, J. Potassium Control of Plant Functions: Ecological and Agricultural Implications. Plants 2021, 10, 419. [Google Scholar] [CrossRef]
  48. Grover, M.; Ali, S.Z.; Sandhya, V.; Rasul, A.; Venkateswarlu, B. Role of Microorganisms in Adaptation of Agriculture Crops to Abiotic Stresses. World J. Microbiol. Biotechnol. 2011, 27, 1231–1240. [Google Scholar] [CrossRef]
  49. Agehara, S. Characterizing Early-Season Nitrogen Fertilization Rate Effects on Growth, Yield, and Quality of Strawberry. Agronomy 2021, 11, 905. [Google Scholar] [CrossRef]
  50. Wu, Y.; Li, L.; Li, M.; Zhang, M.; Sun, H.; Sigrimis, N. Optimal Fertigation for High Yield and Fruit Quality of Greenhouse Strawberry. PLoS ONE 2020, 15, e0224588. [Google Scholar] [CrossRef]
  51. Hawkins, H.-J.; Cargill, R.I.M.; Nuland, M.E.V.; Hagen, S.C.; Field, K.J.; Sheldrake, M.; Soudzilovskaia, N.A.; Kiers, E.T. Mycorrhizal Mycelium as a Global Carbon Pool. Curr. Biol. 2023, 33, R560–R573. [Google Scholar] [CrossRef] [PubMed]
  52. Cecatto, A.P.; Ruiz, F.M.; Calvete, E.O.; Martínez, J.; Palencia, P. Mycorrhizal Inoculation Affects the Phytochemical Content in Strawberry Fruits. Acta Sci. Agron. 2016, 38, 227–237. [Google Scholar] [CrossRef]
  53. Cordeiro, E.C.N.; de Resende, J.T.V.; Córdova, K.R.V.; Nascimento, D.A.; Saggin, O.J.; Zeist, A.R.; Favaro, R. Arbuscular Mycorrhizal Fungi Action on the Quality of Strawberry Fruits. Hortic. Bras. 2019, 37, 437–444. [Google Scholar] [CrossRef]
  54. Nam, J.H.; Thibodeau, A.; Qian, Y.L.; Qian, M.C.; Park, S.H. Multidisciplinary Evaluation of Plant Growth Promoting Rhizobacteria on Soil Microbiome and Strawberry Quality. AMB Express 2023, 13, 18. [Google Scholar] [CrossRef]
  55. Berger, B.; Baldermann, S.; Ruppel, S. The Plant Growth-promoting Bacterium Kosakonia Radicincitans Improves Fruit Yield and Quality of Solanum Lycopersicum. J. Sci. Food Agric. 2017, 97, 4865–4871. [Google Scholar] [CrossRef]
Agriengineering 07 00381 g001
Figure 1. Experimental design scheme (RCBD) in a split-plot arrangement with a factorial design of 2 × 4 and three blocks for strawberry in Cañete, Peru.
Figure 1. Experimental design scheme (RCBD) in a split-plot arrangement with a factorial design of 2 × 4 and three blocks for strawberry in Cañete, Peru.
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Figure 2. Experimental area and agronomic measurement of an RCBD in a split-plot arrangement with a factorial design of 2 × 4 and three blocks for strawberry in Cañete, Peru.
Figure 2. Experimental area and agronomic measurement of an RCBD in a split-plot arrangement with a factorial design of 2 × 4 and three blocks for strawberry in Cañete, Peru.
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Figure 3. Regression graph with quadratic models of yield (Mg/ha) vs. fertilizer doses (%) for Sabrina (left) and San Andreas (right) cultivars in Cañete, Peru. Confidence intervals are shown at 95%.
Figure 3. Regression graph with quadratic models of yield (Mg/ha) vs. fertilizer doses (%) for Sabrina (left) and San Andreas (right) cultivars in Cañete, Peru. Confidence intervals are shown at 95%.
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Table 1. Mean (SE) values for the number of leaves, foliar area (cm2), number of crowns, number of flowers, number of stolons, petiole length and diameter (cm), crown diameter (cm), number of fruits, and yield (Mg/ha) with two strawberry cultivars and the application of different fertilizer doses and microorganisms in Cañete, Peru.
