Selection and incorporation of hydrocolloid for gluten-free leavened millet breads and optimization of the baking process thereof

Selection and incorporation of hydrocolloid for gluten-free leavened millet breads and optimization of the baking process thereof

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Journal Pre-proof Selection and incorporation of hydrocolloid for gluten-free leavened millet breads and optimization of the baking process thereof Subir Kumar Chakraborty, Nachiket Kotwaliwale, Surekha Ashok Navale PII:

S0023-6438(19)31220-4

DOI:

https://doi.org/10.1016/j.lwt.2019.108878

Reference:

YFSTL 108878

To appear in:

LWT - Food Science and Technology

Received Date: 2 April 2019 Revised Date:

2 October 2019

Accepted Date: 22 November 2019

Please cite this article as: Chakraborty, S.K., Kotwaliwale, N., Navale, S.A., Selection and incorporation of hydrocolloid for gluten-free leavened millet breads and optimization of the baking process thereof, LWT - Food Science and Technology (2019), doi: https://doi.org/10.1016/j.lwt.2019.108878. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

Leavened gluten-free millet bread

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Selection and incorporation of hydrocolloid for gluten-free leavened millet breads and optimization of the

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baking process thereof 1a

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1

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Subir Kumar Chakraborty , Nachiket Kotwaliwale , Surekha Ashok Navale 1

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Agro Produce Processing Division, ICAR - Central Institute of Agricultural Engineering, Bhopal, India

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College of Agricultural Engineering and Technology, DBS Konkan Agricultural University, Dapoli, India

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a

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Senior Scientist, Agro Produce Processing Division, ICAR – Central Institute of Agricultural Engineering,

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Nabibagh, Berasia Road, Bhopal, India. email - [email protected], Orchid: 0000-0002-1560-1728

Corresponding author

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Abstract

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Suitability amongst the hydrocolloids, - tragacanth gum, gum arabic, guar gum and xanthan gum to be used as

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an ingredient for mimicking the action of gluten was carried out based on gluten-free millet (pearl, little and

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kodo) bread quality in terms of expansion (cm), specific volume (mL/g) and textural characteristics. Xanthan

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gum was found to be the most suitable hydrocolloid for rendering an acceptable structure to the bread.

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Gluten-free leavened breads were made using central composite rotatable experimental design of response

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surface methodology with proofing time (Pt, 1.3 - 4.7 h), baking time (Bt, 32 - 48 min) and baking temperature

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(BT, 158 – 192 C) as input variables. Statistically significant (p<0.01) second order models were used to

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understand effect of variables upon the responses. Textural property of little millet flour bread was observed

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to be better amongst all the millet breads. Optimum conditions for little millet bread in terms of Pt, Bt and BT

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was 3.5 h, 48 min and 190 C, respectively; under these conditions this bread exhibited best expansion,

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springiness and hardness. 2-tailed paired t-test revealed that quality characteristics of bread prepared at

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model predicted values did not significantly (p<0.01) differ from that actually prepared under optimum

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condition.

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o

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Keywords: Bread quality; Gluten-free; Hydrocolloids; Kodo millet; Pearl millet; Little millet

1

Leavened gluten-free millet bread

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1. Introduction

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The world is witnessing an upsurge of consciousness among the consumers for nutritional and safety aspect of

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food like never before. Across the world, consumption of baked goods is common and widespread. Refined

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wheat flour (RWF) is the key ingredient in all such culinary preparations. RWF provides carbohydrate, protein

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and some minerals (magnesium, phosphorus, iron) but, it is failing the consumers on two counts, one - RWF is

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deficient in fibre and has high glycemic index (GI); two - RWF contains gluten, incidence of gluten intolerance

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causing allergic reaction for individuals resulting in inflammation of the small intestine leading to mal

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absorption of several important nutrients and intestinal mucosal damage. This is called coeliac disease, which

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does not have a pharmaceutical cure; initiation of clinical recovery is possible only by a strict adherence to

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gluten-free diet throughout the lifetime of the patient (Gallagher, Gormley, & Arendt, 2004).

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Millets are gluten free, high in fibre content and rich in minerals (Chakraborty, Singh, & Kumbhar, 2014). Fibre

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rich foods have low GI and can reduce the risk of postprandial oxidative stress (a factor for onset of several

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chronic diseases) (Jenkins, Josse, Wong, Nguyen, Kendall, 2007). Consumption of millets lessens the chance of

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cardio vascular diseases, certain forms of cancer, abnormal blood pressure, obesity and results in a healthy

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gastrointestinal tract (Jones and Larzelere, 2008). Also, bolstering gluten-free baked products with dietary

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fibres is helpful for coeliac patients as they have a low intake of fibres attributed to their gluten-free diet

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(Thompson, 2000).

