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Article

Effect of Organic Amendments and Biostimulants on Zucchini Yield and Fruit Quality Under Alkaline Conditions

by
Samira Islas-Valdez
,
Reagan Sproull
,
Ty Sumners
and
Nicole Wagner
*
Department of Agricultural Sciences, Texas State University, 601 University Dr, San Marcos, TX 78666, USA
*
Author to whom correspondence should be addressed.
Agriculture 2025, 15(19), 2078; https://doi.org/10.3390/agriculture15192078
Submission received: 3 September 2025 / Revised: 2 October 2025 / Accepted: 2 October 2025 / Published: 5 October 2025
(This article belongs to the Section Agricultural Soils)
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Abstract

Soil amendments can enhance soil and plant health; however, limited research has addressed their effects on soil health and crop productivity in alkaline soil. This study investigated the effects of various soil amendments and biostimulants by the Haney Soil Health Test, plant sap analysis, and Cucurbita pepo cv. ‘Dunja’ yield and quality. Treatments included unamended soil (T1) and applications of Humisoil® (T2), Humisoil with biochar (T3), wood vinegar (T4), Ensoil algaeTM (T5), and Humisoil with biochar and basaltic rock dust (T6). Compared to T1, T6, T5, T2, and T3 increased yield by 107%, 87%, 86%, and 52%, respectively. Regarding total fruit number per plant, T2, T6, and T5 outperformed T1 by 42%, 37%, and 37%, respectively. Additionally, T6 decreased Na concentration by 59% in the sap of young leaves and 50% in old leaves compared to T1. Compared to T1, T2 also reduced Na concentration in the sap of old leaves by 63%. For Cl, decreases of 30%, 16%, and 24% in old leaves were observed in T2, T4, and T6 treatments, respectively. These findings highlight the potential of biostimulants and soil amendments to improve zucchini yield and quality while improving soil health in alkaline soils.

1. Introduction

Soil degradation poses a major global challenge. Approximately one-third of the world’s agricultural land suffers from at least one type of degradation, such as soil or water pollution, erosion, depletion of soil organic matter, nutrient imbalances, salinization, acidification, crusting, or loss of soil biodiversity [1,2]. The use of organic and inorganic soil amendments, including compost, biochar, algae, and minerals, can be an effective strategy for improving soil, specifically by improving soil organic content, aggregation, and soil structure in the short term, leading to increased water infiltration and retention, carbon sequestration, microbial biodiversity, and nutrient availability [3]. The benefits of soil amendment applications, however, depend on several parameters, including the quality and type of amendment and application rate, timing, and method [4], as well as soil parameters, such as pH [5].
Among the wide range of soil amendments and biostimulants available on the market, several have been shown to enhance soil properties and crop productivity. Specifically, biochar, a carbon-rich byproduct of pyrolysis, is resistant to decomposition and remains stable in soils for hundreds of years, contributing to improved soil porosity, water holding capacity, and carbon sequestration [6]. Some studies have also demonstrated its positive effect on soil microbial biomass, enzymatic activities [7], and diversity [7,8]. Applications of algae, Chlorella vulgaris, have been shown to increase leaf and root biomass, reduce nitrogen (N) and phosphorus (P) leaching, enhance water quality, and increase nutrient concentrations in soils [9,10]. Basaltic rock dust (BRD) releases macro- and micronutrients, which improves nutrient availability, promotes crop development, and helps balance soil pH [11,12,13]. Humisoil, a static compost that utilizes aerobic and fermentation processes, enhances N fixation and P mobilization [14]. Additionally, Humisoil is known to sequester higher rates of carbon and nitrogen compounds during its production compared to thermophilic aerobic compost methods and increase nutrient availability to plants [14]. A byproduct of biochar production, wood vinegar, has been shown to enhance soil health by increasing enzymatic activity, reducing heavy metal toxicity, and inhibiting ammonia volatilization [15].
These organic amendments may mitigate the adverse effects of high pH in alkali soils, which impair crop water and nutrient uptake (e.g., P, Fe, Mn, Zn, Cu, B), reducing chlorophyll synthesis, nutritional quality, taste, and plant growth, and sometimes causing crop loss [16]. By improving soil structure and enhancing microbial activity, these amendments promote soil health and boost crop productivity. Additionally, when used in combination, they can offer synergistic benefits [17], providing an alternative to other methods, such as using traditional chelates or alkali-resistant crop varieties [18]. This is critical for addressing the estimated $27.3 billion in annual losses, which increase by 1 to 2 million hectares each year, considering that approximately 954 million hectares of saline–alkali land exist globally, with alkaline soils comprising about half of this area [18].
The scientific literature has elucidated the benefits of various soil amendments, as briefly described above. However, farmers, especially those in temperate to arid climates with alkaline soils, may be challenged to choose amendments and/or biostimulants for their context given the wide array of products on the market. To help discern differences among products, this study evaluated several common and promising amendments and biostimulants available to farmers—specifically Humisoil, biochar, EnSoil Algae, wood vinegar, and BRD—on crop development in alkaline soils, which are prevalent across Texas and other arid regions. These amendments and biostimulants were chosen based on support in the scientific literature and global case studies for their beneficial effects on soil health and plant growth.
While summer squash (Cucurbita pepo) is among the most widely grown and economically important cucurbits worldwide [19], it was chosen for this study due to several practical reasons as well as its broad agricultural relevance. Specifically, zucchini (Cucurbita pepo, cv. ‘Dunja’) has fast growth, large fruit and leaf size, and early production, which facilitates rapid data collection for differential plant sap analysis. Plant sap analysis allows for real-time assessment of the nutrient status in both young and old leaves, allowing for the adjustment of fertilization accordingly to address nutrient deficiencies [20]. Due to zucchini’s relatively fast growth and short lifecycle, researchers can observe the effects of soil treatments within a single growing season. Additionally, this crop is sensitive to changes in soil conditions such as fertility and pH, making it easier to detect the impact of amendments. Because Cucurbita pepo has a high nutrient demand, improvements in soil quality often translate into noticeable differences in growth and fruit yield.
This work aims to fill the mention knowledge gap about the agronomic effect of amendments and/or biostimulants in temperate to arid climates with alkaline soils. It can therefore be hypothesized that the application of Humisoil, biochar, EnSoil Algae, wood vinegar, and BRD would increase yield and fruit quality by improving plant nutrition and soil health. Thus, the specific objectives were to (1) compare the efficiency of these amendments and/or biostimulants to increase zucchini yield and fruit quality under alkaline conditions, and (2) test the ability of differential sap analysis and the Haney soil health test to detect changes in nutrient status and soil health.

