Impact of ultrasound as a pretreatment on the malting properties of Ragi and foxtail millet

Introduction

Research on millets, specifically Finger millet or Ragi (Eleusine coracana) and Foxtail millets or Kangni (Setaria italica), has gained popularity due to their high nutritional value and suitability for developing healthy foods rich in dietary fibre, bioactive compounds, antioxidants, and other minerals, while also demonstrating climate-resilient production [1][2][3][4][5] . Malting improves nutrient bioavailability, protein digestibility, phenolic content and antioxidant activity. However, a longer soaking time causes the leaching of nutrients and promotes microbial growth [6][7][8] .The tough seed coats and antinutrients of millet increase soaking time, affect germination and reduce nutrient bioavailability [9][10][11] . To tackle these limitations, ultrasound pretreatment emerged as a clean and green novel technology that is effective in accelerating the hydration and germination of seeds. Ultrasound works through acoustic cavitation, where the formation and collapse of microbubbles create high-pressure, high-temperature zones, enhancing mass transfer, softening the seed coat, increasing membrane permeability, and stimulating early metabolic and enzymatic activity [12][13][14][15][16] . In Barley, 20 kHz sonication improved germination yield by 4-6.5% reducing germination time by 45% [17] . Milk thistle seeds treated with a 24kHz, 400W probe system showed nearly double root length and significantly improved vigour indices [18] . Studies also showed improved germination in wheat, mung bean, lentil, adzuki bean, tomato, kidney bean, chickpea, peanut and soyabean under bath frequencies of 25-45kHz due to increased permeability and enzyme activation [19][20][21][22][23] . Ultrasound pretreatment of the millet seeds thus has the potential to affect the hard seed coats and improve hydration and germination. To study hydration, empirical models such as the Peleg, Page, Weibull, and Midilli models are widely used in food grains [24][25][26][27] . These models are used extensively to estimate hydration rate constants, equilibrium moisture uptake, and the entire hydration behaviour of many grains; however, limited scientific work is available on ultrasoundassisted hydration and malting of ragi and foxtail millet, where a probe sonicator is used for pretreatment. Therefore, this study aims to investigate the influence of ultrasound pretreatment of millet seeds using a probe sonicator and to study the hydration and malting behaviour using different kinetic models, as well as analysing germination traits, such as germination, dormancy, and root-shoot development, to identify the optimal ultrasound treatment under our experimental design.

Materials and Methods

Finger Millets (Ragi) and Foxtail Millets (Kangni) were collected from a local farmer in Jajpur, Odisha, and Uttar Dinajpur, West Bengal, India, respectively. The initial moisture content of finger millet was found to be 6.5%, and that of foxtail millet was 5.5%, as calculated using a moisture analyser (Aczet MB-50). The millets were treated with ultrasound using a probe sonicator (PRO Scientific, Model PRO656, Touchscreen Series, USA), as shown in Fig. 1, equipped with a 6mm titanium probe and operating at a frequency of 25kHz. A total of eight treatments, as shown in Table 1, were designed using two amplitudes (20% and 40%) and two treatment times (60 and 120 seconds), applied in a pulsed manner (3 seconds on and 6 seconds off) mode. Seeds (0.005kg) in 0.08 L of distilled water were treated in a beaker at a temperature of 298 K. The distance between the probe tip and the samples was maintained at more than 4 cm, and the probe was immersed 2 cm into the water. For amplitudes of 20% and 40%, the input power was 130W and 260W, respectively. The change in temperature was 95.59 K for 60s and 49.79 K for 120s. The power densities were 1194.84 W/L for a 60s treatment and 597.42 W/L for a 120s treatment, showing that short treatments delivered higher energy for this experimental design. Output acoustic power and power densities were quantified calorimetrically using temperature rise during treatment and treatment time [28] . Ultrasound-pretreated seeds were soaked (12h) and germinated (7 days). During soaking, changes in weight were checked at 2-hour intervals until 12 hours using an analytical balance. The 24 th hour reading was also taken for analysis. For model fitting, the moisture content at each interval on a dry basis% was calculated using the mass balance method [29] , considering the initial weight (5g) and initial moisture contents. This study employed the empericals modelsthe Peleg Model, M_t= M_0+ t/(K_1+K_( 2 to explain the hydration behaviour and soaking time needed for the millets. Here, M t is the moisture content at time t, M 0 is the initial moisture content, K shows the rate constant, M e is the equilibrium moisture content, n is a dimensionless empirical exponent, α is the scale parameter (time to reach ~63.2% of total change), and β is the shape parameter. The moisture ratio (MR) was calculated as , where M e is the 24 th hour moisture content. A non-linear least square method with a trust-region-reflective algorithm was used in MATLAB to estimate model parameters (Fig. 3). The treated samples were compared with the two control samples of Ragi (R) and Foxtail (F) millets. On the 7th day of germination, seed viability (SV), root length (RL), and shoot length (SL) were recorded, and the seeds were then kilndried at 45 °C for 6 hours. The seed weight (SW), root weight (RW) and shoot weight (SW) were collected for analysis. The entire data was collected in triplicate to minimise the errors. Table 2 shows the calculated germination rate (GR %), dormancy rate (DR %), germination capacity (GC%), malting loss (ML%), malting yield (MY%) and seed vigour indexes (SVI-I AND SVI-II) [30,31] .