Table 1. Mean (SE) values for the number of leaves, foliar area (cm2), number of crowns, number of flowers, number of stolons, petiole length and diameter (cm), crown diameter (cm), number of fruits, and yield (Mg/ha) with two strawberry cultivars and the application of different fertilizer doses and microorganisms in Cañete, Peru.
Treatments Number of Leaves Foliar Area—cm2Number of CrownsNumber of FlowersStolonsPetiole Length—cmPetiole Diameter—cmCrown Diameter—cmNumber of Fruits—106 Yield—Mg/ha
Cultivars (n = 3)
Sabrina49.32 (10.32) a108.9 (15.18) a2.18 (0.81) a1.83 (0.58) a0.09 (0.07) b17.50 (2.33) a2.49 (0.32)33.79 (1.70) a3.47 (0.08) a62.5 (15.7) a
San Andreas30.21 (6.15) b93.2 (14.55) b1.82 (0.46) b1.51 (0.44) b0.16 (0.09) a15.16 (2.70) b2.46 (0.24)30.70 (1.62) b3.08 (0.10) b54.2 (11.5) b
Pv*********ns****
Doses % (n = 3)
042.28 (10.21)84.3 (8.72) c2.54 (0.61)1.40 (0.41)0.15 (0.08)15.42 (2.63)2.62 (0.34)33.76 (1.63)2.79 (0.3) c49.9 (12.0) c
5036.94 (6.89)121.7 (17.96) a1.25 (0.26)1.71 (0.47)0.13 (0.08)16.51 (2.51)2.27 (0.15)32.18 (2.10)3.63 (0.17) a62.7 (13.8) a
10041.40 (11.51)108.2 (12.93) a1.55 (0.58)1.62 (0.55)0.06 (0.07)15.29 (2.48)2.45 (0.33)31.25 (1.68)3.45 (0.16) a64.6 (17.1) a
15039.55 (10.64)90.0 (10.45) b2.61 (0.70)1.91 (0.61)0.18 (0.09)17.94 (2.63)2.57 (0.21)31.57 (1.83)3.24 (0.12) b56.4 (13.0) b
Pvns****nsnsnsns***
Microorganisms (n = 3)
Azospirillum brasilense47.58 (11.43) a103.0 (14.43) a2.1 (0.80)1.65 (0.64) b0.11 (0.08)15.82 (2.60)2.41 (0.25)32.74 (1.77) a3.54 (0.06) a62.2 (11.8) a
Rhizophagus sp.42.63 (8.79) a112.7 (18.48) a1.97 (0.71)1.69 (0.43) b0.12 (0.09)16.17 (2.82)2.44 (0.26)33.15 (1.88) a3.25 (0.08) b59.6 (10.1) a
Trichoderma sp.41.17 (7.74) a102.9 (15.13) a2.13 (0.73)1.94 (0.62) a0.11 (0.09)15.6 (2.62)2.56 (0.36)33.0 (1.55) a3.52 (0.11) a64.2 (8.59) a
Control26.09 (7.62) b85.6 (8.08) b1.78 (0.29)1.36 (0.30) c0.17 (0.08)17.53 (2.38)2.49 (0.24)29.84 (1.69) b2.13 (0.08) c40.9 (7.13) b
Pv****ns*nsnsns*****
Notes: * indicates significant differences at 0.05; ** indicates significant differences at 0.01; ns indicates no significant differences at 0.05. Different letters indicate significant differences at 0.05 according to the Scott–Knott test.
Table 2. Mean (SE) values for macronutrients (N, P, K, Ca, and Mg) in % with two strawberry cultivars and application of different fertilizer doses and microorganisms in Cañete, Peru.
Table 2. Mean (SE) values for macronutrients (N, P, K, Ca, and Mg) in % with two strawberry cultivars and application of different fertilizer doses and microorganisms in Cañete, Peru.
TreatmentsNPKCaMg
%
Cultivars (n = 3)
Sabrina2.88 (0.13) b0.43 (0.03) b1.83 (0.16) b0.94 (0.15)0.37 (0.04)
San Andreas2.95 (0.15) a0.46(0.05) a1.98 (0.21) a0.92 (0.14)0.36 (0.04)
Pv****nsns
Doses (n = 3)
02.90 (0.13)0.42 (0.06) b1.77 (0.20) c0.87 (0.15) b0.32 (0.03) b
502.89 (0.18)0.45 (0.03) a2.01 (0.15) a 0.97 (0.14) a0.39 (0.04) a
1002.95 (0.16)0.45 (0.05) a1.95 (0.19) a0.91 (0.14) b0.37 (0.04) a
1502.91 (0.11)0.44 (0.03) a1.85 (0.15) b0.98 (0.11) a0.37 (0.03) a
Pvns******
Microorganisms (n = 3)
