Optimizing sulphur management for sugarcane grown in sulphur-deficient Inceptisols of Odisha, India coastal plains

Sugarcane is an important agricultural crop for industrial application especially for sugar industries. The production of sugarcane is declining day by day due to the low soil fertility status. Sulphur (S) is one of the important secondary macronutrients responsible for enhancing the quality and yield of sugarcane by keeping a good fertility status. An experiment was conducted on sulphur management in sulphur deficient sugarcane grow soil. The experiment was laid out for three years with application of S at 60 kg ha^-1 through two different sources of sulphur like gypsum and elemental S. The result revealed the highest (0.49%) concentration of nitrogen in the trash was observed in STD+ Gyp_{15 + 30 + 15} (T₁₀), which also corresponded to the highest nitrogen uptake of 81.3 kg ha⁻¹. The highest (0.21%) phosphorus concentration was estimated in STD+ S^{015 + 30 + 15}(T₆), with uptake of 31.71 kg ha⁻¹. The control treatment had the lowest phosphorus and nitrogen uptake in trash. The highest sulphur concentration in the trash (0.19%), resulting in a total sulphur uptake of 31.54 kg ha⁻¹ in STD+ Gyp_{15 + 30 + 15.} The pH decreased in the post-harvest soil after three years of continues cropping irrespective of the treatment’s indicating slight acidification of soil in all the treatments. Irrespective of the treatments compared, available N in postharvest soil decreased from an initial 265 kg ha^-1 to 240 kg ha^-1 in the control. The organic carbon status was enhanced in all the treatments except STD. The split application of Sat 60 kg h^-1 enhanced soil nutrients status with improved microbial activity. The split application of 60 kg S ha^-1 at basal, 40 days after sowing and 80 days after sowing enhanced the soil fertility.

1 Introduction

Sugarcane (Saccharum officinarum L.) cultivation is contributing significantly to the nation’s sugar and allied industries. India is the second largest producer of sugarcane after Brazil worldwide (1). Nearly 80% of global sugar demand is fulfilled by sugarcane (2). Sugarcane is also an essential crop for food and energy production (3). The current status of soil health has emerged as a significant issue for achieving optimum sugarcane production. The widespread deficit of sulphur in Indian soil is mostly attributed to intensive farming techniques, the growth of high yielding cultivars, soil erosion, climate change, erratic rainfall patterns, the use of high analysis sulphur-free fertilisers, and carelessness towards sulphur replenishment (4). Approximately 70% of Odisha soil is deficient in available sulphur out of which 29.5% of soil is acutely S deficient (5).

The efficient sulphur management in sugarcane will contribute to increased sugar production, sugar quality and biomass yield. Sulphur is an important growth-limiting plant nutrient, and regulates absorption of other nutrients such as N, P, K, Mo, Zn, Fe, Se and B (6, 7). In nature and agriculture-based ecosystems sulphur is one of the most critical secondary macronutrients which ensure the appropriate nourishment and development of several plants and microorganisms (8). Sulphur is a constituent element in various proteinaceous amino acids such as methionine, cysteine, glutathione, vitamins (biotin and thiamine), phyto-chelatins, chlorophyll, coenzyme A and S adenosyl-methionine (9). Also, sulphur is discovered in photosynthetic membranes as sulfolipids (10). The Lack of sulphur in plants interferes with the growth, development, disease combating ability, and functionality of plants and has a tremendous influence on the nutritional quality of crops (11).

This is crucial for maintaining crop quality and yield, as sulphur deficiency can lead to reduced protein content and overall plant vigour. Sustainable sulphur management can enhance soil health by promoting the beneficial microbial activity that is essential for nutrient cycling (12). This includes the transformation of organic sulphur into forms that are more readily available to plants (13). Sulphur application positively influences microbial properties in the soil. The addition of sulphur can affect soil chemical properties such as pH and electrical conductivity (EC). The judicious use of sulphur fertilizers is important for maintaining soil quality. The integration of sulphur with fertilizer applications can lead to improved soil fertility and health, which is crucial for sustainable agricultural practices. The management of S in sugarcane leads to sugar yield upto8.47 t ha⁻¹ (14).

As much of the research information on sulphur is largely scattered, in this study, an attempt has been made towards balanced fertilization beyond NPK in sugarcane. In this study 60 kg S ha^-1 was taken and applied with different sources and time keeping total doses of S fixed during the cropping period to find out the appropriate split dose and sources for optimizing the soil health. Keeping this in view an investigation entitled “Influence of Sulphur Management on Sugarcane Grown Sulphur Deficient Inceptisols under East and South Eastern Coastal Plain Zone of Odisha, India” has been undertaken to study the impact of sulphur management options on nutrient uptake and soil physico-chemical and biological properties.