2. Materials and Methods

2.1. Experimental Location

The experiment was conducted in a 7.32 m × 30.48 m semi-permanent hoop house with a plastic film roof, roll-up sidewalls, ventilation fans, and natural light conditions at Texas State University’s experimental farm in San Marcos, Texas (29°56′18.411″ N; 98°0′36.891″ W). The climate of this area is classified as subtropical subhumid mixed prairie, savanna, and woodlands [21].

2.2. Soil, Soil Amendments, and Biofertilizer Analysis

Zucchini plants were grown in a manufactured soil blend, consisting of 50% screened local topsoil, 30% mushroom compost (composed cottonseed meal, cottonseed burrs, brewer’s grains, gypsum, and wheat straw, with the addition of poultry litter), 10% hardwood mulch, and 10% granite sand. The manufactured soil blend was classified as sandy loam, composed of 71% sand, 14% silt, and 15% clay, with 7.6% organic matter (OM). Soil samples were submitted to Regen Ag Lab (Kearny, NE) for analysis using the Haney Soil Health Test (HSHT). The H3A extractant was used to assess the availability of several soil nutrients, including P, NH4-N, NO3-N, Fe, Mn, B, Cu, Zn, Na, S, K, Ca, and Mg. This manufactured soil blend’s Cl concentration was measured using the Ca(NO3)2 extraction method, while the remaining physicochemical and biological indicators were assessed using the Haney Soil Health Test (Table 1). Well water was used to irrigate plants in this study. Well water analysis was conducted by Logan Labs (Lakeview, Ohio).
Humisoil is a soil amendment developed by VRM Biologik® and is produced by aerobic decomposition and fermentation of organic materials. Humisoil in this study was made from 70% woodchips and 30% horse manure, and supplied by a local manufacturer, Bluebonnet Biologicals (Austin, TX, USA). Humisoil’s physicochemical and microbiological characterization is found in Table 1. Wood vinegar, also referred to as pyroligneous acid or liquid smoke, was supplied by British Columbia Biocarbon Ltd. BRD was supplied by Martin Marietta Inc (Dallas, TX, USA). The BRD’s composition included the following percentages: SiO2 (30.50), CaO (15.19), MgO (13.84), Fe2O3 (12.05), Al2O3 (8.13), Na2O (2.59), K2O (1.03), P2O5 (0.7), MnO (0.20), and SO3 (0.12). Wood biochar, produced from softwood pine pyrolyzed at 677 °C and sieved to a particle size of 26–50 mesh, was purchased from Biochar Now, Inc. (Berthoud, CO, USA). This biochar’s characterization was analyzed according to the International Biochar Initiative standards and provided by the manufacturer (Table 1). Ensoil Algae™, a soil-amending biostimulant made from a concentrated medium of living Chlorella vulgaris, was provided by Enlightened Soil Corp (Johns Island, SC, USA).

2.3. Treatments and Experimental Setup

Individual zucchini seedlings (Cucurbita pepo L., cv. ‘Dunja’ (F1)) at the two-true leaf stage were transplanted into 19-L pots (29.21 cm top diameter × 22.23 cm bottom diameter × 27.94 cm height) on 10 March 2025. After transplanting, the pots were watered daily with well water to maintain 80% of soil water holding capacity (SWHC). The SWHC for each treatment was determined by filling each pot with 13 kg of air-dried soil that had been sieved through 1.9 cm mesh. To prevent soil loss, filter fabric was placed at the bottom of the pots. Three pots per treatment were placed in water-filled trays for 24 h, then drained for an additional 24 h until no more water drained from the pots. The tops of the pots were covered with aluminum foil to avoid evaporation. SWHC was calculated using the following formula by Liyanage et al. [22]:
S W H C = W e t   s o i l − A i r − d r i e d   s o i l A i r − d r i e d   s o i l   ×   100
A total of 60 pots were arranged in a randomized complete block design (Figure 1) with 10 replicates (blocks) per treatment, spaced 1.0 m apart. The experiment included six treatments:
  • unamended soil, for which each pot was filled with 13 kg of air-dried soil.
  • soil amended with Humisoil 65 g pot−1 (6.1 t ha−1, equal to a rate of 0.50% w/w), assuming a depth of 15.24 cm and a soil bulk density of 0.80 g cm−3.
  • soil amended with 6.1 t ha−1 Humisoil and biochar 15 g pot−1 (soil equivalent at a rate to 1.4 t ha−1, equal to a rate of 0.12% w/w).
  • soil amended with wood vinegar, at a dose of 1% (v/v).
  • soil amended with EnSoil Algae, at a dose of 5 mL 3.785 L−1 well water.
  • soil amended with 6.1 t ha−1 Humisoil, 1.4 t ha−1 biochar, and air-dried BRD 15 g pot−1 (soil equivalent at a rate to 1.4 t ha−1, equal to a rate of 0.12% w/w).
Humisoil, biochar, and BRD were manually and evenly mixed into the soil and applied only at the beginning of the experiment. The wood vinegar treatment was applied biweekly to minimize interference with soil microbial activity [23]. According to the manufacturer’s recommendations, the Ensoil algae treatment was applied weekly for the first two weeks, then biweekly thereafter. For both treatments, application volumes were adjusted to match the water volume required to maintain 80% SWHC.
In addition to the six treatments applied, organic fertilizers purchased from Advancing Eco Agriculture (Middlefield, OH, USA) were applied to all the pots, at the label-recommended rate (Table S1), adjusted for the specific pot area. The fertilization scheme for all treatments was further adjusted based on the growth stage of the plants, the results of differential plant sap analysis, and the manufacturer’s recommendations.

