Residual Impacts of Vermicompost-Derived Nutrients on a Strawberry–Corn Double Cropping System Under Plasticulture in South Florida

Abstract

The increasing demand for sustainable agricultural practices necessitates strategies such as organic fertilizer alternatives and residual nutrient use to enhance crop productivity while maintaining soil health. This study investigates the residual effects of vermicompost on strawberry growth and physiology after a corn cropping cycle. The objectives were to assess how different vermicompost application rates impact strawberry yield, biomass, chlorophyll content, and fruit quality. The experiment was conducted over six months, using raised beds previously cultivated with corn and treated with six nutrient management strategies, namely, V0 (control), VC1, VCT100, VC1+VCT50, VC3, and VC3+VCT50. Metrics such as SPAD values, Brix sugar content, and stomatal conductance were measured throughout the growing season to assess physiological responses. Soil and plant chemical concentrations were determined at the end of the study to evaluate nutrient status. Results showed that the VC1 treatment produced the highest yield (11,573 kg/acre) and biomass (38,364 kg/acre), with significantly improved fruit quality (Brix sugar content of 8.3%) compared to the control (6.8%). SPAD values declined over time and showed no statistically significant differences among treatments. In the surface soil, VC3+VCT50 exhibited the highest N, P, Mg, Na, organic matter, and cation exchange capacity (CEC), and it also resulted in the highest leaf N. Leaves had higher N, P, K, and Mg concentrations, while Fe, Mn, and Cu were more concentrated in roots. Spectral reflectance data indicated reduced chlorophyll content in the VC3+VCT50-treated plants. These findings suggest that moderate vermicompost applications, such as VC1, can significantly contribute to sustainable agriculture by enhancing strawberry productivity and reducing dependence on synthetic fertilizers. However, high-rate applications, especially VC3 and VC3+VCT50, reduced plant vigor and yield, possibly due to salinity stress and the high sodium content in the vermicompost used in this study. Such outcomes may vary depending on feedstock composition, highlighting the importance of salinity screening when using organic amendments in salt-sensitive crops like strawberries.

1. Introduction

Strawberry (Fragaria ananassa) is one of the most economically significant fruit crops globally, with production exceeding 9 million metric tons in 2022 [1]. Major producers include China, the United States, Mexico, and Turkey, with the U.S. contributing over 1.3 million tons annually, generating approximately USD 3.42 billion in economic value [2,3]. California dominates national production in the U.S., but Florida ranks second, cultivating strawberries on 10,000 to 12,000 acres annually, with a market value exceeding USD 500 million [4]. The fruit’s high market demand stems from its nutritional benefits, including high antioxidant content, making it a consumer favorite worldwide [5]. While most production is concentrated in Central Florida, South Florida, including Miami-Dade County, is emerging as a valuable region due to its subtropical climate and unique winter growing window [6]. However, production here remains small-scale and understudied despite increasing interest in local markets and organic production systems.

Despite its economic value, strawberry cultivation is highly input-intensive and vulnerable to various pests and diseases. In Florida, strawberries are predominantly grown using raised-bed plasticulture with drip irrigation, requiring frequent pesticide applications to combat pests such as the two-spotted spider mite (Tetranychus urticae), fall armyworm (Spodoptera frugiperda), southern armyworm (Spodoptera eridania), aphids, and thrips [7,8]. The phase-out of methyl bromide soil fumigant has increased reliance on chemical pesticides, leading to resistance development and environmental concerns [9]. Over 63 pesticide products are registered for strawberry cultivation [10], and nearly 70% of market strawberries have been found to carry over 20 different pesticide residues [11], placing them consistently at the top of the “Dirty Dozen” list for several years [12]. These challenges have driven interest in organic management strategies, including using organic soil amendments that enhance fertility and improve pest and disease resilience. In South Florida, the challenge is compounded by unique agronomic conditions such as calcareous, shallow soils with low organic matter, high rainfall variability, and elevated temperatures, which affect nutrient availability and pest dynamics. These site-specific challenges show the need for regionally tailored nutrient and pest management approaches that support long-term sustainability.

Vermicompost (VC), often referred to as “black gold,” is a nutrient-rich organic amendment produced through the microbial decomposition of organic waste by earthworms [13]. Its aqueous derivative, vermicompost tea (VCT), is prepared by steeping VC in water under aerated or non-aerated conditions to extract soluble nutrients and beneficial microbes [14]. VC is rich in essential nutrients, beneficial microbes, phytohormones, and phenolic acids that can enhance plant growth and suppress soilborne pests and pathogens [14,15]. Recent studies have also highlighted the role of vermicompost in disease suppression and plant health promotion in various crops [16]. VCT, commonly applied as a foliar spray, provides similar benefits in a liquid form. The VC functions as a slow-release nutrient source, while VCT provides readily available plant nutrients, improving soil structure and biological activity while minimizing leaching [13,17]. While several studies have documented the short-term benefits of VC and VCT on strawberries [18,19], little is known about their effectiveness when applied during a preceding crop cycle, such as corn, a heavy nutrient feeder. This raises important questions about whether residual nutrients from organic amendments such as VC and VCT, which are applied to a preceding crop like corn, can support strawberry yield, fruit quality, and nutrient availability in a subsequent rotation in regions like South Florida, where input efficiency and pest suppression are critical.

Incorporating strawberries after corn can improve soil health and promote pest management in crop rotation. Corn is typically rotated with crops like soybeans, peas, wheat, and beans [20,21], replenishing nitrogen levels in the soil, while strawberries are usually rotated with peas, beans, and leafy greens [22,23]. Introducing strawberries into corn rotation can help break pest and disease cycles, as strawberries are not closely related to corn and share one or two common pests or diseases. However, the residual nutrient effects of VC and VCT on strawberry yield and physiology following corn cultivation have not been quantified in subtropical cropping systems.

This study addresses these gaps by evaluating the residual impacts of VC and VCT applied during a corn-growing season on the subsequent growth and nutrient performance of strawberries grown without additional fertilization within a real field rotation context. Specifically, this study aimed to (1) assess the effects of residual VC and VCT treatments on strawberry morphological traits and physiological responses; (2) quantify macro- and micronutrient concentrations in soil and plant tissues to determine the extent of nutrient carryover from the previous crop season; and (3) evaluate treatment-induced differences in fruit quality, particularly Brix sugar content, as a proxy for marketable quality under organic management.

While strawberry–corn rotation is not widely practiced, the experimental design allowed for assessing the residual impacts of organic inputs across growing seasons. These findings offer broader implications for agricultural systems incorporating organic nutrient sources, managing salinity risks, and reducing dependence on synthetic fertilizers in high-value horticultural crops.

