Sulfur Source Effects on Soil Sulfur Concentration, Vegetation Indices, Biomass, and Sulfur Uptake in Potato

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Sulfur Source Effects on Soil Sulfur Concentration, Vegetation Indices, Biomass, and Sulfur Uptake in Potato

https://doi.org/10.21203/rs.3.rs-3214123/v1

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Potato is an important tuber crop, consumed globally by over a billion people. Among the essential nutrient for optimum potato growth, sulfur (S) is the most crucial after nitrogen, phosphorous, and potassium. In addition, the S is necessary for amino acid production, disease resistance, protein synthesis, and N assimilation. In this study, we tested the performance of three S sources: magnesium sulfate (EPTOP), gypsum, Ammonium sulfate (AS) applications at 45 and 90 kg ha^− 1 for soil S availability, vegetative indices, above- and below-ground biomass, and potato S uptake. It was found that maximum soil S availability was reported when applied as EPTOP, followed by gypsum and AS at 90 kg ha^− 1 compared to 45 kg ha^− 1. For vegetative indices such as normalized difference vegetative index (NDVI), normalized difference red-edge index (NDRE), and chlorophyll content (CC), the maximum values were reported when gypsum and EPTOP were applied compared to AS. These differences were decreased later in the crop stages. Besides, individual band reflectance red and red-edge values decrease with time and near infra-red increases with time, following the same trend as of vegetative indices. For S uptake, sources or rates did not affect shoot S uptake, but for tuber S uptake, the factors such as S source, rate, and sites had a significant interaction. The maximum S (9.65 kg ha^− 1) among the tubers was removed when EPTOP was applied at 45 kg ha^− 1. It was reported that the EPTOP can release the S slowly so can retain in the soil for longer time which eventually reflects in its responses as biomass production and S removal.

Biological sciences/Plant sciences/Light responses

Biological sciences/Plant sciences/Plant development

Earth and environmental sciences/Environmental sciences

Physical sciences/Optics and photonics

Potato (Solanum tuberosum L.) contributes to global food security due to its high yield in terms of volume and nutrients. It supplements or replaces grain-based meals when transport chain disruptions reduce the availability of grains such as wheat (Triticum aestivum L.), rice (Oryza sativa L.), and maize (Zea mays L.) (Camire et al., 2009). Its adaptability to diverse environmental conditions and high yield potential make potato an ideal vegetable for ensuring food and nutrition security (Kyamanywa and Kashaija, 2011). In terms of volume, potatoes are the fourth most produced crop in the world, after rice, wheat, and maize (Hirpa et al., 2010). It ranks first in production volume among tuber and root crops (Cromme et al., 2010). In addition, potatoes are adaptable to numerous climates and cultures, and their global consumption has increased (Campos and Ortiz, 2019)

Florida is among the top spring potato production states, although yields are far lower than those of the midwestern and western United States (DeFauw et al., 2012). However, increasing potato yield and quality with conventional fertilization techniques is challenging because of the old fertilizer recommendations; as a result, new agronomic strategies are required to meet the producer and industry demands(Sharma et al., 2017).

Nutrients such as nitrogen (N), phosphorous (P), and potassium (K) have been extensively studied and recommended for potatoes in Florida. In addition, crop sulfur (S) requirements become essential because of the decreasing atmospheric S deposition and increasing fertilizer's purity with time (Hinckley et al., 2020; Weil and Brady, 2018). The S is critical for potato tuber quality, N assimilation, amino acid production, and protein synthesis. Nevertheless, different sources of S are available, which have varying characteristics when interacting with soil, environment, and plants. Such as, in the coarse sandy soils of Florida, S leaching is the challenge that makes it more difficult to retain S in soil for later stages of plant growth, mainly if the S sources are applied as sulfate (SO₄²⁻) (Grant et al., 2012; Stark et al., 2004).