2.4. Determination of Plant Nutrient Analysis

Differential sap analysis was conducted by pooling leaf blade samples (80 g per treatment), with one composite replicated per treatment. Samples were sent to Nova Crop Control Lab (Oisterwijk, The Netherlands) for analysis according to protocols by Advancing Eco Agriculture (Middlefield, OH, USA). Sampling began 28 days after transplanting (DAT; 7 April 2025) and was repeated on 21 April and on 12 May 2025. Young and old leaf blades were collected between 6:00 am and 9:00 am and packaged separately according to Advancing Eco Agriculture guidelines. The leaf blades were analyzed for various nutrients, including N-NH4, N-NO3, Total N, K, Ca, Mg, Na, Cl, S, P, Si, Fe, Mo, Mn, Zn, B, Cu, and Al, total sugar content, pH, and EC.
Chlorophyll index and N content were measured weekly using a chlorophyll meter (Portable Plant Chlorophyll Analyzer Meter GYJ-C, GOYOJO, Hong Kong, China). Measurements were taken from between the midrib and the leaf margin of three fully expanded leaves per replicate. The average of the three readings was recorded as a single value per replicate.

2.5. Yield and Fruit Quality Analysis

From 11 April to 21 May 2025, fruits were harvested when they reached a marketable length between 15.24 and 20.32 cm, and a maximum diameter of 5.08 cm based on commercial standards for optimal quality [24]. Fruits shorter than 15.24 cm or those that were misshapen were classified as non-marketable [25]. The following yield parameters were recorded: fruit yield, fresh weight of the fruits per plant; mean fruit weight (calculated by dividing the fruit yield by the number of fruits per plant); and number of fruits per plant.
Among key indicators of marketability and postharvest fruit quality are total soluble solids (TSS) and fruit pH. TSS, expressed as °Brix, reflects the sugar concentration and serves as an index of ripeness and sweetness [26]. Fruit pH influences post-harvest quality, with more acidic levels associated with longer shelf life and affecting the degree of sweetness or sourness of a fruit [26]. To assess fruit quality, 10 zucchini fruits were sampled per treatment. The mesocarp, excluding seeds, placenta, and rind, was homogenized using a commercial blender and then squeezed to extract the juice [27,28]. Juice samples were analyzed for TSS at 20 °C, using a digital handheld refractometer (model 3810 Pal-1 Atago Co. Ltd., Tokyo, Japan) Each TSS value recorded per replicate represents the average of three technical readings. Juice pH was measured using a digital pH-meter (Ohaus model a-AB33M1 ZH, Parsippany, NJ, USA).

2.6. Manufactured Soil Analysis

Manufactured soil samples to be analyzed using the HSHT were collected twice: on 10 March 2025, immediately after treatment incorporating, and again after harvest on 21 May 2025. For each treatment, one composite sample was created by homogenizing 20 soil cores collected with a stainless-steel soil core sampling probe (2 cm in diameter and 15.24 cm in depth), following the methodology described by Singh et al. [29]. Each sample was sent to Regen Ag Lab for analysis. The H3A extractant was used to assess the availability of several soil nutrients, including P, NH4-N, NO3-N, Fe, Mn, B, Cu, and Zn, Na, S, K, Ca, and Mg.

2.7. Statistical Analysis

Fruit yield, total soluble solids, and pH data were analyzed using one-way Analysis of Variance (ANOVA), followed by Dunnett’s post hoc test to compare each treatment against the control (T1), using R software version 4.3.3 (PBC, Boston, MA, USA). Levene’s and Shapiro–Wilk tests were run to check for homoscedasticity and normality. When assumptions were not met, the Kruskal–Wallis test was used, followed by the Conover post hoc test with Bonferroni correction. Data from the differential plant sap analysis were analyzed with Friedman’s test, a non-parametric alternative to repeated-measures ANOVA. The Conover test with Bonferroni correction was used for post hoc comparisons. Treatments were designated as grouping variable, while sampling times were considered as blocking factor. Kendall’s tau (τ) correlations were carried out to explore the relationships between the data from the plant sap analysis for young and old leaves, respectively, and plotted heatmaps. The effect of treatments on chlorophyll index and N content was analyzed using linear mixed effect models (packages lme4 and lmerTest) with block as a random effect and both DAT and treatments as fixed effects. Means were compared using the emmeans function (package emmeans), applying the Tukey method to the p values. All statistical analyses were conducted with a p value < 0.05. It is important to note that statistical comparisons among treatments for the manufactured soil health data were not carried out, as individual replicates were pooled into bulk composite samples for each treatment at both the beginning and end of the experiment.