2 Materials and methods

2.1 Experimental details

The experiment was carried out for three years from 2022–2024 at Sugarcane Research Station, Odisha University of Agriculture and Technology, Nayagarh, Odisha, India, situated at Latitude – 19⁰54' -20⁰32 'N, Longitude - 84⁰29 ' - 85⁰27 'E and 118m above sea level. The soil order of the experimental site was Inceptisols having near neutral pH (6.54), low organic carbon (4.53 g kg^-1) available phosphorus (13 kg ha^-1), sulphur (8 kg ha^-1), medium in available nitrogen (265 kg ha^-1), and potassium (199 kg ha^-1). The bulk density of initial soil was 1.39 Mg m^-3, particle density 2.57 Mg m^-3, porosity 54.1% and water holding capacity 46%. The soil was classified as Inceptisols and the suborder was Ustepts. The experiment consisted ten (10) treatments and three (3) replications. The experiment was laid out with each treatment of 36m² area and the total gross area of the experiment was 1555 m². The treatments consisted of two sources of sulphur such as gypsum and elemental sulphur applied at 60 kg ha^-1 both in split as well as blanket application. The treatments were T₁: Absolute Control (No external input), T₂: soil test dose of fertilizers (STD), T₃: application of STD with at 60 S kg ha^-1 as basal through elemental S (S⁰) (STD+S⁰⁶⁰), T₄: application of STD with Sat 60 kg ha^-1 in two splits as 30 kg as basal and 30 kg at 40 days after planting (DAP) through S⁰(STD+S^{030 + 30}), T₅: application of STD with Sat 60 kg ha^-1 in two splits as 15 kg as basal and 45 kg at 40 DAP through S⁰ (STD+S^{015 + 45}), T₆: application of STD with Sat 60 kg ha^-1 in three splits as 15 kg as basal, 30 kg at 40 DAP and 15 kg at 80 DAP through S⁰(STD+S^{015 + 30 + 13}), T₇: application of STD with S at 60 S kg ha^-1 as basal through Gypsum (GYP) (STD+Gyp₆₀), T₈: application of STD with Sat 60 kg ha^-1 in two splits as 30 kg as basal and 30 kg at 40 DAP through GYP (STD+ Gyp_{30 + 30}), T₉:application of STD with Sat 60 kg ha^-1 in two splits as 15 kg as basal and 45 kg at 40 DAP through GYP (STD+ Gyp_{15 + 45}), T₁₀: application of STD with Sat 60 kg ha^-1 in three splits as 15 kg as basal, 30 kg at 40 DAP and 15 kg at 80 DAP through GYP (STD+ Gyp_{15 + 30 + 13}).

The experiment was carried out for three years 2022, 2023 and 2024, the treatments were imposed every year as per the treatment details. Representative composite soil samples from 0–15 cm were taken before the starting of experiment and treatment wise soil samples were taken after the completion of third year of the experiment. Form each treatment 5 samples were taken and the sample size was reduced to 500 g by following the mixing and quartering process. The un-processed fresh soil samples were taken for microbial properties. For physico-chemical parameters, samples were air dried and ground with a wooden hammer followed by sieved through a 2 mm sieve.

2.2 Methods of plant analysis

The plant samples were taken during harvest of the crop, ten samples of the cane (middle portion) and trash (apical part of the sugarcane plant) from each treatment were collected. Both cane and trash samples were dried in a hot air oven followed by ground and kept with proper labelling for further chemical analysis. For nitrogen analysis, 1 g of processed plant sample was taken in the Kjeldhaltube and 5 ml of concentrated H₂SO₄ and 3g of digestion mixture, 1g of salicylic acid was added and kept overnight. The sample with the Kjeldhal tube was kept on the digestion unit of the Kelplus nitrogen auto analyser, after digestion the samples allowed to cool followed by distillation and titration with 0.2N H₂SO₄ and calculated the N concentration (15). For P, K, Ca and Mg content of the plant sample, 1g of processed oven dried samples were taken in the 150ml conical flask, 5 ml of diacid was added and kept overnight. The conical flasks with the sample were digested on the hot plate. After digestion the conical flasks were rinsed with distilled water and filtered to a 50ml volumetric flask through Whatman No 1 filter paper and stored in the refrigerator for further analysis. The phosphorus content in plant tissue was by the vanadomolybdate method using spectrophotometer at 470nm wavelength (16). The potassium was estimated by using a flame photometer (16). Plant sulphur was estimated by the turbidimetric method (16). The Ca and Mg of plant samples were determined by the versenate titration method (16). The nutrient uptake was calculated by the following formula (17).

$$Nutrient Uptake (kg h{a}^{-1})=\frac{Nutrient concentration (\%)}{Yield (q h{a}^{-1})}$$

2.3 Methods of soil analysis

2.3.1 Physico-chemical properties

The soil texture was determined by Bouyoucos Hydrometer method (18) as outlined by Piper (19). Bulk density was calculated as the dry weight of soil per unit volume of the core collected by the core sampler in the field (20). Particle density was determined by the pycnometer method, Flint and Flint (21). The porosity was calculated by the bellow mentioned formula. Keen Raczkowski boxes were used for the measurement of the maximum water holding capacity of soil as outlined by Piper (19).

$$\text{Porosity}= (1-Bulkdensity/Particledensity)X 100$$

The pH and electrical conductivity (EC) of soil were determined by taking a 1:2.5 ratio of soil: water in a 50 ml beaker and intermittent stirring was done for 30 min. The pH and electrical conductivity (EC) of the suspension were measured by a glass electrode digital pH meter and EC meter respectively as described by Jackson (16).

The organic carbon content was estimated by taking 1g processed soil in a 500ml conical flask, 10 ml of 1N K₂Cr₂O₇ and 20 ml of H₂SO₄ was added to it and kept for 30 min. the distilled water of 200 ml was added to the conical flask and waited tiling flask become cool followed by titrated against 0.5N Ferrous ammonium sulphate using ferroin indicator (22). Available nitrogen (N) was estimated by the alkaline KMnO₄ method using the N-auto analyser (23). Available P was determined by using Bray’s P-1 extract (0.03 N NH₄F + 0.025N HCl) method (24). Available K of the soil was analysed by the neutral normal ammonium acetate extraction method (16). Available sulphur (S) was estimated by turbidimetric method (25). Exchangeable Ca and Mg were estimated through the Versenate titration method (16).

2.3.2 Biological properties

The microbial population of the fresh soil of 0-15cm depth was collected aseptically and kept in a zip locked polythene bag with proper labelling. The population was enumerated by using serial dilution followed by the plate count method. Microbial Biomass Carbon was analysed by following the chloroform fumigation method (26). Arylsulphatase activity was estimated by using the method given by Browman and Tabatabai (27). Dehydrogenase activity was estimated by using the TTC-TPF method given by (28). The β-glucosidase activity was determined colorimetrically, following the procedure as given by Browman and Tabatabai (27).

2.4 Statistics designs

The experiment was laid out using a randomised block design (RBD), consisting of 10 treatments and 3 replications. The data were calculated using the formula of RBD for ANOVA followed by Gomez and Gomez (29). The graphs were created and Duncan’s Multiple Range Test was performed by using R software (Version: R-4.5.1).