The impacts of S sources on crop growth yield, diseases, quality, and soil health were explored. Grant et al. (2012) found that adding S as a sulfate boosted rapeseed yield. Furthermore, S application was shown to have an interaction impact when combined with polymer-coated urea in N uptake (Geng et al., 2016). The research on peanuts found that gypsum was the best S source for application, followed by single super phosphate and ammonium sulfate in typical haplaquent soil (Prasad, 2003). The naturally occurring S forms elemental S, and SO₄²⁻ S may be employed. Three-year research on sandy loam soil using three S sources indicated that only 7% of S leached from the soil in the first year when administered with a mixture of bentonite clay and S followed by micronized elemental S (26%) and ammonium sulfate (AS) (72%). After three years, Riley et al. (2002) observed that 33%, 75%, and 96% of S leached from bentonite clay and S, micronized elemental S, and AS, respectively. Furthermore, Sharma et al. (2023) reported higher tuber yield when treated with magnesium sulfate (EPTOP) or gypsum than AS.

Vegetative indices (VIs) such as normalized difference vegetation index (NDVI), normalized difference red-edge index (NDRE), and chlorophyll content (CC) have historically been used to assess plant health. The VIs monitors the plant cell composition, which fluctuates with changes in plant chemistry, development stage, and environment, by focusing on a particular band of lights reflected by the plant canopy. These VIs may be utilized to research the S source response since S deficiency symptoms appear on the plant's young leaves. Puyska et al. (2018) used SPAD and chlorophyll fluorescence to investigate the impact of foliar S and B application on oil seed rape and reported a significant increase in yield due to the application of S. Pagani and Echeverra (2011) also reported that applying S boosted maize yield, total biomass, S concentration, and the changes were detectable by chlorophyll meter readings.

Extensive research is still required to fully comprehend the S concentration response to light reflection to adapt to advanced technology, such as active and passive sensors. Therefore, this study was conducted to investigate the effect of S sources on the various aspects of potato cultivation with the objectives a) to understand the S source, rate and location effects on in-season soil S movement, potato biomass production, and S uptake by potato plants. It also includes the VIs as in responses of treatments.

The part of the experiment already published(Sharma et al., 2023) which discussed the effects of S sources and rates on the potato tuber yield, specific gravity internal and external tuber quality. In that study it was reported that the EPTOP and gypsum outperformed the AS in tuber yield. Where the maximum yield was reported from the lower rate (45 kg ha^− 1) compared to the higher rate (90 kg ha^− 1). The S source and rates did not had effects on the internal and external tuber quality. This article discusses the S source and rate responses measured as soil S availability, Crop biomass, VIs, and S uptake.

Experimental site

This study was established at the University of Florida, Institute of Food and Agricultural Sciences, Hastings Agricultural Extension Center (HAEC), Hastings, Florida, in spring 2022, with two separate trials on site 1 and site 2. The field trials were located nine to ten meters above sea level at 29˚41'34.60" N and 81˚26'29.42" W. This region has tropical-subhumid weather with cold winter and spring. The average minimum and maximum temperatures are 5–16°C and 25–35 ˚C in the winter and summer, respectively. The soil of the site 1 were nonhydric soils with elezy series fine sand and site 2 has a nonhydric soil with holopow series fine sand (Soil Survey Staff, 2023). But both sites had poor drainage due to the high water table caused by shallow impermeable layer at 3m depth (Biscaia Ribeiro da Silva et al., 2018). Additionally, site 1 has been under agricultural cultivation for > 80 years, whereas site 2 was first cultivated in the spring of 2013.

Treatments and Experimental Design

The trials were established as a randomized complete block design with a split-plot restriction on randomization. The main-plot factor was source of sulfur, with the three levels – EPTOP salt (12.94% S), gypsum (17% S), and AS (27% S) – and the sub-plot factor was sulfur rate, with two levels: 45 and 90 kg ha^− 1. These treatments were applied using a four-row applicator (Hansel applicator designed for fertilizer application in research at HAEC) for uniform application across the treatment plot. Each treatment was applied to the 9.1 m long and 4 m wide plot, which includes four rows separated at a 1 m distance. Seed pieces of the potato cultivar "Atlantic" were planted at a 10 cm depth and 20 cm distance from each other, on 1st April. Subirrigation method (seepage irrigation) method was used, where the ground water table was raised and maintained at 55 to 65 cm below planting hills. Irrigation was provided during the growing season between February and May according to the soil moisture and weather conditions.