3. Results and Discussion

3.1. Effect of Treatments on Zucchini Growth and Fruit Quality

None of the treatments had any impact on fresh shoot biomass or fruit juice pH (Table 2. These findings align with previous studies that reported no effects on fruit juice pH (6.3–6.6) when vermicompost, phytoregulators, guano-based fertilizer, and arbuscular mycorrhizae were applied under alkaline soil conditions [25,30]. Similarly, the pH values of fruit juice found in this study (Table 2) are within the range of 6.5–6.9 reported for different zucchini genotypes [31]. This slightly acidic pH levels might indicate the potential ability of the treatments to enhance postharvest shelf life, as well as their sweetness degree [26].
In contrast, TSS was significantly affected by the treatments. TSS decreased by 15% in T2 (p < 0.05) and by 13% in T6 (p < 0.1), compared to T1 (Table 2). The highest TSS value in T1 may be attributed to the highest Na and Cl concentrations measured in the leaves of this treatment. Previous studies have demonstrated that increased salinity from NaCl can raise soluble sugar concentrations (e.g., glucose, fructose, and sucrose) or TSS in fruit juice (5.25 °Brix). This effect occurs due to a reduction in fruit weight and water accumulation, resulting in more concentrated sugars in the fruit juice [32,33,34]. In our study, the mean weight of marketable fruit did not differ between T1 and treatments T2 through T6. Therefore, we hypothesize that the high TSS in T1 might be attributed to lower water content in the fruits. Since this parameter was not measured in this study, future research should include measurements of fruit water content to further evaluate this hypothesis.
TSS values exhibited in the T2–T6 treatments (Table 2) fell within the range reported for different zucchini genotypes, which is between 3.4 and 4.6 °Brix [31]. Cardarelli et al. [25] also reported values between 4.27 and 4.32 °Brix when zucchinis were cultivated with guano-based fertilizer and arbuscular mycorrhizae in alkaline soil conditions, which were closer to the values observed in this study. Prior studies have shown that organic amendments and biofertilizers, such as compost, can improve both yield and fruit quality, particularly TSS, compared to conventional fertilizers by improving soil properties [25,35,36]. Conversely, lower TSS values (3.3–4.1 °Brix) were reported when vermicompost or phytoregulators were used under similar soil conditions. These differences may be due to several parameters, including cultivar, crop maturity, moisture content, and soil fertility, all of which are known to affect TSS [31,37].
No significant differences were observed in the chlorophyll index values and N content in leaf samples over time when comparing treatments T2 through T6 to the T1 (Figure 2). Similarly, according to Montemurro et al. [38], no differences were found in the chlorophyll index among zucchinis grown with manure, digestate, or compost for two years under alkaline soil conditions, with readings from 38 to 44. Rekaby et al. [39] also reported no differences in the chlorophyll index, with values ranging from 30 to 40, across zucchinis treated with compost or vermicompost under alkaline conditions at 50 days after seeding. This aligns with the results of our study, where all the treatments exhibited chlorophyll values between 33 and 38 at 53 days after transplanting. In contrast, another study reported chlorophyll index values between 27 and 30 at 15 days after application of compost, biochar, or co-composted biochar, which were lower than those obtained in our study at 22 DAT. The higher chlorophyll values observed in our study across all the treatments might be attributed to the higher percentage of OM of the soil used (7.6%), compared to the low percentage of OM (0.30%) reported in that study. This higher OM content likely releases more nutrients as it degrades and contributed to higher chlorophyll levels at the beginning of our experiment. Conversely, chlorophyll index values in our study were lower at 69 DAT compared to those reported by Cardarelli et al. [25], who obtained values between 40.3 and 42.2 at 61 DAT in zucchinis treated with guano-based fertilizer and arbuscular mycorrhizae. This decline in our study may be related to salinity stress, as excesses of nutrients, such as K, Na, and Cl were detected in the sap analysis data across all treatments. High NaCl concentrations at 54 DAT accelerated leaf senescence and reduced chlorophyll content in zucchini [34]. This effect might be more exacerbated at the end of the experiment, as zucchini plants are more salt-tolerant during germination than vegetative, flowering, or fruit stages of growth [40].

3.2. Effect of Treatments on Fruit Yield Parameters

Total and nonmarketable zucchini yields were significantly affected by the treatments, while the marketable zucchini yield was not significantly affected by the treatments (Table 3). Specifically, treatments T6, T5, T2, and T3 increased the total yield by 107%, 87%, 86%, and 52%, respectively, compared to T1. In terms of non-marketable yield, T5, T6, and T2 enhanced it by 74%, 73%, and 69%, respectively, relative to T1. Regarding the total fruit mean weight, T6, T2, T5, and T3 increased it by 193%, 184%, 108%, and 97%, respectively, compared to T1. Treatments T6 and T5 also increased the non-marketable fruit mean weight by 40% and 35%, respectively, compared to the T1 treatment. For the total number of fruits per plant, treatments T2, T6, and T5 showed significantly better performance by 42%, 37%, and 37%, respectively, compared to T1. T2 also significantly raised the non-marketable number of fruits by 35%, compared to T1.
The improvement in total and non-marketable parameters under treatment T5 may be attributed to the capacity of Chlorella vulgaris to increase OM due to its growth, which adds new OM to the soil tolerance [41]. Minaoui et al. [41] also reported that Chlorella vulgaris might release bioactive compounds and organic N, which are mineralized into inorganic N. These processes improve soil structure, fertility, water retention capacity, and plant stress tolerance [41]. These findings align with the observed increases in OM and the organic N/inorganic N ratio exhibited in the HSHT for the T5-treated plants, despite the limited replication of this study. Therefore, T5 appears to be a promising treatment for improving total yield, mean fruit weight, and fruit number in zucchini grown under alkaline soil conditions, as well as for enhancing certain soil health indicators. However, further research with increased replication or repeated measures over time is needed to confirm the relationship between yield performance and soil health improvements.
The absence of significant differences in the marketable parameters evaluated across all treatments can be attributed to the accumulation of salts in both the soil and the leaves, which resulted in a higher incidence of misshapen fruits being classified as non-marketable.