3 Results

3.1 Influence of sulphur management on N and P concentration and uptake

The data related to nutrient concentration and uptake of nitrogen and phosphorus have been presented in Table 1. The nitrogen concentration in sugarcane trash was less (ranging from 0.25 to 0.49%) than its cane ranging from 0.32 to 0.74%. The highest concentration (0.49%) of nitrogen in the trash was observed in STD+ Gyp15 + 30 + 13 (T₁₀), which also corresponded to the highest nitrogen uptake of 81.3 kg ha⁻¹. TheT₆showed similarly high nitrogen content in trash (0.47%) with an uptake of 71.0 kg ha⁻¹, indicating a strong nutrient uptake capacity. The treatment T1 recorded the lowest nitrogen concentration in trash (0.25%) and uptake (20.0 kg ha⁻¹), reflecting poor nitrogen absorption in this treatment. Nitrogen concentration in the cane was significantly higher in T₁₀ (0.74%), leading to a total uptake of 194.6 kg ha⁻¹, the highest of all treatments. This demonstrates the superior nitrogen assimilation by plants under T₁₀. TheT₆and T₅ also showed higher nitrogen uptake in cane (191.5 kg ha⁻¹ and 167.6 kg ha⁻¹, respectively), suggesting that these treatments promote efficient nitrogen utilization. The treatment T₁ had the lowest nitrogen uptake in cane (43.2 kg ha⁻¹), corresponding with its lower trash uptake, showing minimal nitrogen absorption overall. TheT₁₀ showed the highest total nitrogen uptake (276 kg ha⁻¹), followed by T₆ (262 kg ha⁻¹) and T₅ (230 kg ha⁻¹). The control treatment (T₁) had the lowest total nitrogen uptake (63 kg ha^-¹), showing a stark contrast in nutrient absorption efficiency between T₁ and the top-performing treatments. Supplementation of S in soil helped better uptake and utilization of other nutrients like N, especially with supplementation of S with gypsum than elemental sulphur.

Table 1

Table 1. Influence of sulphur management on nitrogen and phosphorus concentration and uptake pooled over three years.

The concentration of P in sugarcane trash was less (ranging from 0.09 to 0.23%) than in the cane (ranging from 0.11 to 0.29%). The treatment of T₁₀had the highest phosphorus concentration in the trash (0.23%), leading to a trash uptake of38.18 kg ha⁻¹, indicating high P absorption efficiency. TheT₆and T₅ also showed high phosphorus concentration (0.21% and 0.18%, respectively), with uptake values of 31.71 kg ha⁻¹ and 26.1 kg ha⁻¹.TheT₁ had the lowest phosphorus uptake in trash (7.2 kg ha⁻¹), reflecting minimal phosphorus availability or absorption in this treatment. TheT₉ and T₆followed with cane uptakes of 63 kg ha⁻¹and67 kg ha⁻¹, respectively. The T₁ again had the lowest phosphorus uptake (15 kg ha⁻¹), with only 0.11% P concentration in the cane. The treatment ofT₁₀ had the highest total phosphorus uptake (114 kg ha⁻¹), followed by T₆ (98 kg ha⁻¹) and T₉ (92 kg ha⁻¹). The T₁ showed the least phosphorus absorption, with a total uptake of 22 kg ha⁻¹, reflecting poor P uptake efficiency. The gypsum integrated practice proved superior to the elemental sulphur source.

3.2 Influence of sulphur management practices on potassium and sulphur concentration and uptake by sugarcane crop

The table presents data (Table 2) on potassium (K) and sulphur (S) concentration and uptake in the trash and cane components of sugarcane for different treatments (T₁–T₁₀). Both concentration (%) and uptake (kg ha⁻¹) are measured to assess the efficiency of nutrient absorption by plants. The sugarcane trash contained less K (ranging from 0.22 to 0.55%) than the cane (ranging from 0.38 to 0.72%). The treatment, T₁₀ had the highest concentration of potassium in the trash (0.55%), resulting in an uptake of 91 kg ha⁻¹, indicating efficient potassium absorption. TheT₆ and T₉also demonstrated high potassium uptake (79 kg ha⁻¹ and 80 kg ha⁻¹, respectively) with similarly high concentrations (0.52% for both). The control practice had the lowest uptake of 18 kg ha⁻¹, with a concentration of only 0.22%, showing minimal potassium absorption in untreated plants. T₁₀also led in potassium uptake in the cane (189.4 kg ha⁻¹), with a concentration of 0.72%, confirming superior potassium absorption in this treatment. T₆ and T₉ followed with cane uptakes of 183.5 kg ha⁻¹ and 170 kg ha⁻¹, respectively. The control had the lowest potassium uptake in the cane (47.3 kg ha⁻¹), with a concentration of 0.35%, indicating poor potassium assimilation without nutritional supplementation. The control treatment (T₁) showed the least total potassium uptake was 65 kg ha⁻¹, highlighting the stark difference in potassium absorption efficiency between T₁ and the enhanced treatments.

Table 2

Table 2. Influence of sulphur management on potassium and sulphur concentration and uptake pooled over three years.

The concentration of sulphur was lower in sugarcane trash (ranging from 0.05 to 0.19%) than in its cane (ranging from 0.09 to 0.29%). The highest sulphur concentration in the trash (0.19%), resulting in a total sulphur uptake of 31.54 kg ha⁻¹, demonstrating the superior sulphur absorption capacity in T₁₀. The control had the lowest sulphur uptake in trash (4 kg ha⁻¹), with a concentration of 0.05%, reflecting poor sulphur absorption. The highest sulphur uptake by the cane (76.27 kg ha⁻¹) with a concentration of 0.29% shows effectiveness of sulphur assimilation. The lowest sulphur uptake in cane (12.15 kg ha⁻¹), with a concentration of 0.09%, consistent with its poor nutrient absorption across parameters (T₁).