Weather data

The weather parameter, such as air temperature (Daily average ˚C), rainfall (mm), and solar radiation (MJ m^− 2), were recorded from the Florida Automatic Weather Network (FAWN) Hasting station daily, as shown in Fig. 1. This data was recorded with the automatic weather station available at the research site (UT30, Cambell Scientific) recorded the observation at a temporal resolution of 15 min and calculated at hourly and daily summaries (accessed through Florida Automated Weather Network (FAWN, https://fawn.ifas.ufl.edu//)

Soil data

The pre-plant soil samples were collected to determine the S baseline concentration (Table 1). After planting, in-season soil samples were collected at five different crop stages: 29, 43, 60, 73, and 108 days after planting (DAP). These soil samples were collected from the two central rows of each plot at 0–30 cm depth. A minimum of four subsamples were collected from two center rows and combined as a composite soil sample, out of which representative samples were collected and air-dried. The dried samples were then submitted to the Agricultural Research Laboratory, IFAS, UF, Gainesville, for the S analysis using the Mehlich III extractant (Hochmuth et al., 2022).

Table 1

The pre-planting soil conditions for site 1 and site 2 were analyzed by using the Mehlich III extraction method.
Particular	Site 1	Site 2
Soil series type	Ellezy fine sand, poor drainage	Holopaw fine sand, poor drainage
Soil texture	Sandy Soil	Sandy Soil
pH	6.2	5.5
CEC meq 100g^− 1	3.5	5.6
P (mg kg^− 1)	247.0	52.7
K (mg kg^− 1)	25.2	32.7
S (mg kg^− 1)	14.0	21.7
Ca (mg kg^− 1)	403.5	446.7
Mg (mg kg^− 1)	44.0	73.7

Vegetation Indices (VIs)

The vegetation indices (VIs), such as NDVI (Eq. 4), NDRE (Eq. 5), and chlorophyll content (CC), were recorded by using the handheld active optical sensor (430 ACS Crop Circle, Holland Scientific, Lincoln, Nebraska). This data was recorded at six different crop stages throughout the growing season from a single center row of the plot at 42, 48, 63, 72, 79, and 86 DAP. In addition, the active optical sensors recorded the reflection for three bands such as red (R), red edge (RE), and near-infrared (NIR), where the other indices were calculated by using equations 4 and 5.

R = Red band (670 nm) (1)

RE = Red-edge band (730 nm) (2)

NIR = Near-infra red band (780 nm) (3)

NDVI = (Red + NIR)/ (Red – NIR) (4)

NDRE = (Red edge + NIR)/ (Red edge – NIR) (5)

Biomass

Samples of the potato plant were collected at 42, 63, 72, and 107 DAP of the crop growing season. At each sampling event, two representative plants were collected from the border rows and measured as above-ground biomass (AGB) and below-ground biomass (BGB). At the last sampling, the tuber yield was considered BGB, and shoots were harvested separately. The fresh weight of the samples was used for calculating the AGB and BGB by considering the crop stand (supplementary table 1).

Sulfur Uptake

The biomass samples collected in the previous step were oven-dried (60˚C) separately as AGB and BGB until they reached constant weight for two consecutive days. Then dried biomass samples were grounded using the grinding mill (Thomas Model 4 Wiley Mill, Thomas Scientific, Swedesboro, NJ, USA) in 40 mesh size. The samples were then sent to UF/IFAS Analytical Services Laboratories, Gainesville, Florida, to measure the S (mg kg^− 1) concentration available in samples by using the ICP method (Soon et al., 1996). The available concentration was then further used to compute S uptake by the potato crop throughout the growing season.