3.3. Plant Nutrient Concentration

No significant differences were found for most parameters measured in plant sap analysis across treatments, for both young or old leaves, except for Cl and Na concentrations (Table 4). A significant treatment effect was observed for Na in young leaves: T6 decreased Na concentration by 59%, while in old leaves, it decreased by 50%, compared to T1. Similarly, T2 showed a 63% reduction in Na concentration in old leaves compared to T1.
Regarding Cl concentrations in old leaves, treatments T2, and T6, and T4 resulted in significant decreases of 30%, 24% and 16% when compared to T1. The lack of response for most other parameters might be due to the high EC, pH, and excess of Cl, K, Na, NO3, N-NO3, and S concentrations present in both young and old leaves across all treatments (Table 4). These levels exceeded the sufficiency ranges recommended for zucchini by Advancing Eco Agriculture: EC (12.13–13.68 mS cm−1), pH (6.21–6.59), Cl (400–556 ppm), K (4064–4732 ppm), Na (2.3–4.4 ppm), NO3 (10–30 ppm), N–NO3 (4–6 ppm), and S (174–232 ppm). We hypothesize the excessive levels of these parameters in leaves are likely attributed to their high Cl, Na, K, and S concentrations in the soil blend used, specifically poultry litter blended with the mushroom compost (Table 1). The lack of replicates in our soil health sampling limits our ability to confirm the statistical significance of our findings. Further research with increased replication or repeated measurements over time is needed to investigate the relationship between K, Cl, Na, and S concentrations in this manufactured soil and the excessive levels in leaves.
All treatments also exhibited P, Mn, and NH4 deficiencies in both young and old leaves when compared to the sufficiency ranges: P (185–374 ppm), Mn (1.76–3.33 ppm), and NH4 (197–452 ppm). This occurred despite sufficient levels of total, inorganic, and organic P reported by the HSHT, which are considered sufficient for most production systems [42]. Similarly, the observed P and Mn deficiencies may be related to the high soil pH and Ca concentrations across all treatments, stemming from the nutrient composition of the manufactured soil blend used (Table 1). Furthermore, these deficiencies might result from the antagonism between Ca, Cl, and Na with P in young leaves (Figure 3a), or between N– NO3 and NO3 with P, and between K and Cl with Mn in old leaves (Figure 3b). The NH4 deficiencies present in both young and old leaves may also be due to the high Cl concentration in the manufactured soil blend (Table 1), as Cl concentrations > 50 ppm are considered excessive [43]. This was confirmed by the correlograms showing negative correlations between Cl and NH4 (Figure 3) in both young and old leaves.
Additionally, most treatments exhibited Ca concentrations in young leaves, below the sufficiency range (1433–2133 ppm). This might be attributed to antagonistic effects from elevated K and Na concentrations [44] and the low Ca mobility in the phloem. Furthermore, the observed Ca deficiency and excess of Na concentrations may be due to the high concentration of bicarbonates (>90 ppm) in well water used (Table 1). This high bicarbonate concentration can result in the precipitation of Ca and Mg as carbonates and an increase in Na concentration [45]. Even though negative correlations of Ca with K, Cl, Na, and EC weren’t observed in the correlogram for young leaves, it was reflected in the correlogram of old leaves (Figure 3b). This outcome is consistent with the pattern observed in the differential plant sap analysis data, where Na, Cl and EC levels were consistently higher in old leaves than in young leaves.

3.4. Soil Health

Table 5 summarizes soil health indicators that responded to changes between the start and end of the experiment across different treatments. However, no statistical analysis was conducted due to the lack of soil sample replicates. Most treatments showed decreases ranging from 37% to 94% in total N, NO3, NH4, inorganic N, and organic N, except for T2, which increased 55% in organic N. Additionally, the organic N/inorganic N ratio increased across all treatments, with the greatest changes observed in T2 (2310%), T5 (239%), T6 (173%), and T3 (148%). The organic N/inorganic N ratios >2 observed in T2, T3, T5, and T6 indicated a larger organic N pool, which supports more efficient microbial N cycling and plant uptake efficiency [46]. These results align with the organic N levels, which exceeded the general sufficiency range (10–30 ppm) across all treatments, despite decreases observed at the end of the experiment.
The organic C:N ratio remained within the optimal range (8:1 to 15:1), indicating active mineralization of N and P and sufficient nutrient availability [47]. For P, all treatments maintained total organic P, inorganic P, and organic P within standard sufficiency ranges (25–60 ppm, 20–50 ppm, and <10 ppm, respectively). Although P levels declined by 9–44%, these changes were less pronounced than for N forms. However, the mineralization and N and P availability may have been insufficient to prevent P and NH4 deficiencies across all treatments, as indicated by the differential sap analysis (Table 4). This may be due to alkaline conditions that limit the nutrient bioavailability.
The microbial active carbon (MAC) values were <25% at both sampling times, indicating that C availability uptake was not the limiting factor for the low tendency of soil respiration at the end of the experiment, which fell below the optimal range (71–100 ppm). This finding is consistent with the typical range of total organic C (100–300 ppm), which exceeded expectations across treatments, suggesting that the soil’s fertility (rather than energy sources) constrained microbial activity [46].
We hypothesize that the soil’s fertility, specifically nutrient imbalances (Table 5), such as Fe and Zn deficiencies (<20 ppm and <0.5 ppm, respectively) and Na, K, and S excess (>200 ppm, >100 ppm, and >20 ppm, respectively) based on sufficiency ranges for most production systems [42] might contribute to the decrease in % MAC. However, using manufactured alkaline soil and the absence of replicates in HSHT sampling hinder the confirmation of statistical significance and the ability to extrapolate these results to native alkaline soils.
Soil health scores didn’t account for these nutrient imbalances, as all treatments presented soil health scores > 7 in both samplings (Table 5), which are considered good cropland soils [47,48]. Moore et al. [49] also reported soil health scores > 7 in manure-treated soils, despite elevated EC, Na absorption ratio, and excesses of K, Na, and Cl, which led to a decline in aggregate stability. These authors also demonstrated that the soil health scores increased with increasing OM and nutrient content. We hypothesize that the good soil health scores in our treatments and the beginning and end of the experiment might also be due to the manufactured soil’s high OM content (7.6%), which may also hide any treatment effect on soil health. Consequently, further research with increased replication or repeated measures over time is needed to investigate the relationship between soil health scores and increases in organic matter in native soils.
Chu et al. [50] also indicated that the soil health score, calculated solely based on soil biology (CO2-C, water-extractable organic C, and water-extractable organic N), failed to capture treatment effects after 4 years of cover cropping. Additionally, a study conducted in an organic vegetable production field found no differences in weak-acid-extracted nutrients or soil health score among organic farms; conversely, OM was identified as a valuable soil health indicator for detecting differences [51]. These findings align with our study, where the OM showed changes over time, with treatments T2, T5, and T6 increasing by 26%, 19%, and 16%, respectively, compared to the other treatments at the end of the experiment. Therefore, our study highlights the limitations of the HSHT in accounting for nutrient imbalances and underscores the need to identify soil health indicators to evaluate soil amendments under alkaline conditions more accurately, such as N forms, OM, or % MAC trends. Long-term, replicated studies are also necessary to validate these findings and improve the robustness of soil health assessments in diverse production systems.