2. Methodology

2.1. Experimental Setup

This study was conducted at the organic garden (1.5 acres) of the Agroecology Program, Department of Earth and Environment, Florida International University, Miami, FL, USA (25.7539281, −80.3800388). The site is characterized by calcareous sandy loam soils with a history of organic management under the USDA People’s Garden Initiative [24]. This research served as a follow-up to a previous corn experiment [25], exactly one month after the experiment concluded, using the same six raised beds (457 × 30 × 91 cm, L × W × H). The aim was to evaluate the residual effects of prior VC treatments on strawberry growth without any additional fertilizer inputs. Treatments applied during the preceding corn experiment were as follows: V0 (control—The Old Farmer’s Almanac organic fertilizer with NPK percentage of 8-4-8, applied twice at a rate of 0.3 ton/acre); VC1 (vermicompost at 1 ton/acre); VCT100 (vermicompost tea, 100 mL per plant); VC1+VCT50 (vermicompost 1 ton/acre and vermicompost tea, 50 mL per plant); VC3 (vermicompost 3 ton/acre), and VC3+VCT50 (vermicompost 3 ton/acre and vermicompost tea, 50 mL per plant). The VC and VCT were sourced from Lions Fruit Farm, Redlands, Miami, FL, using rabbit manure, fruit waste (e.g., avocado), and cocoplum as feedstock. VC and VCT preparation details are described in [25]. Soil nutrient content following the corn harvest and before strawberry planting is summarized in Table 1, derived from the same study (Table 2 in [25]), to contextualize nutrient availability at the start of the strawberry trial. The nutrient composition of the VC used in the preceding corn study, whose residues were evaluated here, is detailed in [25], including total N, P, K, and Na levels.

Beds were covered with cloth mulch, and each was planted with 12 Chandler bare-root strawberry plants (sourced from Willis Orchards, Cartersville, GA, USA) in November 2022. To ensure consistent replication across treatments, the strawberry plants in each raised bed were grouped into three replicates by dividing the 12 plants into three sets of four. These plant-based replicates were used for biomass and nutrient analysis within each treatment. The experiment lasted six months, ending in April 2023. Throughout the strawberry growing season, beds were irrigated manually using a hand-held sprinkler every evening to ensure uniform moisture coverage across each raised bed. Watering was skipped on days when rainfall occurred. The weather data of the study area during the strawberry growing season (November 2022 to April 2023) were obtained from the National Oceanic and Atmospheric Administration (NOAA, https://www.weather.gov/wrh/Climate?wfo=mfl accessed on 15 May 2025). Monthly average temperatures ranged from 22.3 °C in January to 26.3 °C in April. The precipitation was low with values of 7.1 mm (November 2022), 1.5 mm (December 2022), 0 mm (January 2023), 5.1 mm (February 2023), 3.8 mm (March 2023), and 8.4 mm (April 2023).

2.2. Strawberries Physiology

Physiological measurements were taken weekly between weeks 10 and 24 after transplanting, corresponding to Chandler strawberry’s vegetative stage, flowering, and early fruit development stages in subtropical climates. These time points were selected to capture changes in chlorophyll content, water use efficiency, and canopy development during peak physiological activity. The relative chlorophyll content was determined using a Soil-Plant Analysis Development chlorophyll meter (SPAD 502 plus, Spectrum Technologies Inc., Aurora, IL, USA) from weeks 10 to 24 after planting. The stomatal conductivity of the strawberries was measured using a porometer and fluorometer (Li-600, LI-COR Environmental, Lincoln, NE, USA) from week 10 to week 24. The SPAD readings and stomatal conductance were taken from five mature leaves (at the mid-height of the plant) per plant between 8:30 am and 10:30 am to reduce diurnal variations. Leaf-level (five leaves per plant, four plants per replicate) and canopy-level (three plants per replicate) spectral reflectance of the strawberries was taken in week 17 at 11:00 am using a hand-held spectral radiometer (Spectral Evolution Inc., Haverhill, MA, USA) across the 350–2500 nm.

2.3. Strawberry Harvesting and Yield Determination

The strawberry fruits were harvested continuously throughout the experimental period from November 2022 to April 2023, coinciding with the typical fruiting window for Chandler strawberries in subtropical climates. Harvesting was performed manually on multiple dates as fruits reached full ripeness (entirely red). Only marketable-quality fruits free from deformities, pest damage, or disease symptoms were collected and included in the yield analysis. Treatments VC3 and VC3+VCT50 were excluded from the yield data due to insufficient production of marketable fruits.

The fresh weight of harvested strawberries was recorded immediately after harvest using a digital balance (precision ± 0.01 g). This approach reflects commercial practices, where strawberries are sold fresh. Brix sugar content was also measured immediately upon harvest using a hand-held Brix digital pocket refractometer (Atago Co., Ltd., Bellevue, WA, USA) to ensure accuracy, and the sugar content was compared with organic strawberries purchased from the grocery store (Publix, Miami, FL, USA). The total yield per treatment was calculated by summing the cumulative fresh fruit weight collected across all harvests. The yield was then expressed per acre (kg/acre) by scaling the total fruit mass to the area of the raised beds used in each treatment using the following equation:

$$Yield in \mathrm{kg} \mathrm{per} \mathrm{acre}={\displaystyle \frac{Total yield from plot in \mathrm{k}\mathrm{g}}{Area of the plot in {\mathrm{m}}^2}}\times 4046.86$$

2.4. Plant and Soil Sampling and Chemical Analysis

At the termination of the experiment (end of April 2023), despite ongoing fruiting, plants were uprooted, and biomass (shoots and roots) was harvested for final biomass determination. Strawberry plants were at the late reproductive stage, characterized by ongoing fruit production and senescence of early leaves. Fresh biomass per bed was weighed immediately after uprooting the plants. From this, representative subsamples were collected for laboratory analysis. These subsamples were carefully washed with clean water to remove soil and debris, particularly from the roots. The cleaned subsamples were oven-dried at 70 °C until constant weight to determine dry biomass. Once dried, the roots were manually separated from the shoot tissue. Both roots and leaves were then ground separately into a fine powder using a Mixer/Mill (SPEX Sample Prep, Metuchen, NJ, USA). The resulting ground root and leaf samples were analyzed for nutrient content following the procedure previously described in [25]. Briefly, the total carbon and total nitrogen content in the leaves and root samples were determined using dry combustion with a C/N elemental analyzer (LECO TruSpec, LECO Corporation, St. Joseph, MI, USA).

The elemental concentrations of Ca, K, Mg, P, S, B, Fe, Mn, Zn, and Cu were determined using Inductively Coupled Plasma Mass Spectroscopy (ICP-MS; Agilent 7900, Santa Clara, CA, USA). The powdered plant samples were digested using a standard acid digestion procedure, using concentrated nitric acid, to solubilize macro- and micronutrients. Quantification was performed using multi-element calibration standards, and quality control was maintained using reagent blanks and certified reference materials. Elemental concentrations were expressed in mg/kg or ppm (parts per million) dry weight.