Among four important nutrients, K uptake was highest (ranging from 65 to 28 kg ha^-1) followed by N (ranging from 63 to 276 kg ha^-1), P (ranging from 22 to 114 kg ha^-1) and S (ranging from 16 to 108 kg ha^-1). Integration of S sources with soil test dose of fertilizers (STD) significantly influenced the uptake of major nutrients, particularly the gypsum rather than elemental sulphur. Split application of S specifically in the ratio of 1:2:1 (15 kg basal, 30 kg at 40days and last 15 kg at 80 DAP) proved superior to other split or lone basal applications.

3.3 Influence of sulphur management on soil chemical properties

The data related to postharvest soil properties have been depicted in Table 3. The initial pH was 6.54. Irrespective of the treatments, pH decreased indicating slight acidification of the soil. The initial EC was 0.04 dS m⁻¹. In the postharvest soil, the soluble salt content decreased in most of the treatments or maintained in gypsum added treatments. Overall, the EC levels remained relatively stable compared to the initial value. Irrespective of the treatments the soil organic carbon content was maintained at harvest stage. The initial N was 265 kg ha⁻¹, irrespective of the treatments compared, available N in postharvest soil decreased. It was decreased from initial 265 kg ha⁻¹ to 240 kg ha⁻¹ in control. The status turned from medium to lower level. The initial phosphorus content in soil was 13 kg ha⁻¹. Irrespective of the treatments, its status decreased and remained lower. Like the other two major nutrients, its status decreased irrespective of the treatments, but remained in medium status. The initial calcium level was 4.44 cmol P⁺ kg⁻¹ soil, which was adequate though its content decreased compared to the initial level, but maintained an adequate status. The initial magnesium content was 2.21 cmol P⁺ kg⁻¹ soil. It was adequate in status. In the postharvest soil, treatments exhibited values ranging from 2.01 to 2.14 cmol P⁺ kg⁻¹ soil, which was above critical level of 1 cmol(p⁺) kg^-1soil. The initial sulphur content was 8 kg ha⁻¹. Treatments received S maintained its status even at the harvest stage compared to the treatments not receiving it. content (10 kg ha⁻¹) and T₇ the lowest (5 kg ha⁻¹). This suggests some variability in sulphur availability compared to the initial value.

Table 3

Table 3. Influence of sulphur management practices on post-harvest soil of sugarcane crop after three years.

3.4 Influence of sulphur management on soil physical properties

The influence of sulphur management on soil physical properties has been presented in Table 4. The initial bulk density of soil was 1.39 Mgm^-3. After three years of sulphur management practices, it varies between 1.22 and 1.41 Mgm^-3. The lowest was observed in the package where sulphur at 60 kg ha^-1 was applied at basal through gypsum followed by STD+ Gyp_{30 + 30} and the highest (1.41 Mgm^-3) was recorded in STD treatment which was statistically at par with absolute control (1.40 Mgm^-3). The initial soil particle density was 2.57 Mg m⁻³ and it varied between 2.50 Mgm^-3 and 2.63 Mgm^-3. Unintegrated treatment (control) (2.63 Mgm^-3) and lone STD (2.62 Mgm^-3) treated soil maintained higher PD than all S integrated treatments. Gypsum integrated treatments maintained lower PD values than the elemental S source. The initial soil porosity was 54%. Irrespective of the treatments, the porosity in post-harvest soil decreased. The lowest (45.7%) was recorded in STD+ S^{015 + 45} and the highest (51.2%) was recorded in gypsum applied plots of the experiment. Elemental S source maintained less porosity than gypsum treated soil. Porosity in soil decreased with control and lone STD practices including treatments receiving S⁰ application but with gypsum sources. The initial soil WHC was 46% and reduced in the elemental S applied plots and increased in the gypsum applied plots.

Table 4

Table 4. Influence of sulphur management practices on post-harvest soil of sugarcane crop after three years.

3.5 Influence of sulphur management on soil biological properties

The initial bacterial count was 25 × 10⁵ cfu g⁻¹, with different treatments bacterial population increased in all the practices except in control with values ranging from 19 × 10⁵ to 53 × 10⁵ cfu g⁻¹, indicating an increase in microbial activity in most treatments compared to the initial count. The initial fungal count was 18 × 10³ cfu g⁻¹ (Figure 1). Treatments varied in fungal count number and ranged from 5 to 19 × 10³ cfu g⁻¹, with T₁ showing the lowest fungal count and T₃ the highest (34 × 10³ cfu g⁻¹), indicating varying effects on fungal populations. The initial actinomycetes count was 8 × 10³ cfu g⁻¹, with treatments receiving fertilizers application increased its population, ranging from 5 to 18 × 10³ cfu g⁻¹. The treatment T₁₀ had the highest count (18 × 10³ cfu g⁻¹), indicating a potential increase in actinomycete populations. The initial MBC was 126 μg C g⁻¹ dry weight soil. Treatments receiving fertilizers based on soil test and S application exhibited values between 98 and 225 μg C g⁻¹ dry weight soil, with T₁₀ showing the highest MBC (225 μg C g^-1 dry weight soil), indicating increased microbial activity and biomass compared to the initial state. The initial MBS was 25 μg S g⁻¹ dry weight soil. Treatments receiving STD based fertilizers with S application had higher MBS which ranged from 24 to 85 μg S g⁻¹ dry weight soil, with T₁₀ showing the highest value (85 μg S g⁻¹ dry weight soil), suggesting increased sulphur biomass (Table 5). The initial β-glucosidase activity was 35 µg pNP g⁻¹ h⁻¹, with treatments receiving STD based fertilizers, particularly S supplementation increased the enzyme activity ranging from 24 to 85 µg pNP g⁻¹ h⁻¹, indicating increased enzyme activity, particularly in T₁₀. The initial sulphatase activity was 56 mg S kg⁻¹ h⁻¹, with integrated treatments varying from 42 to 138 mg S kg⁻¹ h⁻¹, with T₁₀ showing the highest activity, indicating improved sulphur cycling. Gypsum integrated treatment had a greater influence over the elemental sulphur source. Application of fertilizers based on soil test had an advantage over the control practice.

Table 5

Table 5. Influence of sulphur management on soil biological properties after three years.