4. Conclusions

Preliminary findings of this study suggest that Humisoil, Humisoil blended with biochar and BRD, and Ensoil algae may have potential as biostimulants and soil amendments for addressing the environmental challenges of alkaline soils. Their application significantly increased total yield, mean fruit weight, and fruit number, while also enhancing specific soil health indicators, including percent OM and the organic N/inorganic N ratio. However, these results should be interpreted with considerable caution due to the study’s limitations, including the use of manufactured alkaline soil, which differs significantly in physicochemical and biological properties from native alkaline soils. Moreover, the treatments with Humisoil and Humisoil blended with biochar and BRD decreased the excessive levels of Na and Cl in leaves, which may have indirectly improved yield and fruit quality. Nonetheless, their effectiveness may vary depending on soil properties, climate, and feedstock, underscoring the need for further investigation into the interactions between soil health and amendments in the long-term efficacy in native alkaline soils. While all treatments exhibited HSHT scores > 7, which is generally indicative of healthy soils, nutrient imbalances were still observed, including excesses and deficiencies that may have impacted plant nutrition, marketable yield, and microbial activity. This was corroborated by microbial active carbon values < 25%, suggesting that soil fertility was the limiting factor for microbial respiration. The use of manufactured alkaline soil and the lack of replicates in HSHT sampling prevent confirmation of statistical significance for the observed HSHT scores (>7), which suggest healthy soils despite nutrient imbalances or extrapolation to native alkaline soils. Yet, these trends, showing high HSHT scores despite elevated salt levels, are consistent with a previous study that used manure as a soil amendment. Given the limited research on soil amendments and soil health, these preliminary findings are significant for guiding future studies on native alkaline soils. Further research is needed to assess multiple soil health indicators that contribute to high soil health scores while accounting for parameters, such as elevated salt concentrations, that affect crop yield and fruit quality. Long-term studies should also investigate how biostimulants and soil amendments influence soil health, crop yield, fruit quality, and mitigation of salinity stress in native alkaline soils.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agriculture15192078/s1, Table S1: Description of the organic fertilizers applied to all the pots.

Author Contributions

Conceptualization, N.W.; methodology, S.I.-V. and N.W.; software, S.I.-V.; validation, S.I.-V.; formal analysis, S.I.-V.; resources, N.W.; data curation, S.I.-V., R.S. and T.S.; writing—original draft preparation, S.I.-V.; writing—review and editing, N.W. and R.S.; visualization, S.I.-V.; supervision, S.I.-V. and N.W.; project administration, N.W.; funding acquisition, N.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Translational Health Research Center at Texas State University.

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Materials. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest. The funder had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

The following abbreviations are used in this manuscript:
BRDBasaltic rock dust
DATDays after transplanting
ECElectrical conductivity
HSHTHaney Soil Health Test
MACMicrobial activity carbon
MMarketable yield
NMNon-marketable yield
OMOrganic matter
SWHCSoil water holding capacity
TSSsTotal soluble solids
TTotal yield