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Gluten provides a plastic structure that entraps gases generated during proofing and temporarily binds water

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required to gelatinize starch. Hydration of proteins of gluten during dough formation and gelatinization of

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starch ensures the desirable structure of bread crumb. Millets do not contain gluten and bread made from

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gluten free dough pose a big challenge to any baker. Gluten-free bread suffers from structural and textural

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defects (Renzetti and Arendt, 2009). Millet doughs are liquid and similar to a batter because of an unstable

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starch and the existence of mutually repulsive forces between the starch granules (Onyango, Mutungi,

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Unbehend, & Lindhauer, 2010). The resultant incoherent structure is unsuitable for entrapping gases

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generated during batter mixing and proofing. Thus, the batter does not rise resulting in a bread with rigid and

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crumbly texture.

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Gluten-free doughs must show appropriate viscoelastic characteristics to enhance the acceptance of the final

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product by the consumer. Hydration during dough formation define the rheological properties of the gluten-

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free dough (Crockett et al., 2011). Adding the right volume of water can control quality aspects of gluten-free

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bread such as, - loaf specific volume and crumb hardness (Rozylo et al., 2015). Water-starch system relies on

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fragile intermolecular bonds for structural stability or the lack of it, hence the gluten-free dough has a low

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mixing tolerance and poor extensional property (Lazaridou, Duta, Papageorgiou, Belc, & Biliaderis, 2007).

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Adding an extra source of starch as an ingredient to gluten free bread formulation is widespread and well

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researched. It has been reported that tapioca starch inherits the polymeric substances that makes it a suitable

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gluten-free ingredient (Milde, Ramallo, & Puppo, 2012). It can reproduce the viscoelastic properties of gluten

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and can provide the structure to retain gases produced during proofing (McCarthy, Gallagher, Gormley,

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Schober, & Arendt, 2005).

2

Leavened gluten-free millet bread

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Characteristic properties of gluten-free dough, say millet dough, can be improved with the presence of

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hydrocolloids (Meza et al., 2011). Hydrocolloids exhibit a special function in gluten-free dough in order to help

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to mimic the gluten properties (Moreira, Chenlo, Torres, & Rama, 2014). The gel network structure of the

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hydrocolloids serves to stabilization of the gluten-free dough system by increasing the dough intermolecular

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viscosity (Houben, Höchstötter, & Becker, 2012) resulting in a higher gas retention during leavening and

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specific volume of breads (Mancebo, San Miguel, Martínez, & Gómez, 2015)

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A variety of hydrocolloids have been investigated for making good quality gluten-free bread, these include

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guar gum, xanthan, hydroxyl propyl methyl cellulose, methylcellulose, carboxy methyl cellulose, locust bean

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gum, and psyllium gum (Houben et al., 2012; Lazaridou et al., 2007). However, their utility and suitability is

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based on the objective purpose.

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This study envisages to develop leavened bread using a suitable hydrocolloid amongst tragacanth gum, gum

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arabic, guar gum and xanthum gum as an ingredient for mimicking the action of gluten. The bread made

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thereof has been evaluated on quality (expansion, specific volume and textural characteristics) aspects based

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on the varying baking conditions in terms of proofing time (Pt), baking time (Bt) and baking temperature (BT).

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2. Materials and methods

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2.1 Materials

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Based on the rheological studies conducted by Chakraborty, Kotwaliwale, & Navale (2018), the following

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millets were used for preparing gluten-free breads, - pearl millet (Pennisetum glaucum), little millet (Penicum

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milliare) and Kodo millet (Paspalum scrobiculatum). Kodo and little millet were donated by M.P. Vigyan Sabha,

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Bhopal, India (a non-government organization working in the tribal areas of Central India since 1985) as whole

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grain, dehusking was carried out by ICAR - CIAE millet mill. Pearl millet and other miscellaneous ingredients

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were purchased from the local market of Bhopal. Cleaned and dehusked millets were pulverized in an attrition

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mill. Hydrocolloids (Thomas Baker Pvt. Ltd., Mumbai, India) used for the present study were tragacanth gum,

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gum arabic, guar gum, xanthum gum.