Fig 1:

The figure illustrates the method of ultrasound treatment using a probe and germination.

Results and Discussions Empirical Model Analysis

Both millets exhibited an initial rapid uptake, followed by slower hydration towards equilibrium (Fig. 3). Ultrasound pretreatment enhanced the kinetic behaviour observed in the analysis of the empirical model fits. Table 1 shows that the Midilli model outperformed others with R 2 (0.9972 to 0.99996) and RMSE (0.0017). The parameters K 4 decreased markedly under optimal conditions from 0.957 in the control sample of Ragi to 0.0586 in Treatment 2, and from 0.8058 in the control foxtail to 0.338 in Treatment 6, indicating faster moisture uptake. Diffusion. The exponent n, within the range of 0.49-0.78, indicated a mixed Fickian and non-Fickian transport mechanism, with ultrasound yielding higher values of n, indicating faster hydration. The Peleg parameters supported the acceleration of initial hydration with ultrasound, reducing K1 from 1.936 in the R-control to the lowest value of 1.580 in Treatment 3, and in foxtail from 0.475 in the F-control to 0.475-0.798 across all treatments, confirming the enhancement of initial water uptake. K 2 of 0.294 in F-control to 0.249 in Treatment 8 indicated a faster approach to equilibrium. In the page model, K 3 increased under ultrasound from 1.329 in Treatment 3 to 0.814 in Treatment 7, and discussion exponents were higher in treated seeds (n = 0.71-0.78 in foxtail, showing improved water uptake. The Weibull shape parameters (α) decreased in the most responsive treatments (e.g., α = 0.88 in 3-20%120s, α = 1.15 in F-control, α = 1.27-3.86 in treated foxtail), consistent with faster early-phase hydration under acoustic cavitation and structural modification. Hence, these model parameters show that the ultrasound pretreatment accelerates both the initial absorption phase (lower Peleg K₁, higher Page K₃) and the later diffusion-controlled phase (higher Midilli n, lower Peleg K₂). The exceptionally high Midilli R² values (>0.998 for most treatments and 0.999956 for F-8) confirm that this model most effectively captures the combined exponential and linear transport behaviour induced by ultrasound. Using the Midilli model and defining hydration completion as 95% of equilibrium moisture (MR = 0.05), the model gave the lowest time to reach 95% hydration at Treatment 3, where t95 =5.1609 represents a 28.075% reduction compared to the control ragi, and for foxtail greatest reduction was for 7-20%120s, where t 95 =7.4224 gave a 29.89% reduction.

Germination Analysis

Depending on exposure time and amplitude, ultrasound enhances the germination performance (Table 2). Treatment 2 produced the best germination performance, with GR% increasing from 51.11% in the control to 71.11%, while reducing dormancy from 48.89% to 28.89%. This increased the GC% from 2.22% to 42.22%, accompanied by the highest SVI-I (590.22) and SVI-II (0.144), indicating better seedling development. A comparable response was observed in foxtail millet, where Treatment 6 enhanced the germination rate from 63.33% to 75.56%, reduced dormancy by 12.22 percentage points, and yielded the maximum germination capacity (51.11%), with the highest SVI-I of 414.93, indicating better seedling growth and mass. Thus, the 60s treatment consistently performed better, suggesting that short-time, moderate-intensity sonication pulses can also be used to enhance germination and soaking of seeds under the stated experimental conditions for Ragi and Foxtail millet seeds.

Conclusions

This study explains how ultrasound pretreatment can be used as a rapid, chemical-free method to non-thermally treat seeds, thereby enhancing soaking and germination during the malting of minor millets, including Finger and Foxtail. Empirical modelling revealed an acceleration of water uptake by reducing Peleg constants and improving Weibull α, confirming faster hydration under the 60s treatment of our experimental design. These improvements further enhanced germination performance with 40% amplitude and 60s treatments giving the highest GR and strongest SVI for both ragi and foxtail. The convergence of empirical modelling and germination outcomes demonstrated that moderate intensity, a short pulse of treatment, and a short time are practical and scalable pretreatments for seeds, reducing soaking time and enhancing germination, which will clearly benefit millet processing and sustainable agriculture.

Acknowledgement

I acknowledge the School of Community Science and Technology, IIEST, for providing the laboratory research facilities and the Indian Institute of Engineering Science and Technology, Shibpur, Howrah, West Bengal, for providing the fellowship.

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