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Agriculture 15 02078 g001
Figure 1. Experimental layout, which contains 60 pots arranged in a randomized complete block design within a plot area measuring approximately 19 m × 7 m.
Figure 1. Experimental layout, which contains 60 pots arranged in a randomized complete block design within a plot area measuring approximately 19 m × 7 m.
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Agriculture 15 02078 g002
Figure 2. Readings of the (a) chlorophyll index and (b) N content of zucchini leaves measured using a Chlorophyll meter. Error bars represent the standard error (N = 10). ns denotes non-significant differences. The treatments are defined as follows: T1: soil; T2: soil amended with Humisoil; T3: soil amended with Humisoil and biochar; T4: soil amended with wood vinegar; T5: soil amended with Ensoil algae; and T6: soil amended with Humisoil, biochar, and BRD.
Figure 2. Readings of the (a) chlorophyll index and (b) N content of zucchini leaves measured using a Chlorophyll meter. Error bars represent the standard error (N = 10). ns denotes non-significant differences. The treatments are defined as follows: T1: soil; T2: soil amended with Humisoil; T3: soil amended with Humisoil and biochar; T4: soil amended with wood vinegar; T5: soil amended with Ensoil algae; and T6: soil amended with Humisoil, biochar, and BRD.
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Agriculture 15 02078 g003
Figure 3. Kendall correlation between parameters of sap analysis for (a) young and (b) old leaves, respectively. TN, total nitrogen. The symbols *, **, and *** indicate that the differences were significant at p < 0.1, p < 0.05, p < 0.01, and p < 0.001, respectively.
Figure 3. Kendall correlation between parameters of sap analysis for (a) young and (b) old leaves, respectively. TN, total nitrogen. The symbols *, **, and *** indicate that the differences were significant at p < 0.1, p < 0.05, p < 0.01, and p < 0.001, respectively.
Agriculture 15 02078 g003
Table 1. Physicochemical characterization of the soil, well water, and Humisoil and biochar amendments used in this study.
Table 1. Physicochemical characterization of the soil, well water, and Humisoil and biochar amendments used in this study.
ParametersSoil aWell WaterHumisoilBiochar
pH7.47.56.56.65
EC (mmho/cm)3.610.730.230.014
Chloride (ppm)238.5135n.d.brl
Bicarbonate (ppm)n.d.182n.d.n.d.
Nitrate (ppm)1971.3n.d.1.1
NH4 (ppm)1.2n.d.n.d.6.4
Sulfur (ppm)543.34n.d.1142n.d.
Total Phosphorus (ppm)68.8<0.02270023
Calcium (ppm)3388114.412,900n.d.
Magnesium (ppm)24024.9800n.d.
Potassium (ppm)8501.31000n.d.
Sodium (ppm)1700.121100brl
Boron (ppm)n.d.0.0640.93brl
Iron (ppm)11<0.111,42597.9
Manganese (ppm)2.2n.d.112.8615.9
Copper (ppm)0.23n.d.20.250.37
Zinc (ppm)0.19n.d.60.893.8
Aluminum (ppm)7n.d.n.d.n.d.
brl: below the reporting limit, n.d.: not determined. EC: electrical conductivity. a The Cl concentration was measured using the Ca(NO3)2 extraction method, while the remaining physicochemical and biological indicators in the soil’s column were assessed using the Haney Soil Health Test method.
Table 2. Effects of treatments on fresh shoot biomass, total soluble solids (TSS) content, and fruit-juice pH. Values represent the mean of ten replicates.
Table 2. Effects of treatments on fresh shoot biomass, total soluble solids (TSS) content, and fruit-juice pH. Values represent the mean of ten replicates.
TreatmentsFresh Shoot BiomassTSSpH
g Plant−1°Brix
T1303.70 ns5.026.69 ns
T2391.804.26 *6.79
T3376.004.526.67
T4332.504.506.86
T5375.504.436.72
T6359.504.36 •6.74
The symbols • and * indicate that the differences were significant at p < 0.1 and p < 0.05, respectively, while ns denotes non-significant differences. The treatments are defined as follows: T1: soil; T2: soil amended with Humisoil; T3: soil amended with Humisoil and biochar; T4: soil amended with wood vinegar; T5: soil amended with Ensoil algae; and T6: soil amended with Humisoil, biochar, and BRD.
Table 3. Effects of treatments on total (T), marketable (M), and non-marketable (NM) yield, fruit mean weight, and number of fruits of zucchini plants. Values are the mean of ten replicates.
Table 3. Effects of treatments on total (T), marketable (M), and non-marketable (NM) yield, fruit mean weight, and number of fruits of zucchini plants. Values are the mean of ten replicates.
TreatmentYield (g Plant−1)Fruit Mean Weight (g Fuit−1)Fruit (No. Plant−1)
TMNMTMNMTMNM
T1447.60211.00 ns384.3073.16127.83 ns34.8111.501.67 ns11.00
T2895.90 ***244.60651.30 *207.49 ***163.3044.1916.30 **1.5014.80 •
T3734.70 *214.29584.70144.30 *144.0043.5014.701.4313.70
T4518.40155.33471.8067.27112.1733.6213.401.0013.10
T5899.50 ***287.50669.50 *152.05 *131.3946.94 •15.80 *2.1314.10
T6997.40 ***333.40664.00 *214.67 ***165.8748.81 *15.70 *2.1013.60
The symbols •, *, **, and *** indicate that the differences were significant at p < 0.1, p < 0.05, p < 0.01, and p < 0.001, respectively, while ns denotes non-significant differences. The treatments are defined as follows: T1: soil; T2: soil amended with Humisoil; T3: soil amended with Humisoil and biochar; T4: soil amended with wood vinegar; T5: soil amended with Ensoil algae; and T6: soil amended with Humisoil, biochar, and BRD.
Table 4. Effect of treatments on differential plant sap analysis. Data represent the mean of three sampling times of nutrient concentration (ppm), pH, electrical conductivity (EC, mS cm−1), and sugars (%) for both young and old leaves.
Table 4. Effect of treatments on differential plant sap analysis. Data represent the mean of three sampling times of nutrient concentration (ppm), pH, electrical conductivity (EC, mS cm−1), and sugars (%) for both young and old leaves.