Furthermore, the soil samples from all 12 plants were collected from two depths, that is, 0–10 cm (surface soils) and 10–20 cm (subsurface soils), and pooled to make three soil samples per bed per depth. The soil samples and background soil collected just before planting strawberries were air-dried and sieved through a 2 mm mesh and analyzed for nutrient and elemental concentrations [25]. The soil pH was determined in CaCl₂ solution, CEC was determined using unbuffered 1 M NH₄Cl, and organic matter was determined by the loss-on-ignition method. Total nitrogen in the soil was measured using the same C/N elemental analyzer. At the same time, P, K, Ca, Mg, Zn, and Na concentrations were determined using the same ICP-MS procedure for plant samples.

2.5. Statistical Analysis

All data collected in the study were analyzed using Minitab (version 21, Minitab LLC, State College, PA, USA) at a 5% significance level. A one-way analysis of variance (ANOVA) was conducted to evaluate the effect of different treatments on soil and plant parameters. For each parameter, ANOVA was first used to test whether there were significant differences among treatment means (p < 0.05). A post hoc test (Tukey’s Honestly Significant Difference (HSD)) was performed to separate treatment means only when ANOVA indicated a significant difference. All assumptions for ANOVA, including normality and homogeneity of variances, were checked before conducting the analyses.

3. Results

3.1. Soil Chemical Characteristics

We assessed soil nutrients in the surface (0–10 cm) and subsurface (10–20 cm) layers after corn harvest and strawberry planting to understand residual fertility. The data (see Table 1, adapted from [25]) showed significant treatment effects, with VC3+VCT50 showing significantly higher N, P, Mg, organic matter (OM), Na, and cation exchange capacity (CEC) in surface soils compared to most of the treatments (p < 0.05). Treatments VC1 and VC3 also showed enriched nutrient profiles compared to the control, although to a lesser extent. Nutrient levels in the subsurface layers were generally lower, but VC3 maintained higher N and Ca levels. Furthermore, nutrient levels were generally lower in the subsurface layer (10–20 cm). However, VC3 and VC3+VCT50 exhibited significantly greater %OM and %C than VC1. Despite these differences, CEC values in subsurface soils did not differ significantly among treatments. These nutrient patterns showed that VC and VCT applications from the prior corn cycle left enough nutrient residues to influence subsequent strawberry growth; this nutrient carryover effect was explored in the current strawberry-focused results. Moreover, the high CEC observed under VC3+VCT50 treatment suggests enhanced soil capacity to retain water and nutrients, which is especially advantageous in organic systems with limited fertilizer inputs.

Table 1. Post-harvest soil nutrient concentrations at two depths (0–10 cm and 10–20 cm) following corn cultivation under different vermicompost (VC) and vermicompost tea (VCT) treatments. Data were extracted and adapted from [25] to illustrate residual soil fertility before strawberry planting.

Treatment	pH	N * (%)	P * (ppm)	K * (ppm)	Ca (ppm)	Mg * (ppm)	Zn (ppm)	Na * (ppm)	OM * (%)	CEC (cmol/kg)	C * (%)
Surface soils (0–10 cm)
V0	7.9	0.79 a	286 a	181 a	2717	742 ab	15.1	50.6 b	25.9	20.3	14.6
VC1	8.0	0.63 b	247 c	161 b	2640	716 ab	14.9	48.0 bc	20.8	19.6	11.7
VCT100	8.0	0.63 b	209 d	165 b	2735	692 b	13.9	50.5 b	22.3	19.9	12.5
VC1+VCT50	8.0	0.63 b	205 d	118 c	2661	620 c	13.0	45.7 c	22.5	18.8	12.6
VC3	8.0	0.65 b	268 b	123 c	2549	744 ab	14.1	48.3 bc	21.4	19.3	12.0
VC3+VCT50	8.0	0.72 ab	289 a	185 a	2637	757 a	15.3	75.5 a	23.6	20.0	13.2
Subsurface soils (10–20 cm)
V0	8.1	0.48 bc	117 b	279 a	2345	545 ab	10.9	41.9 b	18.9 ab	17.0	10.6 ab
VC1	8.1	0.47 c	132 a	219 b	2346	543 ab	11.3	43.4 b	17.6 b	16.8	9.9 b
VCT100	8.1	0.41 c	74.8 d	196 b	2314	403 c	10.4	44.6 b	18.7 ab	15.4	10.5 ab
VC1+VCT50	8.1	0.49 bc	99.4 c	140 c	2345	486 bc	10.7	40.9 b	19.4 ab	16.1	10.9 ab
VC3	8.1	0.54 ab	119 b	87.1 d	2372	589 a	8.2	45.7 b	23.0 a	17.0	12.9 a
VC3+VCT50	8.1	0.60 a	114 b	152 c	2326	578 ab	10.0	154 a	22.8 a	16.8	12.8 a

Nutrient concentrations are presented on a dry weight basis. The elements with an asterisk (*) are statistically significant. Means that do not share a letter differ significantly (p < 0.05).

Table 1. Post-harvest soil nutrient concentrations at two depths (0–10 cm and 10–20 cm) following corn cultivation under different vermicompost (VC) and vermicompost tea (VCT) treatments. Data were extracted and adapted from [25] to illustrate residual soil fertility before strawberry planting.

Treatment	pH	N * (%)	P * (ppm)	K * (ppm)	Ca (ppm)	Mg * (ppm)	Zn (ppm)	Na * (ppm)	OM * (%)	CEC (cmol/kg)	C * (%)
Surface soils (0–10 cm)
V0	7.9	0.79 a	286 a	181 a	2717	742 ab	15.1	50.6 b	25.9	20.3	14.6
VC1	8.0	0.63 b	247 c	161 b	2640	716 ab	14.9	48.0 bc	20.8	19.6	11.7
VCT100	8.0	0.63 b	209 d	165 b	2735	692 b	13.9	50.5 b	22.3	19.9	12.5
VC1+VCT50	8.0	0.63 b	205 d	118 c	2661	620 c	13.0	45.7 c	22.5	18.8	12.6
VC3	8.0	0.65 b	268 b	123 c	2549	744 ab	14.1	48.3 bc	21.4	19.3	12.0
VC3+VCT50	8.0	0.72 ab	289 a	185 a	2637	757 a	15.3	75.5 a	23.6	20.0	13.2
Subsurface soils (10–20 cm)
V0	8.1	0.48 bc	117 b	279 a	2345	545 ab	10.9	41.9 b	18.9 ab	17.0	10.6 ab
VC1	8.1	0.47 c	132 a	219 b	2346	543 ab	11.3	43.4 b	17.6 b	16.8	9.9 b
VCT100	8.1	0.41 c	74.8 d	196 b	2314	403 c	10.4	44.6 b	18.7 ab	15.4	10.5 ab
VC1+VCT50	8.1	0.49 bc	99.4 c	140 c	2345	486 bc	10.7	40.9 b	19.4 ab	16.1	10.9 ab
VC3	8.1	0.54 ab	119 b	87.1 d	2372	589 a	8.2	45.7 b	23.0 a	17.0	12.9 a
VC3+VCT50	8.1	0.60 a	114 b	152 c	2326	578 ab	10.0	154 a	22.8 a	16.8	12.8 a

Nutrient concentrations are presented on a dry weight basis. The elements with an asterisk (*) are statistically significant. Means that do not share a letter differ significantly (p < 0.05).