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2.2 Hydrocolloids

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The hydrocolloids tragacanth gum, gum arabic, guar gum and xanthan gum were used in the present study.

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Separate series of experiments were conducted to select a hydrocolloid and its level (g), to be included as

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bread ingredient by comparing specific volume and texture profile of the millet bread developed using each

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hydrocolloid.

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2.3 Particle size distribution

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The results of rheological studies are affected by particle size of flour used for dough making (Servais, Jones, &

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Roberts, 2002). Availability of particle size allows comparison of rheological data across various researches

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(Fraiha, Biagi, & Ferraz, 2011). Particle size analysis (Mastersizer, Malvern Inc., Worcestershire, United

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Kingdom) of all the flours has been reported in terms of D[4,3] or the volume or mass moment mean or the De

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Broucker mean and as D[3,2] surface area moment mean or Sauter Mean Diameter (SMD). 4,3 =

∑ ∑

(1)

3

Leavened gluten-free millet bread

3,2 =

∑ ∑

(2)

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Where, d is diameter of sphere (µm) best representing the particle

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2.4 Bread making

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Bread made from RWF was considered as a control sample to set target for the quality parameters of the

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gluten-free millet breads. Several preliminary experiments were conducted to set limit of input variables, -

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proofing time (Pt, h), baking time (Bt, min), baking temperature (BT, C) and a fixed quantity of a particular

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hydrocolloid ranging from 2 to 5 per cent (Crockett et al., 2011). Finally, bread was made with Pt, Bt and BT as

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input variables and responses were expansion, specific volume and instrumental textural profile.

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Millet bread was made by straight dough method (Moore, Schober, Dockery, Arendt, 2004). The volume and

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temperature of water used for dough making was 100ml (for 40g millet flour along with all the other

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ingredients) and 40 C, respectively. Temperature of water was given a consideration because, traditionally

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non-wheat-based dough preparation is carried out by using warm water; this initiates the gelatinization of the

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starch which acts as the only resort for assisting the dough formation in the absence of gluten (Hoseney,

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Finney, Pmeranz, & Shogren, (1971)

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Compressed yeast used in bread making process was kept under refrigerated conditions before being used for

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experiments. The yeast was thawed in lukewarm water at 30±2˚C, as recommended by Thiessen (1942). All the

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ingredients were mixed before any water was added. Mixing is normally designed to achieve a target energy

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input into dough or a target final dough temperature. Over mixing can retard the metabolism of yeast.

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Kneading of the dough was carried out by heel of the hand to push and finger tips were used to lift and fold it

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before repeating the same process again and again for 8 -10 min. After mixing and kneading, the round shaped

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dough with all its ingredients (Table 1) was kept in a lightly oiled pan (Schober, Bean, Boyle, & Park, 2008).

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Improved viscoelastic zein-starch doughs for leavened gluten-free breads: Their rheology and microstructure.

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Journal of Cereal Science, 48, 755-767.

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). A damp cotton towel was used as a wrap to prevent a skin formation on dough whilst resting in a draught-

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free place to allow the dough to rise/proof. Thus, the proofing took place at 100 per cent relative humidity (Rh)

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and at ambient temperature of 35±2 C. The Pt (h), Bt (min) and BT ( C) were as per the experimental design.

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The baked bread was allowed to cool down before recording the quality parameters.

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2.5 Bread quality

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The quality of the bread was assessed in terms of expansion, cm; specific volume, mL/g; and texture profile

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analysis (TPA). Expansion: Vertical rise in shape of dough measured as the difference of height (cm) before (L)

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and after (L’) baking (Fig. 1).

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Specific volume (Sv, mL/g): The volume (V, mL) of the bread was measured by mustard displacement method

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(AACC, 1998) and then weighing (W, g) the baked dough (Morreale, Garzón, & Rosell, 2017). Three replicates

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were obtained for each experiment. Specific volume was expressed as,

o

o

o

o

(3)

=

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Texture profile analysis: Instrumental texture was measured in terms of,- hardness, resilience, springiness and

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cohesiveness of bread (Fig. 2) as these properties are considered to be appropriate indicators of textural 4

Leavened gluten-free millet bread

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quality of a bread (Matos and Rossel, 2013; Morreale et al., 2017). The texture analysis was carried out by TA-

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XT Texture Analyser of Stable Micro Systems, UK using the 75 mm diameter plate (P-75 probe). The

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compression mode texture profile analysis was carried out with pre-test speed of 10.0 mm/s, test speed of 2.0

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mm/s, post-test speed of 2.0 mm/s target strain of 40 per cent (Matos and Rosell, 2012) and a trigger force of

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5 g.