Figure 1

Figure 1. Influence of S management on soil microbial population after three years.

3.6 Correlation between post-harvest soil biological properties

The parameters related to microbial biomass (MBC and MBS) showed strong positive correlations with bacterial (Bact) and fungal (Fungi) counts, indicating that as microbial biomass increases, so does the population of bacteria and fungi in the soil. Actinomycetes (Act) also correlate positively with bacterial and fungal populations, highlighting their interdependence within the soil ecosystem (Figure 2). The correlation matrix shows consistently strong positive associations among all soil biological parameters, as indicated by the high r values displayed within the ellipses. Microbial groups such as bacteria, fungi, and actinomycetes are closely linked, with correlations ranging from r = 0.71 to 0.78, suggesting that increases in one microbial population are accompanied by similar increases in others. Microbial biomass carbon (MBC) also exhibits strong positive correlations with microbial populations (r = 0.83–0.92), while microbial biomass sulphur (MBS) shows similarly high correlations (r = 0.84–0.91). Enzyme activities are likewise strongly related to microbial biomass, with glucosidase showing correlations of r = 0.87–0.93 and sulphatase exhibiting values around r = 0.89–0.94. The high and consistent r values across the matrix highlight a tightly integrated soil biological system in which microbial abundance, biomass, and enzymatic activities function synergistically to support efficient nutrient cycling.

Figure 2

Figure 2. Correlogram of post-harvest soil biological properties.

4 Discussion

Elemental sulphur (S⁰) treatments generally cause a significant reduction in soil pH(soil acidification) compared to gypsum (Gyp) source (30). This could be attributed to elemental sulphur undergoes microbial oxidation in the soil, releasing sulphuric acid leading to soil acidification (31). Among treatment combinations, the single large dose of S⁰ application at 60 kg ha^-1 had an immediate and pronounced effect on soil pH, while split applications resulted in a gradual decline in soilpH, showing better control over acidification. Gypsum, being calcium sulphate by nature, has a more buffered and slower effect on soil pH (32) as compared to elemental sulphur. Gypsum tends to improve soil structure and leaching of salts without causing drastic acidification (33). However, elemental sulphur showed a moderate decline in soil pH but generally maintained a stable range, suggesting that gypsum is more suitable for maintaining pH around neutral levels rather than acidifying the soil (34). Split applications (such as 60 kg S in two splits at30kg at basal and 30kg at 40 DAPor 15kg at basal and 45kg at 40 DAP) for both sulphur sources tend to result in a smoother, more controlled acidification pattern (35). This can be particularly useful in managing soil pH for crops like sugarcane that benefit from slight acidification but are sensitive to large fluctuations in pH. The multi-stage applications (15 + 30 + 15) allow for sustained sulphur release (36) covering the growing period, providing a slow and steady pH adjustment. Where long-term pH management is desired, such split application become advantageous. The choice between elemental sulphur and gypsum depends on the desired pH outcome. For immediate pH reduction, elemental sulphur is more effective. However, if the goal is to maintain pH in a more controlled and gradual manner, gypsum, particularly in split applications is preferable. Regular monitoring of soil pH is crucial to avoid over-acidification (37), especially in treatments involving elemental sulphur. The split or multiple applications of sulphur help mitigating this risk while providing effective pH management.

The higher conductivity observed in gypsum treatments (T₇, T₈, T₉, T₁₀) suggested that gypsum’s solubility in water may facilitate quicker ion release, enhancing electrical conductivity more effectively than elemental sulphur. Treatments that utilized split applications (e.g., S⁰ (30 + 30) and Gyp (30 + 30)) generally showed stable conductivity levels, indicating that timing and method of application can influence nutrient availability and soil moisture dynamics. Over the period, the control treatment displayed the least variation, reinforcing the idea that without nutrient amendments, soil electrical conductivity remains low. Conversely, treatments with elemental sulphur and gypsum exhibited fluctuations, indicating their impact on soil chemistry over time.

The control practice (T₁) maintained a consistent growth measurement throughout the observation period, averaging around 4.53, which indicates that the absence of supplemented input did not negatively impact plant growth. In contrast, the added inputs (T₂ to T₁₀) displayed slight variations in growth measurements. Most treatments exhibited a gradual decline in growth values in the initial months, stabilizing towards the later stages. For instance, T₂ (STD) showed a marginal decrease from 4.53 to 4.50 by day 60, but remained relatively stable thereafter. Similarly, T₃ (STD + S⁰(60)) and T₄ (STD + S⁰(30 + 30)) also showed initial declines, with T₃ stabilizing around 4.47 by day 60. Interestingly, treatments involving gypsum (T₇ to T₁₀) had varying outcomes. The T₉ (STD + Gyp(15 + 45)) showed notable recovery towards the end of the observation period, reaching 4.56 by harvest time. T₁₀ (STD + Gyp(15 + 30 + 15)) had the highest measurement of 4.58 at harvest, indicating that this treatment will be beneficial for promoting plant growth in later stages.

This suggests that without adequate sulphur supplementation, plant growth declined as the crop matures, likely due to nutrient deficiencies affecting metabolic functions essential for biomass accumulation. The steady reduction in height also indicated a decline in overall crop vigor under sulphur-deficient conditions. This indicated that standard nutrient management practices provided the sugarcane crop with better growth conditions compared to the control practice. However, the decline after 60 days after planting suggests that even with the standard nutrient regime, additional sulphur might be required to sustain growth during later stages of development. Calcium is essential for soil structure and plant nutrition, so its behaviour in response to different treatments can significantly affect soil fertility and crop performance.

The study showed clear trends in the management of calcium in soils under different sulphur application strategies. The control (T₁) and standard (T₂) treatments demonstrated a steady decline in calcium levels, emphasizing the need for external calcium supplementation to prevent nutrient depletion over time.