Table 2 presents the nutrient content in the post-harvest soils of strawberries at both surface and subsurface depths across the different treatment groups. Significant increases in soil concentrations of N, P, Ca, Mg, Na, organic matter, and CEC were observed among all the treatments, with increases in VC and VCT concentrations in both surface and subsurface soils (Table 2). The pH, K, and Zn concentrations in the surface and subsurface soils were unaffected by the increased VC and VCT concentrations. The high VC application rates (VC3 and VC3+VCT50) generally exhibited higher soil nutrient content, while VC1+VCT50 exhibited the lowest nutrient concentration (Table 2). Furthermore, the N levels were significantly higher across all treatments compared to P and K in the surface and subsurface soils.

In the surface depth (0–10 cm), pH was relatively consistent across all treatments, ranging from 7.6 to 8.0. The VC3+VCT50 treatment exhibited the highest N content (0.81%), which was more significant than the other treatments, except VC3. It was observed that high VC rate (VC3 and VC3+VCT50) treatments contained more N compared to those with 1 ton/acre (VC1). Similar findings were made for P and Mg, where P levels were significantly higher in the VC3 treatment, with 216 ppm, significantly higher than VC1+VCT50 (94 ppm). VC3+VCT50 had significantly higher Mg content (648 ppm) than VC1+VCT50 (435 ppm). The highest Na content was found in the VC3+VCT50 treatment (67.8 ppm), which was significantly higher than the control group V0 (61.9 ppm) (Table 2). VC3+VCT50 resulted in 29% and 13% higher OM content and CEC in surface soils compared to the control (Table 2).

Table 2. Post-harvest soil nutrient content at two depths (surface and subsurface) after strawberry cultivation.

Treatment	pH	N * (%)	P * (%)	K (%)	Ca * (%)	Mg * (%)	Zn (ppm)	Na * (ppm)	OM * (%)	CEC *
Surface soils (0–10 cm)
V0	8.0	0.59 bc	0.013 ab	0.009	0.30	0.05 abc	10.2	61.9 b	22.6 b	19.5 ab
VC1	7.6	0.61 bc	0.014 ab	0.009	0.34	0.05 bc	9.8	63.0 ab	24.9 ab	20.8 ab
VCT100	7.6	0.57 bc	0.013 ab	0.007	0.31	0.04 bc	9.5	65.2 ab	23.5 b	19.7 ab
VC1+VCT50	7.9	0.47 c	0.0094 b	0.007	0.29	0.04 c	11.6	66.9 ab	22.2 b	18.2 b
VC3	7.6	0.71 ab	0.022 a	0.009	0.34	0.06 ab	12.2	67.7 ab	26.1 ab	22.3 a
VC3+VCT50	7.8	0.81 a	0.020 ab	0.009	0.32	0.06 a	11.4	67.8 a	29.2 a	22.1 a
Subsurface soils (10–20 cm)
V0	7.8	0.49 abc	0.008	0.006	0.27 ab	0.05 ab	7.2	61.3	22.2 b	17.6 ab
VC1	7.9	0.49 abc	0.008	0.006	0.29 a	0.05 ab	7.5	63.4	22.2 b	18.6 ab
VCT100	8.1	0.48 bc	0.007	0.006	0.30 a	0.05 ab	8.3	63.6	21.4 b	18.8 a
VC1+VCT50	8.0	0.44 c	0.006	0.004	0.26 b	0.04 b	8.1	61.0	22.7 ab	16.6 b
VC3	8.0	0.60 a	0.100	0.006	0.29 a	0.05 a	7.7	62.7	25.0 a	19.2 a
VC3+VCT50	8.0	0.59 ab	0.010	0.0066	0.30 a	0.06 a	8.3	66.6	24.8 a	19.5 a

Nutrient concentrations are presented on a dry weight basis. The elements with an asterisk (*) are statistically significant. Means that do not share a letter are significantly different.

Table 2. Post-harvest soil nutrient content at two depths (surface and subsurface) after strawberry cultivation.

Treatment	pH	N * (%)	P * (%)	K (%)	Ca * (%)	Mg * (%)	Zn (ppm)	Na * (ppm)	OM * (%)	CEC *
Surface soils (0–10 cm)
V0	8.0	0.59 bc	0.013 ab	0.009	0.30	0.05 abc	10.2	61.9 b	22.6 b	19.5 ab
VC1	7.6	0.61 bc	0.014 ab	0.009	0.34	0.05 bc	9.8	63.0 ab	24.9 ab	20.8 ab
VCT100	7.6	0.57 bc	0.013 ab	0.007	0.31	0.04 bc	9.5	65.2 ab	23.5 b	19.7 ab
VC1+VCT50	7.9	0.47 c	0.0094 b	0.007	0.29	0.04 c	11.6	66.9 ab	22.2 b	18.2 b
VC3	7.6	0.71 ab	0.022 a	0.009	0.34	0.06 ab	12.2	67.7 ab	26.1 ab	22.3 a
VC3+VCT50	7.8	0.81 a	0.020 ab	0.009	0.32	0.06 a	11.4	67.8 a	29.2 a	22.1 a
Subsurface soils (10–20 cm)
V0	7.8	0.49 abc	0.008	0.006	0.27 ab	0.05 ab	7.2	61.3	22.2 b	17.6 ab
VC1	7.9	0.49 abc	0.008	0.006	0.29 a	0.05 ab	7.5	63.4	22.2 b	18.6 ab
VCT100	8.1	0.48 bc	0.007	0.006	0.30 a	0.05 ab	8.3	63.6	21.4 b	18.8 a
VC1+VCT50	8.0	0.44 c	0.006	0.004	0.26 b	0.04 b	8.1	61.0	22.7 ab	16.6 b
VC3	8.0	0.60 a	0.100	0.006	0.29 a	0.05 a	7.7	62.7	25.0 a	19.2 a
VC3+VCT50	8.0	0.59 ab	0.010	0.0066	0.30 a	0.06 a	8.3	66.6	24.8 a	19.5 a

Nutrient concentrations are presented on a dry weight basis. The elements with an asterisk (*) are statistically significant. Means that do not share a letter are significantly different.

In the subsurface soils (10–20 cm), the highest N content was observed in the VC3 treatment (0.60%), which was significantly higher than the VC1+VCT50 treatment (0.44%). All treatments except for the control (V0) had significantly higher Ca content and CEC than VC1+VCT50. A similar trend was observed in Mg content, where VC1+VCT50 had significantly lower Mg content than the VC3 and VC3+VCT50 treatments. Furthermore, except for VC1+VCT50, the OM content was significantly higher in VC3 and VC3+VCT50 compared to the rest of the treatments. Moreover, the results show that the nutrient levels were generally higher in the surface soil samples than in the subsurface soil samples (Table 2). In addition, VC3+VCT50 had significantly higher N content in the surface soil samples than in the subsurface soil samples.