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2.6 Experimental design

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Central composite rotatable design (CCRD) of response surface methodology (RSM) for three variables, -

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proofing time (Pt, h), baking time (Bt, min), and baking temperature (BT, C) was obtained by using Design

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Expert (ver. 10). There were six experiments conducted at centre point and two each for every variable at the

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augmented points and 2 (where, n is the number of variables) experiments across all variables for factorial

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points. In all twenty experiments were conducted (Table 2). Determination of coded values and augmented

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point values for input variables were obtained by methods as described in Chakraborty et al. (2014). A perfect

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solution for a multi response matrix can be obtained with Design Expert (ver. 10) by combining the goals into a

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composite function D(x) called the desirability function (Myers and Montogomery, 2002), it is defined as:

o

n

=

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×

×

× … … . .×



(4)

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where, d1, d2, d3 .......dn are the responses and n is the total number of responses in the measure. Numerical

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optimization solution is obtained as a point with maximum desirability.

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2.7 Statistical analysis

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The experimental data comprised responses from twenty experiments in terms of bread quality parameters.

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Effect of input variables on the responses was understood by conducting regression analysis and analysis of

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variance (ANOVA) by means of a second order polynomial model (eq. 5). n

P= βo +

n

βi Xi + i=1

n-1

βii X2i i=1

n

+

(5) βij Xi Xj

i=1 j=i+1

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where, P is response, n is number of variables, X’s are the variables, βo, βi, βii and βij are the regression

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coefficients.

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3. Results and discussion

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Selection of a particular hydrocolloid and its level was based on the ability of the hydrocolloid to impart

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acceptable textural features to gluten-free bread. Bread was prepared using the selected hydrocolloid and the

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processing variables were optimised.

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3.1 Hydrocolloid selection

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The amount of hydrocolloid to be used as an ingredient was finalized after a series of preliminary experiments.

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All the four hydrocolloids, - gum arabic, guar gum, tragacanth gum and xanthum gum were used for preparing

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leavened breads. The quality of breads was assessed on the basis of expansion, specific volume and textural

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properties in terms of hardness, springiness, resilience and cohesiveness. The responses for the blends made

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from non-gluten dough were compared with that of RWF dough (Fig. 3). Xanthum gum at a higher amount (2.5

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g) exhibited a slight decrease in the specific volume of bread as compared to other hydrocolloids. Schober,

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Messerschmidt, Bean, Park, Arendt, (2005) also reported a similar trend in loaf volume of gluten-free breads

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made from sorghum. This behaviour of xanthan gum is due to its ionic nature caused by the presence of two 5

Leavened gluten-free millet bread

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negatively charged carboxyl groups on its side, hydrogen bonds are formed with water and starch by these

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groups forming a rigid gel at higher concentrations of the gum. Thus, xanthan gum supplemented breads were

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more cohesive and resilient, however the springiness did not exhibit any stand-out trend (Fig. 3). Similar

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observations have been made in the past while using hydrocolloids for gluten-free dough systems (Lazaridou

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et al., 2007; Crockett, Ie, & Vodovotz, 2011).

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During the dough making it was also observed that there was a slight increase in water requirement for dough

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formation due to use of hydrocolloids. This may be attributed to hygroscopic nature of hydrocolloids, as also

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reported by Rosell, Rojas, & Benedito de Barber, (2001). In gluten free doughs system adequate hydration is

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critical for strengthening the three-dimensional batter structure (Morreale et al., 2017).

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3.2 Effect of variables on loaf quality

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The results of the regression analysis have been reported in Table 3, wherein it can be seen that all the second

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order models were found to be statistically significant (p<0.01) and capable to represent the variability (R > 80

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per cent) of the data set to capture the individual (linear and quadratic terms) and interactive effect of the

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input variables over the responses. It was observed that among all the input variables, proofing time (Pt) has

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had the maximum instances of playing a significant role in affecting the responses followed by baking time (Bt)

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and baking temperature (BT). The overwhelming effect of Pt can be attributed to the fact that all the

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responses were indicative of the bread quality which are directly or indirectly reflective of bread volume and

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the generation of gases during Pt directly related to volume of the bread (Lazaridou et al., 2007; Matos and

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Rossel, 2013; Morreale et al., 2017).