Elemental sulphur treatments (T₃ to T₆) showed that sulphur, when applied in split doses, helped to stabilize and even improve calcium levels in the soil. The T₄ (S₀ 30 + 30) and T₆ (S⁰ 15 + 30 + 15) performed particularly well in maintaining calcium content, indicating that split applications optimize nutrient availability and uptake by the crop. Gypsum treatments (T₇ to T₁₀) generally outperformed elemental sulphur treatments in terms of calcium maintenance, as gypsum directly supplies calcium (38). The T₉ (Gyp 15 + 45) and T₁₀ (Gyp 15 + 30 + 15) showed the best performance, indicating that split applications of gypsum not only maintain but also enhance soil calcium levels, offering a consistent supply throughout the crop cycle. Magnesium is a vital nutrient for plant growth, and its availability in soil is critical for maintaining soil productivity. In control without any external nutrient supplementation, magnesium levels decrease due to crop uptake and potential leaching. The trends in the data indicate that different treatments significantly influence the parameter being measured. The control (T₁) shows a gradual decline over time, suggesting that no intervention leads to a reduction in the observed variable.

The fluctuations and eventual declines in all treatments except T₁ (control) suggest that the effects of the treatments diminish over time. These peaks are likely to be related to an early release or uptake of nutrients or other factors that enhance the parameter being measured. The subsequent decline in the values could indicate a depletion of resources or stabilization of the system after the initial treatment effect. Overall, the results indicated that the treatments effectively influenced various soil parameters compared to the initial measurements. The pH remained relatively stable, with slight fluctuations that suggest effective buffering capacity. The electrical conductivity and organic carbon levels were also maintained, indicating good soil health (39).

Physical parameters, such as bulk density and porosity, indicate improved soil structure and water retention capacity (40), particularly in T₇ and T₁₀, which could lead to better root development and crop growth. The increase in bacterial and fungal counts, along with microbial biomass, reflected enhanced soil microbial activity and health (41), contributing to nutrient cycling and organic matter decomposition through appropriate enzyme activity.

The elevated levels of β-glucosidase and sulphatase activity across treatments, especially in T₁₀, demonstrated enhanced soil enzymatic activity, which was vital for nutrient mineralization and overall soil fertility (42). The higher final plant heights in T₁₀, T₉, and T₈ may be associated with optimal nutrient levels, including higher nitrogen (N), phosphorus (P), potassium (K), and microbial biomass (MBC and MBS) as indicated in the previous data. These treatments also showed higher enzyme activity (beta-glucosidase and sulfatase), which was likely to enhance nutrient cycling and availability, further promoting growth. The T₁ and T₃ had consistently lower growth rates across the study. This was related to lower nutrient availability or microbial activity in these treatments. The T₁ had the lowest microbial biomass and beta-glucosidase activity, which could limit nutrient turnover and availability to plants. Treatments with higher microbial biomass and activity (e.g., T₆, T₈, T₉, T₁₀) exhibited better plant growth. Microbial activity, particularly of bacteria and actinomycetes, is known to improve nutrient availability, supporting better plant growth. The high correlation between microbial activity, enzyme production, and plant height suggested that biological processes in the soil, such as nutrient cycling and organic matter breakdown, were critical for maximizing plant growth (43). Treatments with higher nitrogen and potassium content (T₁₀, T₉, T₈) generally outperformed those with lower nutrient levels (44).

5 Conclusion

The practice of adopting soil test-based fertilizers application with S at 60 kg ha^-1 in three splits viz., 15 kg ha^-1 as basal, 30kg ha^-1 at 40 days after planting and rest 15kg at 80days after planting through gypsum is the best approach to maintain the soil fertility. Irrespective of the treatments available N in postharvest soil decreased. It decreased from an initial 265 kg ha⁻¹ to 240 kg ha⁻¹ in the control. The soil physical properties like bulk density decreased by 10% and water holding capacity increased by 20% in comparison to the initial soil. The above sulphur management practice regulated soil pH for a longer period of time covering the active growth period of the crop, maintained optimum soil soluble salts content by in supplying need-based plant nutrients and maintained optimum soil physicochemical and biological properties for sustainable production.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding authors.

Author contributions

RM: Conceptualization, Formal Analysis, Investigation, Methodology, Software, Writing – original draft, Writing – review & editing. DS: Conceptualization, Data curation, Formal Analysis, Methodology, Project administration, Resources, Software, Supervision, Writing – original draft, Writing – review & editing. SMa: Formal Analysis, Software, Writing – original draft, Writing – review & editing. PS: Conceptualization, Data curation, Formal Analysis, Software, Validation, Writing – original draft. JP: Data curation, Formal Analysis, Investigation, Methodology, Project administration, Supervision, Writing – original draft. SMo: Formal Analysis, Investigation, Methodology, Project administration, Resources, Validation, Writing – original draft, Writing – review & editing. KP: Conceptualization, Data curation, Formal Analysis, Investigation, Software, Writing – original draft. AN: Formal Analysis, Resources, Supervision, Visualization, Writing – original draft. SS: Funding acquisition, Methodology, Software, Validation, Visualization, Writing – review & editing. NP: Data curation, Formal Analysis, Funding acquisition, Project administration, Resources, Software, Supervision, Visualization, Writing – original draft. SP: Data curation, Funding acquisition, Investigation, Software, Validation, Visualization, Writing – review & editing.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Acknowledgments

All authors thankful and acknowledge the infrastructure and financial support provided by Sugarcane Research Station, OUAT, Nayagarh for the field experiment. The authors are also grateful to the Department of Soil Science and Agriculture Chemistry, College of Agriculture, OUAT, Bhubaneswar for extending laboratory facilities for chemical analysis.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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The author(s) declare that Generative AI was not used in the creation of this manuscript.

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References

1. Jaiswal R, Mall RK, Patel S, Singh N, Mendiratta N, and Gupta A. Indian sugarcane under warming climate: A simulation study. Eur J Agron. (2023) 144:126760. doi: 10.1016/j.eja.2023.126760

Crossref Full Text | Google Scholar

2. Alokika A, Kumar A, Kumar V, and Singh B. Cellulosic and hemicellulosic fractions of sugarcane bagasse: Potential, challenges and future perspective. Int J Biol Macromolecules. (2021) 169:564–82. doi: 10.1016/j.ijbiomac.2020.12.175

PubMed Abstract | Crossref Full Text | Google Scholar

3. Carioca JOB and Leal MRLV. Ethanol production from sugar-based feedstocks. In: Moo-Young M, editor. Comprehensive Biotechnology (Second Edition). Elsevier. (2011). 3:27–35.