Azospirillum brasilense2.92 (0.16) b0.44 (0.05) 1.89 (0.17) b0.99 (0.14) a0.37 (0.03)
Rhizophagus sp.2.88 (0.09) b0.46 (0.04) 1.87 (0.19) b0.88 (0.13) b0.35 (0.05)
Trichoderma sp.2.87 (0.12) b0.43 (0.04) 1.88 (0.19) b0.89 (0.12) b0.36 (0.04)
Control3.01 (0.15) a0.45 (0.06) 1.99 (0.24) a0.97 (0.17) a0.37 (0.04)
Pv*ns***ns
Notes: * indicates significant differences at 0.05; ** indicates significant differences at 0.01; ns indicates no significant differences at 0.05. Different letters indicate significant differences at 0.05 according to the Scott–Knott test.
Table 3. Mean (SE) values for fruit quality parameters (pH, acidity, Brix grade, firmness (N), and circumference (mm)) with two strawberry cultivars and application of different fertilizer doses and microorganisms in Cañete, Peru.
Table 3. Mean (SE) values for fruit quality parameters (pH, acidity, Brix grade, firmness (N), and circumference (mm)) with two strawberry cultivars and application of different fertilizer doses and microorganisms in Cañete, Peru.
TreatmentspHAcidityBrix GradeFirmness—g-fCircumference—mm
Cultivars (n = 3)
Sabrina3.35 (0.07)0.95 (0.03)7.08 (0.95)386 (75.1)24.95 (9.5)
San Andreas3.30 (0.03)1.03 (0.06)7.18 (0.88)394 (81.2)24.1 (8.88)
Pvnsnsnsnsns
Doses % (n = 3)
03.35 (0.10)1.00 (0.03)7.31 (0.97) a363 (82.3) b23.7 (8.51) b
503.29 (0.03)0.99 (0.05)7.04 (0.89) b437 (65.5) a26.4 (10.3) a
1003.34 (0.02)0.96 (0.07)6.96 (0.94) b396 (59.5) a25.5 (9.43) a
1503.33 (0.04)0.99 (0.09)7.13 (0.86) b364 (77.8) b23.9 (9.55) b
Pvnsns****
Microorganisms (n = 3)
Azospirillum3.33 (0.04)0.95 (0.04)7.25 (0.93) a387 (80.2) b25.1 (9.94)
Rhizophagus sp.3.30 (0.04)0.99 (0.06)6.86 (0.9) b385 (71.2) b25.6 (10.1)
Trichoderma3.32 (0.05)1.01 (0.08)7.20 (0.86) a374 (84.0) c24.9 (9.47)
Control3.34 (0.1)1.01 (0.08)7.18 (0.96) a397 (80.1) a23.2 (8.49)
Pvnsns**ns
Notes: * indicates significant differences at 0.05; ** indicates significant differences at 0.01; ns indicates no significant differences at 0.05. Different letters indicate significant differences at 0.05 according to the Scott–Knott test.
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Ttacca, B.L.; Peña Meneses, A.J.; Chipana Manrique, R.L.; Ñique Alvarez, M.A.; Arévalo-Hernández, C.O. Fertilizers and Microorganisms Promote Strawberry Growth, Yield, and Quality in Peru. AgriEngineering 2025, 7, 381. https://doi.org/10.3390/agriengineering7110381

AMA Style

Ttacca BL, Peña Meneses AJ, Chipana Manrique RL, Ñique Alvarez MA, Arévalo-Hernández CO. Fertilizers and Microorganisms Promote Strawberry Growth, Yield, and Quality in Peru. AgriEngineering. 2025; 7(11):381. https://doi.org/10.3390/agriengineering7110381

Chicago/Turabian Style

Ttacca, Betsabe Leon, Ariana Jossety Peña Meneses, Reyno Leonardo Chipana Manrique, Manuel Alfredo Ñique Alvarez, and César Oswaldo Arévalo-Hernández. 2025. "Fertilizers and Microorganisms Promote Strawberry Growth, Yield, and Quality in Peru" AgriEngineering 7, no. 11: 381. https://doi.org/10.3390/agriengineering7110381

APA Style

Ttacca, B. L., Peña Meneses, A. J., Chipana Manrique, R. L., Ñique Alvarez, M. A., & Arévalo-Hernández, C. O. (2025). Fertilizers and Microorganisms Promote Strawberry Growth, Yield, and Quality in Peru. AgriEngineering, 7(11), 381. https://doi.org/10.3390/agriengineering7110381

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