Statistical analysis

Linear mixed effects models (Pinhiero and Bates, 2009; Pinhiero et al. 2019) were fit to measurements of the vegetation indices (VIs), above-ground and below-ground biomass (Mg ha^− 1), S uptake (kg ha^− 1) and soil S availability (kg ha^− 1), with random effects for block, the main-plot (S source) and sub-plot (S rate). The fixed effects included in the models were: site, sampling date, S source and S rate (all of which were treated as a categorical variables) along with all higher order interactions. Model assumptions were verified using diagnostic plots of the residuals. Finally, Akaike’s Information Criteria was used to assess for each model whether the fit was improved by the inclusion of non-independence and/or in homogeneity in the residual variance-covariance matrix (i.e. R-side modeling to account for repeated measures and heteroskedasticity). F-tests were then performed to determine which of the fixed effects were significant. Post-hoc comparisons were performed using Tukey’s adjustment or multivariate t-test, as appropriate (Lenth et al., 2023). The analysis was performed using RStudio version 4.2.2 (Rstudio Inc, Boston, MA, 2022, R Core Team, 2022). Data visualization and plotting was done using ggplot2 (Wickham, 2016).

Soil Sulfur concentration

All four of the main effects were found to be significant (p < 0.05), along with the site x date interaction (p = 0.0381) and the S source x S rate interaction (p = 0.0381). At Site 1, S availability was found to decline from 29 to 60 DAP before rising again between 60 and 108 DAP (Fig. 3a). The pattern at Site 2 was more ambiguous, with S availability rising briefly at 43 DAP, and again at 108 DAP.

The interaction between S rate and source is visible in Fig. 2b, where soil S availability does not differ significantly among sources when supplied at 45 kg ha^− 1, but EPTOP can be seen to increase soil S availability relative to gypsum when they are supplied at 90 kg ha^− 1.

Vegetation indices (VIs) and Individual bands

The vegetative indices and individual band reflections, such as NDVI, NDRE, CC, R, NIR, and RE, were measured at six DAP. The S sources and DAP were significant (p < 0.05) for all indices and individual bands. (Fig. 3). There was no effect of S rate and location on the VIs and individual band reflection, was reported.

For VIs, the NDVI, NDRE, and CC values increased until 63 DAP, after which they remained stable for the rest of the growing season. Among the various sources, gypsum had the NDVI value at 42 DAP, which was significantly different than AS at both rates. The NDVI values for AS were low at initial sampling events, but after 72 DAP, there was no difference between the sources (Fig. 3a). Similar, trends were reported for NDRE, where significant difference was reported among gypsum and AS at 90 kg ha^− 1 in initial stages (Fig. 3b). It was observed that the difference in NDRE values of the S source reduces in later samplings.

Similarly, the CC values of potato plants in response to S source were significantly different among gypsum and EPTOP with AS at 48 DAP and among gypsum and AS at 63 DAP. The difference in CC among the different S sources reduced at the later crop growth (Fig. 3c).

Individual band reflectance for NIR, RE, and R were measured at various stages of plant development (Fig. 3d, e, f). The RE was reported to be the least sensitive of the individual bands to sources and time, with 20 to 26% reflection in overall sampling events for all three sources. Among NIR, there was a significant difference between EPTOP and AS at 42 DAP and among EPTOP and Gypsum with AS at 48 and 63 DAP for the 90 kg ha^− 1 S rate (Fig. 3d). Similarly, EPTOP and gypsum were significantly different than AS at 90 kg ha^− 1 at all sampling events (Fig. 3e). Conversely, reflectance for the R band was inversely proportional to the RE. The R band reflectance value for AS sources was significantly greater than the EPTOP and gypsum reflectance value at 42, 48 and 63 DAP, when applied at 90 kg ha^− 1 (Fig. 3f). Similarly, it was discovered that the reflectance values for the R band decreased over time, regardless of S sources, whereas the reflectance values for NIR increased (Fig. 3d and 3f).