Google Scholar

4. Biswas BC, Sarkar MC, Tanwar S, Das S, and Kalwe SP. Sulphur deficiency in soils and crop response to fertilisersulphur in India. Fertiliser News. (2004) 49:13–8.

Google Scholar

5. Shukla AK, Behera SK, Prakash C, Tripathi A, Patra AK, Dwivedi BS, et al. Deficiency of phyto−availablesulphur, zinc, boron, iron, copperand manganese in soils of India. Sci Rep. (2021) 11:19760. doi: 10.1038/s41598-021-99040-2

PubMed Abstract | Crossref Full Text | Google Scholar

6. Udayana SK, Singh P, and Jaison M and Roy A. Sulfur: A boon in agriculture. Pharma Innovation J. (2021) SP-10:912–21.

Google Scholar

7. Fowler D, Smith RI, Canfield JB, Hayman G, and Vincent KJ. Changes in the atmospheric deposition of acidifying compounds in the UK between 1986 and 2001. Environ pollut (Barking Essex: 1987). (2005) 137:15–25. doi: 10.1016/j.envpol.2004.12.028

PubMed Abstract | Crossref Full Text | Google Scholar

8. Li Q, Gao Y, and Yang A. Sulfur homeostasis in plants. Int J Mol Sci. (2020) 21:8926. doi: 10.3390/ijms21238926

PubMed Abstract | Crossref Full Text | Google Scholar

9. Narayana OP, Kumar P, Yadav B, Dua M, and Johri AK. Sulfur nutrition and its role in plant growth and development. Plant Signaling Behav. (2023) 18:e2030082. doi: 10.1080/15592324.2022.2030082

PubMed Abstract | Crossref Full Text | Google Scholar

10. Maathuis FJ. Physiological functions of mineral macronutrients. Curr Opin Plant Biol. (2009) 12:250–8. doi: 10.1016/j.pbi.2009.04.003

PubMed Abstract | Crossref Full Text | Google Scholar

11. Kopriva S, Malagoli M, and Takahashi H. Sulfur nutrition: impacts on plant development, metabolism, and stress responses. J Exp Bot. (2019) 70:4069–73. doi: 10.1093/jxb/erz319

PubMed Abstract | Crossref Full Text | Google Scholar

12. Chaudhary S, Sindhu SS, Dhanker R, and Kumari A. Microbes-mediated sulphur cycling in soil: Impact on soil fertility, crop production and environmental sustainability. Microbiological Res. (2023) 271:127340. doi: 10.1016/j.micres.2023.127340

PubMed Abstract | Crossref Full Text | Google Scholar

13. Magnucka EG, Kulczycki G, Oksińska MP, Kucińska J, Pawęska K, Milo Ł, et al. The effect of various forms of sulfur on soil organic matter fractions and microorganisms in a pot experiment with perennial ryegrass (Lolium perenne L.). Plants. (2023) 12:2649. doi: 10.3390/plants12142649

PubMed Abstract | Crossref Full Text | Google Scholar

14. Singh A, Srivastava RN, and Singh SB. Effect of sources of sulphur on yield and quality of sugarcane. Sugar Tech. (2007) 9:98–100. doi: 10.1007/BF02956921

Crossref Full Text | Google Scholar

15. Nelson DW and Sommers LE. Determination of total nitrogen in plant material. Agron J. (1973) 65:109–12. doi: 10.2134/agronj1973.00021962006500010033x

Crossref Full Text | Google Scholar

16. Jackson ML. Soil Chemical Analysis. New Delhi: Prentice Hall of India Pvt. Ltd. (1973). p. 498.

Google Scholar

17. Reddy MSL, Mitra B, Sinha AK, Alshehri MA, Gaber A, and Hossain A. Organic and inorganic nutrient management in combination with rice residue retention influence the productivity and soil health of zero tillage wheat (Triticum aestivum L.). J Soil Sci Plant Nutr. (2025) 25:6661–77. doi: 10.1007/s42729-025-02555-0

Crossref Full Text | Google Scholar

18. Bouyoucos GJ. Hydrometer method improved for making particle size analysis of soils. Agron J. (1962) 54:464–5. doi: 10.2134/agronj1962.00021962005400050028x

Crossref Full Text | Google Scholar

19. Piper C. Soil and Plant Analysis. New York: International Public Inc. (1950).

Google Scholar

20. Black CA. Methods of Soil Analysis: Part I, Physical and Mineralogical Properties. Madison, Wisconsin: American Society of Agronomy (1965). 1572 p.

Google Scholar

21. Flint LE and Flint AL. Porosity. In: Methods of Soil Analysis. John Wiley & Sons Ltd., Hoboken (2002). p. 241–54. doi: 10.2136/sssabookser5.4.c11

Crossref Full Text | Google Scholar

22. Walkley AJ and Black IA. Estimation of soil organic carbon by the chromic acid titration method. Soil Sci. (1934) 37:29–38. doi: 10.1097/00010694-193401000-00003

Crossref Full Text | Google Scholar

23. Subbiah BV and Asija GL. A rapid procedure for the estimation of available nitrogen in soils. Curr Sci. (1956) 25:259–60.