3.2. Plant Chemical Concentrations

The findings show interesting variations of nutrient content in both leaves and roots (

Table 3. Nutrient content in strawberry leaves and roots.

Treatment	N * (%)	P * (%)	K * (%)	Ca (%)	Mg * (%)	S (%)	B (ppm)	Fe * (ppm)	Mn * (ppm)	Zn (ppm)	Cu * (ppm)
Leaves
V0	1.83	0.28	1.72 ab	2.26	0.46	0.08	27.5	96 b	16.6	15.2	6.0
VC1	1.75	0.26	1.96 a	2.31	0.42	0.08	28.5	88 b	16.6	14.7	5.9
VCT100	1.67	0.24	1.32 ab	2.08	0.36	0.07	26.2	114 b	17.6	15.0	5.7
VC1+VCT50	1.60	0.26	1.20 b	2.28	0.37	0.07	25.5	138 ab	17.7	16.4	5.6
VC3	1.82	0.22	0.96 b	1.87	0.29	0.06	21.3	248 a	19.4	20.2	5.6
VC3+VCT50	1.89	0.28	0.93 b	1.99	0.39	0.06	22.1	160 ab	20.6	20.3	5.6
Roots
V0	1.05 ab	0.22 ab	1.68 a	4.39	0.49 a	0.10	19.1	618 bc	34.8 bc	49.5	11.1 ab
VC1	1.24 a	0.23 a	1.70 a	4.58	0.36 ab	0.09	14.1	389 c	26.7 c	45.2	7.9 b
VCT100	0.90 b	0.12 c	0.60 b	5.68	0.21 b	0.09	16.0	804 ab	38.0 bc	51.8	11.5 ab
VC1+VCT50	0.91 b	0.14 c	0.71 b	5.65	0.26 b	0.10	16.4	997 a	43.4 b	47.2	12.1 ab
VC3	0.90 b	0.16 abc	0.52 ab	3.71	0.24 b	0.09	19.6	797 abc	41.6 abc	50.6	15.2 ab
VC3+VCT50	0.97 ab	0.12 bc	0.28 b	3.65	0.17 b	0.09	18.2	948 ab	62.0 a	55.3	20.7 a

The elements with an asterisk (*) are statistically significant. Means that do not share a letter are significant differences.

), with significant differences observed across elemental concentrations except for Ca, S, B, and Zn. The N content in leaf samples was not statistically significant across treatments; however, a slight trend was observed where the VC3+VCT50-treated plants had the highest N content (1.89%) compared to the rest. The control-treated (V0) and VC3+VCT50-treated plants had higher P levels than the other treatments. Furthermore, K content was significantly higher in VC1 (1.96%) than in the VC1+VCT50-, VC3-, and VC3+VCT50-treated plants, showing an inverse relationship between K content and VC application rate (Table 3). Furthermore, VC3 had significantly higher Fe content than the control-treated (V0), VC1-treated, and VCT100-treated plants (Table 3).

In the root samples, VC1 showed significantly higher N content (1.24%) than the VCT100-, VC1+VCT50-, and VC3-treated plants. The P content in root samples varied significantly, with VC1 showing the highest concentration level (0.23%), whereas the VCT100- and VC1+VCT50-treated plants showed significantly lower P levels (Table 3). The K content in root samples was significantly higher in the control-treated (V0) and VC1-treated plants than in the VCT100- and VC1+VCT50-treated plants (Table 3). The Mg content was highest in the V0 treatment (0.49%), while treatments with higher vermicompost rates, such as VC3 and VC3+VCT50, had significantly lower Mg levels, consistent with the findings in leaves. The VC1+VCT50-treated plants exhibited significantly higher Fe content in the roots (997 ppm) than VC1. Furthermore, the VC3- and VC3+VCT50-treated plants had significantly higher Mn levels than all treatments. The Cu content in root samples increased significantly with increased VC concentration along the treatments (Table 3).

When comparing the nutrient contents in leaves and roots, the results showed that the leaves contained higher levels of N, P, K, Mg, and B concentrations, while the roots contained higher levels of Ca, S, Fe, Mn, Zn, and Cu concentrations. Furthermore, when comparing the relative nutrient content in the roots (Table 3) and subsurface soils (Table 2), the results showed that the roots contained higher N, P, K, Ca, Mg, and Zn concentrations than those in surface soils.

3.3. Strawberry Biomass, Yield, and Brix Sugar Content

The VC and VCT applications substantially impacted the biomass, yield, and sugar content of the strawberries, as shown in Figure 1. The VC1 treatment resulted in the highest dry biomass production (38,364 kg/acre), followed by the control (V0), VCT100, and VC1+VCT50 treatments, with a biomass of 11,015 kg/acre. There was statistical significance in strawberry biomass yield across all treatments. The VC3 and VC3+VCT50 treatments faced growth challenges, and most were not as healthy as the rest; therefore, their biomass was not determined.

In terms of yield, the highest yield was observed in the VC1 treatment (11,573 kg/acre), which was higher than that of the control (V0). The VCT100 and VC1+VCT50 treatments yielded only 2203 kg/acre (Figure 1), both of which were lower than the control. A statistical significance in strawberry yield was observed across all treatments. However, VC3 and VC3+VCT50 did not yield enough marketable yield.

Brix sugar content, a measure of sugar concentration in fruit, showed some variation across treatments. The sugar content was determined from 12 fruits per treatment for V0, VC1, VCT100, and VC1+VCT50 treatments, as shown in Figure 1, with the highest sugar content observed in the VCT100 treatment. Although not many fruits were obtained from the VC3 and VC3+VCT50 treatments, strawberries had sugar content values of 8.7% and 8.5%, respectively. Furthermore, when the sugar content in these treatments was compared to organic strawberries on the market, the results showed that the store-bought strawberries had a Brix sugar content of 6.8%, which was lower than all the treatments. A statistical difference was observed between VCT100 strawberries and organic strawberries on the market.

3.4. Relative Plant Chlorophyll Content

SPAD values, a measurement of relative chlorophyll content and an indicator of plant health and N status, were analyzed across different treatments over several weeks after planting. The trend and variations in SPAD values are illustrated in Figure 2. At the early stages of growth (weeks 10 to 17), all treatments show relatively higher SPAD values, but as the weeks progressed, there was a decline in SPAD values across all treatments. VC3+VCT50 consistently had lower SPAD values in comparison to other treatments.