Biomass

Biomass samples of potato plants were taken at 42, 63, 72, and 107 days after planting. AGB and BGB biomass samples were recorded separately. However, the S application affected the AGB over time and did not show the effect of the S source, S rate, and location (supplementary Fig. 2).

For BGB, significant interactions existed between DAP and S sources and DAP and locations. At 42 and 63 DAP, the S Sources did not affect the BGB, but there was a significant S source effect at 72 and 107 DAP (Fig. 4a). The plots treated with gypsum had the highest BGB than the plots treated with AS when S was applied at 45 kg ha^− 1. For BGB, the S rate had no effect, but at a higher rate (90 kg ha^− 1), no significant S source impact was reported, whereas, at a lower rate (45 kg ha^− 1), there was a difference at 107 DAP. Among the locations, site 1 was reported to have the higher BGB when applied as gypsum at 45 kg ha^− 1 (Fig. 4b). Besides, 45 kg ha^− 1 had a higher BGB than 90 kg ha^− 1 of S, irrespective of the S source applied.

Sulfur Uptake

The S uptake was calculated for AGB and BGB based on the laboratory analysis of samples collected during the biomass collection step. There was no significant influence of S source, rate, time, or location on the AGB's S uptake (Fig. 5a). The interaction effect of location, S sources, S rates, and DAP on tuber S uptake was significant (p < 0.05), where the results for 72 and 107 DAP sampling events only represented due to no difference in the early stage (Fig. 5b). The EPTOP reported the highest S uptake (9.65 kg ha^− 1) at harvest (107 DAP) from site 1 when applied at 45 kg ha^− 1 which was significantly different than the AS. Where there was no difference in S uptake by potatoes at site 2 when applied at 45 and 90 kg ha^− 1.

Sulfur source and soil

The S is a leaching prone nutrient where SO₄²⁻ makes it unable to bind with finer particles in soil (negatively charged) (Jones Jr., 2012; Scherer, 2001). Therefore, the elemental S sources, such as EPTOP are also used, as they require mineralization before being available to the plant compared to the SO₄²⁻ S sources like AS and gypsum (Scherer, 2001). Similar observations were reported from this study, where EPTOP S availability was higher throughout the season at all sampling events compared to the SO₄²⁻ S sources (gypsum and AS). Besides, the field history significantly affected the S availability, where the new field under agriculture (Site 2), had more S than the old field (Site 1) throughout the season. Furthermore, initial soil sulfur concentration affects S response, where low SO₄²⁻ S soils respond to the additional S application (Pias et al., 2019), in line with the present study's findings. Irrigation water is also considered the source of S, where this study observed a similar trend where it adds S to the cultivation system (Supplementary Fig. 1). This eventually increases the soil S availability in the later stage of the crop irrespective of the source applied; still, EPTOP had a more available S than other sources which might be due to slow release (Fig. 3b) (Jones, 2015).

Potato responses to sulfur sources and rates with VIs:

The VIs such as NDVI, NDRE, CC, and individual band reflectance for R, RE, and NIR were reported to have S source effects. The VIs has been conventionally used for crop physiology monitoring, stress, and nutrient rate effects on the crop (Saravia et al., 2016). The vegetative indices vary with the sensor type and configuration, such as green seeker use for NDVI, SPAD for chlorophyll content, and canopy cover using the UAV systems (Mahajan et al., 2017; Saravia et al., 2016; Xie et al., 2022). In a similar study conducted by Bushong and coworkers (2018) with corn, where green seeker and SPAD were used for developing the fertilizer recommendation index, it did not perform well until the early stage (V9). Also, it did not represent any differences with the N source. On the contrary, this study reported the differences between VIs and individual band reflection.