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3.2.1 Individual effect

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The significant individual effect of the parameters can be deciphered in terms of their linear or quadratic effect

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on the responses. A negative coefficient of a linear term indicates an inverse relationship of the response with

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the input variable and vice versa. Quadratic term with a negative sign indicates that the particular response is

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maximum at the centre point (coded value: 0) of the respective input variable and it decreases as one moves

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towards the augmented points (coded value: -1.68 or +1.68). A quadratic term was considered a better

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predictor of behaviour of variables as it could describe the variability of the response across the experimental

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range.

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Consumer acceptance of bread has a direct relation with loaf volume, better the volume of the loaf more is the

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consumer acceptance. In the present research work, expansion and specific volume were the two indices by

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means of which variations in loaf volume of gluten-free breads were comprehended. Effect of Pt on

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‘expansion’ was significantly maximum at the centre point values of the input variables for pearl millet

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(p<0.05), little millet (p<0.05) and kodo millet (p<0.1). Specific volume of pearl millet bread exhibited a trend

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opposite to that of the other two breads. While the specific volume was maximum (p<0.1) at centre point for

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pearl millet bread, the same was maximum at the augmented point for the other two types of bread. Specific

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volume of the bread increases significantly (p<0.01) across the whole experimental range of Bt. However, for

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pearl millet bread alone, the specific volume decreased till the centre point and thereafter increased. The

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second order model could not establish any significant relationship between expansion and specific volume of

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bread with baking temperature (BT). Hydrocolloid incorporated breads expand less and are stiff due to the

2

6

Leavened gluten-free millet bread

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increased water binding and reduction in water availability for hydration of starch. Textural characteristics of

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bread assume massive importance due to the intense dependence of crumb features towards consumer

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acceptance. It is always desirable of the bread to have a soft flexible crumb. An increase in Pt contributed to a

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significant (p<0.05) increase in the hardness of the little millet and kodo millet bread. There would be a

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significant (p<0.1) increase in the hardness of the pearl millet bread through the entire experimental range of

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Bt. The hardness of pearl millet would increase significantly (p<0.01) beyond the centre point of BT.

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Variations in baking time (Bt) and baking temperature (BT) had similar effect on hardness of little and kodo

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millet breads. In case of little (p<0.05) and kodo (p<0.01) millet bread, hardness would peak at the centre point

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and then diminished towards the augmented points. Heat treatment caused as a result of increased BT lead to

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uncoiling of existing xanthan chains with water and starch. The open links of chain now cling as ionic bond with

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proteins present in the millet matrix resulting in increased hardness with increase in temperature. Since

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amylose containing starch is more in pearl millet so this trend has been reported after the centre point values.

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The cohesiveness (p<0.01) of all the breads was best at the centre point values of Pt (p<0.1) and Bt (p<0.01)

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which would subsequently decrease beyond this point. Cohesiveness for the breads across all the parameters

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increases till the centre point and then decrease. Similar significant (p<0.01) effect was cast by Pt on the kodo

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millet bread only. Limited size of pores due to strength induced to the lamella of the cells by the xanthan gum

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resulted in formation of a firm mesh like structure of the crust with thick cell walls (Lazaridou, Duta,

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Papageorgiou, Belc, & Biliaderis, 2007). However, upon increase in Bt and BT the enhanced diffusive or

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convective transport of water from crumb towards crust which was otherwise trapped by xanthan gum

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resulted in a crumbly texture and incoherent structure.

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The firm gas cell walls also turned brittle leading to a fragile crumb. Most resilient millet bread (p<0.05) was

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obtained at the centre point value of BT. Springiness of all the breads were significantly (p<0.01) consistent

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with Pt, this response peaked at the extreme point and minimised at the centre point. The significant linear

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terms of Bt (p<0.05) and BT (p<0.1) indicate that the springiness of pearl millet and kodo millet bread would

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decrease with increase in these variables. Xanthan gum is reported to increase dough elasticity by increasing

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G’ (Crockett et al., 2011), but this increase is followed by the dough becoming too stiff to rise during proofing.

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This results in less entrapped air during proofing leading to leavened bread, but with limited springiness.