3.5. Plant Stomatal Conductance

Stomatal conductance is a critical physiological parameter that indicates how open the stomata are, affecting transpiration and photosynthesis. Most treatments showed an overall increase in stomatal conductance from week 10 to week 17 (Figure 3). The high VC rate applications, VC3 and VC3+VCT50, showed the lowest stomatal conductance. In week 17, treatments diverged significantly, with stomatal conductance in VC1 and VC3+VCT50 increasing more than in the other treatments. A one-way ANOVA followed by Tukey’s HSD test (p < 0.05) confirmed that V0 and VC1 had significantly higher stomatal conductance than VC1+VCT50-treated plants.

3.6. Plant- and Foliar-Level Spectral Reflectance and Vegetative Indices

The spectral reflectance values of the strawberries taken at leaf level and canopy level are shown in Figure 3 and Figure 4, respectively. The visible region (400–700 nm) has a distinct chlorophyll peak centered at 550 nm, which is proportional to the chlorophyll content or greenness of the leaf. The leaf-level spectra (Figure 4) represent the reflectance of the younger, fully matured single leaf. In contrast, the canopy-level spectra (Figure 5) represent the plant’s canopy level. The leaf-level spectra of VC3+VCT50 have lower chlorophyll peaks than other treatments. Also, there is low spectral absorption in the blue (400–500 nm) and red (600–700 nm) regions of the spectra. The near infrared (NIR) plateau (800 nm region) has lower leaf-level reflectance for VC3+VCT50 than other treatments. The spectral reflectance values in the water absorption bands at 1400 nm and 1900 nm remain higher in both leaf-level and canopy-level reflectance for VC3+VCT50. The low reflectance of VC3+VCT50 is consistent with the SPAD values, yield, Brix sugar content, and stomatal conductance observations for this treatment.

The vegetative indices NDVI, GNDVI, and NDMI are presented in

Table 4. Vegetative indices for leaf-level and canopy-level spectral reflectance.

	Leaf Level			Canopy Level
Treatment	NDVI *	GNDVI	NDMI *	NDVI	GNDVI	NDMI *
V0	0.83 a	0.69	0.13 ab	0.87	0.77	0.22 ab
VC1	0.82 ab *	0.66 *	0.16 a	0.90 *	0.82 *	0.27 a
VCT100	0.83 a	0.70	0.17 a	0.83	0.74	0.16 ab
VC1+VCT50	0.81 a–c	0.67 *	0.17 a	0.88	0.80 *	0.21 ab
VC3	0.80 bc	0.69 *	0.10 bc	0.85	0.78 *	0.09 b
VC3+VCT50	0.79 c *	0.68 *	0.06 c	0.87 *	0.79 *	0.08 b

Asterisk (*) indicates indices that showed a statistically significant treatment effect (p < 0.05) based on one-way ANOVA. Different letters within a row indicate significant differences among treatments based on Tukey’s HSD test (p < 0.05).

for leaf-level and canopy-level spectral reflectance values across different treatments. The V0 and VCT100 treatments showed the highest leaf-level NDVI values (0.83), significantly higher than those of VC3+VCT50 and VC3 (p < 0.05). The GNDVI did not show significant differences in reflectance at the leaf and canopy levels. The leaf-level NDMI values were low, although VC3 and VC3+VCT50 had significantly lower values than the rest of the treatments (Table 4). At the canopy level, only NDMI showed significant differences with higher VC application rates, with VC3 and VC3+VCT50 having the lowest values compared to VC1. Also, the reflectance was lower at the canopy level than at the leaf level in the water bands.

Comparing the vegetative indices at the leaf and canopy levels, only statistical significance was observed for NDVI and GNDVI. For NDVI at the leaf level, VC1 and VC3+VCT50 values were significantly lower than their corresponding canopy-level NDVI values. GNDVI values at the leaf level for all treatments, except for the control (V0) and VCT100, were significantly lower than their corresponding canopy-level GNDVI values. There was no significant difference between leaf-level and canopy-level NDMI.

4. Discussion

This study explored the residual effects of VC and VCT treatments on strawberry growth and physiology in a rotation system following corn cultivation. The findings show the significance of VC applications for immediate crop enhancement and their prolonged impact on subsequent crop rotations.

4.1. Soil Chemical Analysis

Soil nutrient content data (Table 1) from the preceding corn experiment [25] confirmed that VC and VCT treatments significantly influenced post-harvest soil fertility across surface and subsurface layers. These residual nutrients provided a fertility baseline for the subsequent strawberry trial. However, while subsurface %OM and %C increased under these treatments (Table 1), CEC remained statistically unchanged. This is due to the short-term nature of the amendment, limited biological activity at this depth, and the insensitivity of the unbuffered 1 M NH₄Cl method to modest organic matter contributions in lower horizons [26].

After strawberry cultivation, post-harvest soil nutrient content analysis showed significant differences among the various treatment groups for all the elemental concentrations, especially in the surface soils, except for pH, K, and Zn. High vermicompost application rates, specifically VC3 and VC3+VCT50, were associated with elevated N, P, Mg, Na, OM, and CEC (Table 2). This demonstrates vermicompost’s potential to significantly enhance soil fertility by increasing the availability of macro- and micronutrients and improving soil structure, aligning with previous research findings [27]. It also shows the slow-release nature of vermicompost, which provides a steady nutrient supply essential for chlorophyll synthesis and plant growth [28]. Additionally, the increased P availability in all treatments illustrates VC’s ability to solubilize P, enhancing energy transfer and root development [13].

The elevated Na concentrations in the soils of all treatments could be attributed to using vermicompost with high Na content [25], which affected the VC and VCT applications. The high soil Na concentration might have contributed to high plant stress and poor growth in the VC3+VCT50-treated plants since strawberries are highly salinity-sensitive [29]. Stress in the VC3+VCT50-treated plants was also evident with low SPAD readings (Figure 2), low conductance (Figure 3), and lower chlorophyll reflectance peak (Figure 3 and Figure 4). These stress indicators corresponded to the reduced strawberry yield and slightly lower Brix sugar content observed in the VC3+VCT50 treatment.

In subsurface soils (10–20 cm), while nutrient content was generally lower than in surface soils, significant improvements were still observed in treatments with higher VC applications. The VC3 treatment, for instance, showed the highest N content (0.60%) in subsurface soils (Table 2), illustrating VC’s potential to promote nutrient availability beyond the immediate root zone and support deeper nutrient uptake [13,14,15]. Furthermore, higher Ca and Mg levels, as well as increased CEC, were observed in the VC3 and VC3+VCT50 treatments, improving soil structure and plant health [30]. The higher OM content in these treatments indicates enhanced soil aggregation and microbial activity, promoting long-term soil fertility.

The study findings demonstrate that nutrient levels are generally higher in surface soils than in subsurface soils across all treatments. The limited vertical movement of nutrients from the surface to the subsurface soil depths emphasizes the effectiveness of surface application techniques, which maximize nutrient availability in the critical root zone. This pattern can be attributed to the direct application of vermicompost to the soil surface, where it undergoes decomposition and nutrient release. The higher nutrient content in surface soils is crucial for crop establishment and early growth, providing readily available nutrients for young plants. The findings from Table 2 affirm that the observed strawberry responses were due to inherent soil properties and a direct consequence of nutrient carryover from the previous corn cropping season.