Sulfur Sources and Biomass production

Additional S to the systems has increased the production of biomass and yield in the crops such as rape seeds and lettuce (Abdalla et al., 2021; Jankowski et al., 2015). In this study, we reported the same trend where the maximum BGB was reported from site 1, which had less pre-planting S availasbility than site 2. Similarly, the S application affects the total biomass production, which was in line with the findings of this study (Kim et al., 2013; Raza et al., 2018). In addition, the additional S to the system increased the photosynthetic activities and availability of the other nutrient, which might positively affect biomass production (Solomon et al., 2019).

Sulfur sources and sulfur uptake

The S uptake varies with the plant species and the crop stages, whereas the S concentrations in different plant parts vary with crop stage (Raza et al., 2018; Schnug & Ji, 2005). The maximum S concentration from vegetative parts moves to the reproductive parts in sesame at a later crop stage (Raza et al., 2018), in line with what this study found. This study found that the S moves to the tuber from the vegetative stage, and shoot S uptake remains constant, where tuber S concentration increased until harvesting. The S uptake by the crop varies with legacy S concentration in soil (Kim et al., 2013), similar to what was reported by this study, where the soil with high soil organic matter was less responsive to the S application.

The sandy soils of Florida are prone to nutrient leaching, which makes soils deficient in nutrient availability for optimum crop growth. Various S sources are available in the soil application market but vary in response and S availability. The findings of the present investigation imply that the elemental S source (EPTOP) stays longer in soils compared to the gypsum and AS. However, the soil S availability also depends on the legacy S concentrations and Field history. Besides, it also depends on the S rate applied where higher rates (90 kg ha^− 1) had more available S than lower rates (45 kg ha^− 1). Still, lower rates outperformed higher rates in plant responses such as biomass production and S uptake. The active handheld sensors can monitor crop nutrient status by estimating NDVI, NDRE, and CC. Besides this, the S uptake by the potato crop shows that the elemental S had a maximum S uptake by the crop than other sources. But soil S availability was affected by the irrigation water SO₄²⁻ concentrations. Further research should be conducted with a complete S budget to understand the various S inputs and their share in crop production systems, which can help with precise nutrient recommendations.

Acknowledgment:

We appreciate the support of the United States Department of Agriculture (USDA) Specialty crop block grant and the Florida Department of Agricultural and Consumer Services (FDACS) for funding this research. In addition, we want to thank Amanpreet Kaur, Benjamin Tubb, Brenden Burns, Holden P. Muehleisen, and Hayden Shellenbarger for assisting in the field for sampling and collecting data required for this manuscript. I would also like to thank Dr. Diego for his valuable comments to improve this manuscript. Finally, we would also like to thank all our Hastings Agricultural and Extension Center field members for their help in conducting the successful experiment.

Data availability: The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Author contributions:

Ayush K Sharma- Conducting research, data analysis, framing and writing.

Simranpreet Kaur Sidhu- Establishing experiment and data collections.

Simon Riley – Data analysis and writing.

Winniefred Griffin- Conducting experiment and resourcing.

Lincoln Zotarelli- Supervising and writing.

Lakesh K. Sharma- Supervising, framing research, and writing.

Competing interests

The author(s) declare no competing interests.

Compliance statement

The use of plants in the present study complies with international, national and/or institutional guidelines.

The appropriate permissions and/or licences for collection of plant specimens were taken.

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Sulfur Source Effects on Soil Sulfur Concentration, Vegetation Indices, Biomass, and Sulfur Uptake in Potato

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Abstract

Figures

Introduction

Material and Methods

Experimental site

Treatments and Experimental Design

Weather data

Soil data

Vegetation Indices (VIs)

Biomass

Sulfur Uptake

Statistical analysis

Results

Soil Sulfur concentration

Vegetation indices (VIs) and Individual bands

Biomass

Sulfur Uptake

Discussion

Sulfur source and soil

Potato responses to sulfur sources and rates with VIs:

Sulfur Sources and Biomass production

Sulfur sources and sulfur uptake

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

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