TreatmentsT1T2T3T4T5T6T1T2T3T4T5T6
Young LeafOld Leaf
Sugars0.76 ns1.071.271.031.171.130.77 ns0.970.670.870.700.97
pH7.27 ns7.107.077.177.077.037.47 ns7.537.477.437.437.47
EC16.23 ns13.9013.9715.6014.3014.3319.30 ns17.0719.0318.5319.1718.33
K5742.67 ns5551.335374.335348.005760.335376.005949.33 ns5484.675534.005573.005610.335473.33
Ca1392.00 ns1224.671203.001753.671273.001247.331916.67 ns1931.672008.672082.001975.332107.33
K/Ca ratio4.32 ns4.644.803.394.604.433.18 ns2.842.762.692.862.63
Mg898.00 ns717.33664.671157.00739.00630.671290.67 ns1518.001339.001356.331316.331349.33
Na22.009.6710.0019.6711.679.00 *35.6713.33 •23.0029.0029.0017.67 •
NH472.33 ns85.3377.0058.0069.3397.3362.67 ns64.6758.3367.0052.0081.33
NO3939.67 ns721.33821.67597.00513.331132.001259.00 ns823.672047.331752.331289.001879.00
N-NO3212.00 ns163.00185.67134.67116.00255.33284.00 ns186.00462.00395.67291.00424.33
N-TN1255.00 ns1337.331632.331222.331364.001615.331350.67 ns1223.331432.331447.671095.671355.67
Cl2887.00 ns1603.001955.002819.001769.672005.674784.333372.00 **4030.334033.67 •4695.003637.00 **
S324.67 ns301.67315.67454.00320.33286.00464.00 ns521.00565.33534.33431.00425.33
P131.67 ns179.00178.33124.67183.33166.3368.00 ns71.6754.0063.6754.3360.33
Si64.70 ns64.2054.6358.5760.4758.9760.23 ns64.6366.9757.1364.3061.67
Fe1.18 ns1.751.511.862.261.481.41 ns1.881.571.631.391.51
Mn1.01 ns0.980.901.371.050.931.28 ns1.591.461.501.341.50
Zn8.53 ns8.479.039.838.987.878.39 ns8.506.948.325.747.80
B 5.13 ns5.524.717.664.723.676.90 ns10.67.268.426.917.58
Cu1.52 ns1.541.701.681.801.661.35 ns1.441.341.351.181.24
Mo0.37 ns0.280.310.540.310.240.59 ns0.740.610.610.520.56
Al0.13 ns0.090.180.170.210.100.16 ns0.170.160.150.170.17
Co0.26 ns0.120.160.360.080.080.40 ns0.480.460.420.410.44
The symbols •, *, and ** indicate that the differences were significant at p < 0.1, p < 0.05, and p < 0.01, respectively, between treatments and control (T1) for young or old leaves based on Friedman test followed by Conover test. ns denotes non-significant differences. The treatments are defined as follows: T1: soil; T2: soil amended with Humisoil; T3: soil amended with Humisoil and biochar; T4: soil amended with wood vinegar; T5: soil amended with Ensoil algae; and T6: soil amended with Humisoil, biochar, and BRD.
Table 5. Effect of treatments on soil health based on Haney soil health test. These data represent a single composite sample per treatment, obtained by combining the ten individual replicates.
Table 5. Effect of treatments on soil health based on Haney soil health test. These data represent a single composite sample per treatment, obtained by combining the ten individual replicates.
TreatmentsT1T2T3T4T5T6T1T2T3T4T5T6
SamplingAt StartAt End
OM6.405.406.406.305.406.106.906.806.606.706.407.10
CO2-C78.0682.1667.3154.0172.5345.7453.7547.1066.3351.3046.0762.22
Total N a330.48219.60313.86393.53363.93310.10143.1487.64130.86136.75100.2696.28
Organic N a151.5849.43138.06183.33170.23128.1091.6976.6786.6982.5975.1063.17
Total Organic C a1414.51582.581120.511186.461354.841113.6876.32772.67821.09703.22708.40622.43
NO3 b169.00164.00167.00199.00185.00173.0049.609.0442.4052.2023.4031.20
NH4 b11.907.3710.7017.5010.5010.702.712.822.502.552.752.56
Inorganic N b180.90171.37177.70216.50195.50183.7052.3111.8644.954.7526.1533.76
Total P b51.6653.4459.5850.7857.8358.945.0148.5151.1541.4444.6951.27
Inorganic P b45.9048.9051.4046.3050.6051.6041.5044.5046.6038.5042.145.7
Organic P b5.764.548.184.487.237.303.514.014.552.942.595.57
K b1196.35930.261083.721158.361210.671009.22861.49506.12714.31681.09587.14614.53
Ca b3756.693514.633739.863870.813969.933661.993339.623189.173451.293127.763201.333256.26
S b956.74873.18825.40939.00990.00795.91713.76547.85835.66456.42568.86706.71
Na b257.87183.91212.78259.59258.01204.15280.87190.69280.64223.5207.08215.47
Mn b2.742.402.542.982.812.502.022.092.002.072.112.04
% MAC5.5214.106.014.555.354.116.136.108.087.306.5010.00
Organic C: N a9.3311.798.126.477.968.699.5610.089.478.519.439.85
Organic N: Inorganic N a0.850.290.790.870.880.701.786.991.961.522.981.91
Soil health score51.2524.8142.9547.4651.3739.6632.0727.8331.7227.4526.2924.99
a Water-extraction method; b H3A-extraction method. MAC: microbial active carbon. OM: organic matter. The treatments are defined as follows: T1: soil; T2: soil amended with Humisoil; T3: soil amended with Humisoil and biochar; T4: soil amended with wood vinegar; T5: soil amended with Ensoil algae; and T6: soil amended with Humisoil, biochar, and BRD.
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Islas-Valdez, S.; Sproull, R.; Sumners, T.; Wagner, N. Effect of Organic Amendments and Biostimulants on Zucchini Yield and Fruit Quality Under Alkaline Conditions. Agriculture 2025, 15, 2078. https://doi.org/10.3390/agriculture15192078

AMA Style

Islas-Valdez S, Sproull R, Sumners T, Wagner N. Effect of Organic Amendments and Biostimulants on Zucchini Yield and Fruit Quality Under Alkaline Conditions. Agriculture. 2025; 15(19):2078. https://doi.org/10.3390/agriculture15192078

Chicago/Turabian Style

Islas-Valdez, Samira, Reagan Sproull, Ty Sumners, and Nicole Wagner. 2025. "Effect of Organic Amendments and Biostimulants on Zucchini Yield and Fruit Quality Under Alkaline Conditions" Agriculture 15, no. 19: 2078. https://doi.org/10.3390/agriculture15192078

APA Style

Islas-Valdez, S., Sproull, R., Sumners, T., & Wagner, N. (2025). Effect of Organic Amendments and Biostimulants on Zucchini Yield and Fruit Quality Under Alkaline Conditions. Agriculture, 15(19), 2078. https://doi.org/10.3390/agriculture15192078

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