4.2. Plant Chemical Analysis

The distinct partitioning of nutrients between leaves and roots shows the different roles these plant parts play in nutrient dynamics. Leaves had higher concentrations of macronutrients, which are essential for photosynthesis and growth, while roots exhibited higher levels of micronutrients, reflecting their role in absorbing nutrients from the soil.

The leaf N concentrations were highest in the VC3+VCT50 treatment, indicating that a combination of vermicompost and VCT can potentially enhance N uptake (Table 3). In contrast, roots showed the highest N content in the VC1 treatment, suggesting that moderate vermicompost applications might be more effective for N uptake in roots. This differentiation in nutrient uptake patterns between leaves and roots could be attributed to how residual vermicompost influences soil nutrient availability, potentially enhancing microbial activity and N mineralization [31]. The P content in leaves was relatively higher in the control (V0) and VC3+VCT50 treatments, indicating that residual vermicompost might improve P availability even when applied in previous crop cycles. The inverse relationship between K content and the VC application rate in leaves suggests that higher vermicompost rates might inhibit K uptake or redistribution. This could be due to competitive absorption dynamics with other nutrients, such as Ca and Mg.

Iron and Mn showed enhanced availability in treatments with higher vermicompost rates, particularly VC3 and VC3+VCT50. This indicates that residual vermicompost may improve the solubility and uptake of certain micronutrients by producing chelating agents and improving soil structure. Interestingly, the VC1+VCT50 treatment exhibited the highest Fe content (Table 3) in roots, emphasizing the role of specific treatment combinations in optimizing micronutrient uptake. The differential effects observed across treatments highlight the importance of optimizing vermicompost application rates to achieve balanced nutrient availability. These findings align with previous research, such as Refs. [18,32], which reported positive impacts of vermicompost on plant growth and soil health.

4.3. Strawberry Biomass, Brix Sugar Content, and Yield

4.3.1. Biomass Production

The VC1 treatment resulted in the highest dry biomass at 38,364 kg/acre, followed by the control (V0) with 28,364 kg/acre. This suggests that moderate vermicompost applications can significantly enhance biomass production due to improved nutrient availability and soil structure, a consequence of the slow-release nature of vermicompost. This finding is consistent with studies indicating that moderate organic amendment rates optimize biomass production by improving soil health without overwhelming the plant’s nutrient uptake systems [30].

The statistical analysis and Figure 1 showed that the superior performance of VC1 likely stems from its optimal nutrient profile, which promoted plant vigor without inducing salt stress. In contrast, treatments such as VC3 and VC3+VCT50 were excluded from biomass measurement due to poor plant establishment and health, consistent with their high sodium content (Table 1), which can lead to osmotic stress and growth inhibition.

In contrast, excessive VC applications likely introduced increased salinity, as shown by the elevated Na concentrations in the post-corn soils under VC3 and VC3+VCT50 treatments (Table 1). This salinity stress may have persisted into the strawberry season (Table 2), contributing to inhibited plant growth and reduced biomass accumulation. This finding aligns with previous studies indicating that strawberries are susceptible to soil salinity. High salinity levels can lead to leaf edge burn, necrosis, nutrient imbalances, specific ion toxicity, reduced fruit quality and yield, and even potential plant death if salinity stress persists or worsens [33].

4.3.2. Brix Sugar Content

This measures sugar concentration in fruit and is an essential quality indicator, showing variability across treatments but less pronounced differences than biomass and yield. The VCT100 treatment exhibited the highest Brix sugar content (9.3%), although it was not significantly different from other treatments, suggesting that VC and VCT applications enhance fruit quality. Notably, the lack of statistical significance across treatments (except between VCT100 and store-bought strawberries) indicates that while nutrient amendments may enhance sweetness, other factors such as genetics, maturity, and water availability may also play critical roles.

Interestingly, when comparing the Brix sugar content of strawberries from these treatments to organic strawberries available on the market, the market-bought strawberries had a lower Brix sugar content of 6.8%. This finding aligns with other studies that show organic amendments can enhance fruit quality by improving sugar accumulation compared to conventional practices [34].

4.3.3. Strawberry Yield

The impact of VC and VCT on strawberry yield was notable. The VC1 treatment produced the highest yield, comparable to the average of 11,300 kg/acre reported for South Florida [35]. This suggests that moderate vermicompost applications can optimize strawberry production by providing balanced nutrient availability and improving soil structure. In contrast, yields declined sharply in treatments with higher VC and VCT rates (e.g., VC3 and VC3+VCT50), likely due to increased soil Na levels causing salinity stress [18]. The low yield observed in VC1+VCT50 also suggests that even moderate rates, when combined, may affect nutrient dynamics or exacerbate salinity-related effects if not well-calibrated.

4.4. Relative Chlorophyll Content in Plants

The analysis of chlorophyll content, as indicated by SPAD values, shows varying trends across different treatments over several weeks after planting. The chlorophyll content is a critical indicator of plant health and N status, and its variation provides insights into how different treatments influence plant physiology and growth.

The decrease in chlorophyll content (Figure 2) from weeks 10 to 17 after planting is likely due to the plants reallocating energy resources from chlorophyll production to fruit development as the strawberry plants matured. As the plant shifts its focus to developing flowers, fruits, and seeds, less energy is available to maintain chlorophyll levels in the leaves. This is consistent with the understanding that plants often redirect energy to support reproductive structures as they mature, which can result in reduced leaf chlorophyll levels [36,37]. All treatments showed relatively high SPAD values in weeks 10 to 17, indicating that the residual effects of vermicompost and the inherent soil nutrients provided adequate N and other nutrients to support early growth and chlorophyll synthesis.

The reduced chlorophyll content in VC3+VCT50-treated plants can be attributed to the higher sodium levels observed in these treatments (Table 2), which are known to disrupt chlorophyll biosynthesis and accelerate leaf senescence [33]. Vermicompost and VCT applications influence chlorophyll indirectly by altering soil nutrient availability and salinity balance. Moderate VC rates (e.g., VC1) likely provided sufficient nitrogen and micronutrients to support healthy chlorophyll formation, while excessive applications led to ion toxicity and reduced photosynthetic pigment retention.

4.5. Stomatal Conductance in Plants

Stomatal conductance is a physiological parameter that reflects the openness of plant stomata, affecting both transpiration and photosynthesis. It is an essential indicator of plant response to environmental conditions and nutrient availability. In this study, stomatal conductance showed an overall increase from week 10 to week 17, suggesting an adaptation of the plants to their environment and treatments.