Google Scholar

24. Bray RH and Kurtz LT. Determination of total organic and available forms of phosphorus in soils. Soil Sci. (1945) 59:39–45. doi: 10.1097/00010694-194501000-00006

Crossref Full Text | Google Scholar

25. Chesnin L and Yien CH. Turbidimetric determination of available sulphates. Soil Sci Soc America J. (1950) 15:149–51. doi: 10.2136/sssaj1951.036159950015000C0032x

Crossref Full Text | Google Scholar

26. Vance ED, Brookes PC, and Jenkinson DS. An extraction method for measuring soil microbial biomass C. Soil Biol Biochem. (1987) 19:703–7. doi: 10.1016/0038-0717(87)90052-6

Crossref Full Text | Google Scholar

27. Browman MG and Tabatabai MA. Phosphodiesterase activity of soils. Soil Sci Soc America J. (1978) 42:284–90. doi: 10.2136/sssaj1978.03615995004200020016x

Crossref Full Text | Google Scholar

28. Casida L, Klein D, and Santoro T. Soil dehydrogenase activity. Soil Sci. (1964) 98:371–6. doi: 10.1097/00010694-196412000-00004

Crossref Full Text | Google Scholar

29. Gomez KA and Gomez AA. Statistical Procedures for Agricultural Research. 2nd Edition. New York: John Wiley and Sons (1984). 680 p.

Google Scholar

30. Zhang D, Du G, Zhang W, Gao Y, Jie H, Rao W, et al. Remediation of arsenic-contaminated paddy soil: Effects of elemental sulfur and gypsum fertilizer application. Ecotoxicology Environ Saf. (2021) 223:112606. doi: 10.1016/j.ecoenv.2021.112606

PubMed Abstract | Crossref Full Text | Google Scholar

31. Hammerschmiedt T, Holatko J, Bytesnikova Z, Skarpa P, Richtera L, Kintl A, et al. The impact of single and combined amendment of elemental sulphur and graphene oxide on soil microbiome and nutrient transformation activities. Heliyon. (2024) 10:e38439. doi: 10.1016/j.heliyon.2024.e38439

PubMed Abstract | Crossref Full Text | Google Scholar

32. Kordlaghari MP and Rowell DL. The role of gypsum in the reactions of phosphate with soils. Geoderma. (2006) 132:105–115. doi: 10.1016/j.geoderma.2005.04.022

Crossref Full Text | Google Scholar

33. Bello SK, Alayafi AH, AL-Solaimani SG, and Abo-Elyousr KAM. Mitigating soil salinity stress with gypsum and bio-organic amendments: A review. Agronomy. (2021) 11:1735. doi: 10.3390/agronomy11091735

Crossref Full Text | Google Scholar

34. Tavakkoli E, Uddin S, Rengasamy P, and McDonald GK. Field applications of gypsum reduce pH and improve soil C in highly alkaline soils in southern Australia’s dryland cropping region. Soil Use Manage. (2022) 238:466–77. doi: 10.1111/sum.12756

Crossref Full Text | Google Scholar

35. Thomas A, Cosby BJ, Henrys P, and Emmett B. Patterns and trends of topsoil carbon in the UK: Complex interactions of land use change, climate and pollution. Sci Total Environment. (2020) 729:138330. doi: 10.1016/j.scitotenv.2020.138330

PubMed Abstract | Crossref Full Text | Google Scholar

36. Huang L, Yang X, Xie Z, Li S, Liang X, and Hu Z. Residual effects of sulfur application prior to oilseed rape cultivation on cadmium accumulation in brown rice under an oilseed rape–rice rotation pot experiment. Ecotoxicology Environ Saf. (2021) 225:112765. doi: 10.1016/j.ecoenv.2021.112765

PubMed Abstract | Crossref Full Text | Google Scholar

37. Geng N, Kang X, Yan X, Yin N, Wang H, Pan H, et al. Biochar mitigation of soil acidification and carbon sequestration is influenced by materials and temperature. Ecotoxicology Environ Saf. (2022) 232. doi: 10.1016/j.ecoenv.2022.113241

PubMed Abstract | Crossref Full Text | Google Scholar

38. Zhang D, Du G, Chen D, Shi G, Rao W, Li X, et al. Effect of elemental sulfur and gypsum application on the bioavailability and redistribution of cadmium during rice growth. Sci Total Environment. (2019) 657:1460–7. doi: 10.1016/j.scitotenv.2018.12.057

PubMed Abstract | Crossref Full Text | Google Scholar

39. Das BS, Wani SP, Benbi DK, Muddu S, Bhattacharyya T, Mandal B, et al. Soil health and its relationship with food security and human health to meet the sustainable development goals in India. Soil Secur. (2022) 8:100071. doi: 10.1016/j.soisec.2022.100071

Crossref Full Text | Google Scholar

40. Luo L, Lin K, Tao L, Luo C, Wang J, Duan T, et al. Effects of stand structure and soil depth on soil properties in Cryptomeria japonica plantations. Front For Glob Change. (2025) 8:1548485. doi: 10.3389/ffgc.2025.1548485

Crossref Full Text | Google Scholar

41. Devi NB, Singh LI, Yadava PS, and Khan MR. Shift in microbial biomass, soil and microbial stoichiometry in different land uses of Northeast India. Microbe. (2024) 3:100085. doi: 10.1016/j.microb.2024.100085

Crossref Full Text | Google Scholar

42. Kotroczó Z, Veres Z, Fekete I, Krakomperger Z, Tóth JA, Lajtha K, et al. Soil enzyme activity in response to long-term organic matter manipulation. Soil Biol Biochem. (2014) 70:237–43. doi: 10.1016/j.soilbio.2013.12.028

Crossref Full Text | Google Scholar

43. Solangi F, Zhu X, Solangi KA, Iqbal R, Elshikh MS, Alarjani KM, et al. Responses of soil enzymatic activities and microbial biomass phosphorus to improve nutrient accumulation abilities in leguminous species. Sci Rep. (2024) 14:11139. doi: 10.1038/s41598-024-61446-z

PubMed Abstract | Crossref Full Text | Google Scholar

44. Wang X, Shao X, Zhang Z, Zhong X, Ji X, Xiangbin Shi X, et al. Multi-nutrient fertilization-based analysis of fruit quality and mineral element composition during fruit development in Merlot wine grapevines. J Integr Agriculture. (2025) 24:1503–14. doi: 10.1016/j.jia.2024.04.032

Crossref Full Text | Google Scholar