At the initial stage (week 10), all treatments exhibited relatively similar stomatal conductance, ranging from 0.10 to 0.15 (Figure 3), except for high VC rates (VC3 and VC3+VCT50), which showed the lowest initial conductance. This initial low conductance could be due to the higher organic matter content in these treatments, potentially leading to increased soil moisture retention and reduced stomatal opening, as plants may not need to open their stomata as broadly or as often because there is less need for water uptake from the soil [38,39,40]. The steady conductance observed in VC3 up to week 17 indicates that plants in this treatment maintained a relatively constant water and nutrient uptake strategy. Furthermore, VC3+VCT50 consistently has lower stomatal conductance in weeks 10 to 17, consistent with lower SPAD values. The persistently low stomatal conductance in VC3+VCT50 plants could also be attributed to residual salinity stress from the elevated sodium levels observed in these soils following the corn experiment (Table 2), which may have limited water uptake and physiological activity.

Treatment-related changes similarly influenced stomatal conductance in soil chemistry. In treatments with moderate nutrient levels (e.g., VC1), plants maintained optimal stomatal function, likely due to balanced water and nutrient uptake. In contrast, VC3+VCT50 showed persistently low conductance, which can be explained by salinity-induced osmotic stress, limiting water availability at the root–soil interface, and prompting partial stomatal closure to conserve moisture [39]. This physiological response is consistent with lower chlorophyll content, reduced SPAD values, and spectral reflectance patterns observed in the same treatment.

4.6. Plant- and Leaf-Level Spectral Reflectance and Vegetative Indices

The spectral reflectance data show differences between leaf-level and canopy-level measurements, particularly in the visible and near-infrared (NIR) regions. The leaf-level spectra of VC3+VCT50 have lower chlorophyll peaks than other treatments, indicating lower chlorophyll content. Also, low spectral absorption in the blue (400–500 nm) and red (600–700 nm) regions of the VC3+VCT50 spectra indicates a lower rate of photosynthesis, which is consistent with SPAD and stomatal conductance values. The high-water absorption bands at 1400 nm and 1900 nm in both leaf-level and canopy-level reflectance for VC3+VCT50 indicate water stress in plants. These spectral patterns correspond with the observed reductions in biomass, yield, and Brix sugar content in the same treatment, highlighting a clear link between physiological stress signals and diminished agronomic performance.

The higher reflectance in the green band at the leaf level suggests that individual leaves reflect more green light, which is typical for healthy, chlorophyll-rich leaves. The absorption troughs observed in the blue (400–500 nm) and red (600–700 nm) regions further indicate active photosynthesis and chlorophyll absorption [41]. At the canopy level, the reduced reflectance in the green band and more pronounced absorption in the blue and red regions can be attributed to the increased complexity of the canopy structure, including overlapping leaves, shadows, and varying leaf orientations [42,43]. In the NIR region (760–900 nm), the distinct separation of spectral curves at the canopy level, compared to the indistinguishable curves at the leaf level, reflects differences in canopy architecture, biomass, and leaf area index (LAI). The internal leaf structure and canopy geometry influence the NIR reflectance, with higher NIR reflectance indicating healthier and denser canopies [44]. These findings suggest that canopy-level measurements provide a more integrated view of plant health and structure, whereas leaf-level measurements offer detailed physiological insights.

The Normalized Difference Vegetation Index (NDVI) is a widely used indicator of plant health, reflecting chlorophyll content and photosynthetic activity. The lower NDVI values (Table 4) observed in high VC application rates (VC3 and VC3+VCT50) may indicate nutrient imbalances affecting chlorophyll content and photosynthetic efficiency. At the canopy level, the NDVI values were generally higher than at the leaf level, reflecting the integrated health and vigor of the entire plant canopy. The differences between leaf and canopy NDVI highlight the complexity of scaling leaf-level measurements to whole-canopy assessments, as canopy-level indices capture the combined effects of the leaf area, density, and structure [44,45]. The comparison of vegetative indices at leaf and canopy levels showed that leaf-level NDVI values were lower for VC1 and VC3+VCT50 compared to their respective canopy level values. Leaf-level GNDVI values were lower for all treatments except V0 and VCT100 compared to their canopy-level counterparts, suggesting that canopy measurements integrate more comprehensive plant responses, capturing variations in leaf area and distribution.

The Normalized Difference Moisture Index (NDMI) assesses plant water content and stress. NDMI values were generally lower than 0.4 for all treatments at both the leaf and canopy levels, indicating potential water stress [46,47]. NDMI is particularly useful for assessing relative plant water content and detecting moisture-related stress before visual symptoms appear. The consistently low NDMI values observed in the VC3 and VC3+VCT50 treatments likely reflect reduced water uptake due to elevated soil salinity, as indicated by high Na concentrations in Table 2. This is on par with the lower stomatal conductance (Figure 3) and reduced SPAD values (Figure 2), suggesting that the high Na content in the VC used may have disrupted plant water balance in this study. It is, therefore, essential to characterize vermicompost composition, as salinity-related stress effects may vary depending on feedstock sources. In contrast, higher NDMI in VC1 reflects better water retention and nutrient availability, contributing to improved physiological performance and yield.

Therefore, the corn–strawberry rotation used in this study was intended to simulate conditions where organic inputs are applied to one crop, and their residual effects are observed on a subsequent high-value crop. While this rotation is not standard practice in many production systems, it allowed for a controlled evaluation of nutrient carryover, soil salinity, and plant physiological responses. We recognize that outcomes might differ under alternative rotations, soil types, or amendment application timings. Therefore, caution should be taken when generalizing these results beyond the experimental setup.

5. Conclusions

This study showed the importance of the residual effects of vermicompost (VC) and vermicompost tea (VCT) on strawberry production in a corn–strawberry rotation system. A moderate vermicompost application (1 ton/acre, VC1) significantly enhanced strawberry yield, biomass accumulation, and fruit quality, as evidenced by increased Brix sugar content. These improvements reflect the role of VC in maintaining residual soil fertility and supporting plant physiological performance without additional fertilizer inputs.

However, high-rate applications (VC3 and VC3+VCT50) reduced plant vigor and yield, coinciding with elevated soil sodium concentrations and stress responses in plant physiology. In addition, VCT100, VC1+VCT50, and VC3+VCT50 treatments also resulted in diminished physiological performance and yields compared to VC1. It is important to note that these outcomes were specific to the vermicompost source used in this study, which contained atypically high sodium levels. Such salinity-induced effects may not be observed in vermicompost derived from low-sodium feedstocks. We recommend routine analysis of vermicompost sodium content, especially when applying high rates or using composts derived from salt-accumulating species, to prevent potential salinity stress in salt-sensitive crops like strawberries.

This study was limited to a single growing season under subtropical field conditions, and findings may not fully represent long-term or broader climatic responses. Additionally, the experiment was based on a specific corn–strawberry rotation designed to assess residual amendment effects. Therefore, outcomes may vary depending on alternative cropping systems or environmental conditions. Nevertheless, vermicompost and its derivatives offer a sustainable, rotation-compatible, cost-effective alternative to synthetic fertilizers; it is one that enhances strawberry productivity while reducing chemical input dependence, as long as salinity risks are managed through appropriate feedstock selection and pre-application testing.