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3.2.2 Interactive effect

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The interactive effect of input variables on responses was comprehended with the help of the contour plots

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(Fig 4). It was observed during the regression analysis of the second order models that only some of the

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responses were being affected significantly (p<0.01) by the interaction of input variables. Across all flours,

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expansion was affected (p<0.01) by interaction of Pt-Bt. The interaction of Pt-BT was common for all three

238

flour dough to affect (p<0.01) specific volume of the bread; interaction (p<0.01) of both Pt-Bt and Pt-BT had a

239

direct bearing on springiness of bread.

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It can be seen in Fig. 4 (B, C) that expansion is more at longer proofing time. Absence of gluten in the millet

241

flours necessitates a longer Pt and the same is a vital requirement for expansion and gas retention (Demiralp,

242

Celik, & Koksel, 2000). Pearl millet was the coarsest of all the flours with D [4, 3] = 94.8 µm, may be that is the

243

reason that it is exhibiting high expansion at low Pt (Fig. 4 A). This fact was also observed by de la Hera, 7

Leavened gluten-free millet bread

244

Gomez, & Rosell (2013) that coarser corn flours provide breads with higher volume and softer crumb due to

245

their ability to retain carbon dioxide during proofing. Specific volume of the bread was more for all the millet

246

flours at increased Pt (Fig. 4 D, E, F) within the experimental range. It has been reported by other researchers

247

that increase in bread volume in high fibre dough systems requires a combination of high Pt and lower BT

248

(Foschia, Peressini, Sensidoni, & Brennan, 2013) observed in the present research work. Springiness followed

249

the same trend across all flours while displaying significant (p<0.01) interactive effect of both Pt-Bt and Pt-BT

250

(Fig. 4 G, H, I, J, K, L). Combinations of low Pt and low Bt /BT or a combination of high Pt and high Bt/BT over

251

the experimental range resulted in maximum springiness.

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3.3 Optimization and model validation

253

The optimum bread making condition was decided based on the loaf volume characteristics and the textural

254

characteristics. While expansion and specific volume were constrained with being maximised, hardness was

255

aimed at being minimum, rest of the textural features were not given any specific goal. Results of the

256

numerical optimization solutions for the statistically significant second order models had a desirability of 0.96

257

(Table 4).

258

The predicted quality of RWF bread was better as compared to the corresponding predicted quality

259

parameters of leavened gluten-free millet bread. The results are in concordance with the observations that

260

have been made by other researchers (Robin, Schuchmann, & Palzer, 2012). The veracity of the model

261

predicted results was established by preparing the breads at model predicted optimum condition (Fig. 5) and

262

recording the quality of the breads. The model predicted quality indices were compared with that of the

263

breads prepared under optimum conditions. The results of two tailed t-test (Table 5) for all the millet breads

264

revealed that there was no significant difference between the model predicted values and the actual values

265

4. Conclusion

266

Intake of fibre rich foods lessens the chances of onset of many chronic disorders and diseases in human beings.

267

Millets are a potent source of dietary fibres, but they are gluten-free and hence are not suitable for being used

268

for making leavened breads. Suitability amongst the hydrocolloids, - tragacanth gum, gum arabic, guar gum

269

and xanthan gum to be used as an ingredient for mimicking the action of gluten has been carried out based on

270

the gluten-free millet (pearl, little and kodo) bread quality in terms of expansion (cm), specific volume (mL/g)

271

and textural characteristics. Xanthan gum was found to be the most suitable hydrocolloid for rendering an

272

acceptable structure to the bread. Gluten free yeast leavened breads were made using a central composite

273

rotatable experimental design of response surface methodology with proofing time (Pt), 1.3 - 4.7 h, baking

274

time (Bt), 32 – 48 min and baking temperature (BT), 158 – 192 C as input variables. Statistically significant

275

(p<0.01) second order models were used to understand effect of variables upon the responses. The textural

276

property of little millet flour bread was observed to be better amongst all the millet breads. Optimum

277

conditions for little millet bread in terms of Pt, Bt and BT was 3.5 h, 48 min and 190 C, respectively. Under the

278

optimum conditions the little millet bread exhibited minimum hardness and best springiness values. A 2-tailed

279

paired t-test revealed that quality characteristics of bread prepared at model predicted values did not

280

significantly (p<0.01) differ from that actually prepared at optimum condition.

o

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10

Figure 1 Measure of expansion for leavened bread. Figure 2 A representative figure of texture profile analysis curve and definition of terms. Figure 3 Effect of different hydrocolloids at various levels on the quality characteristics of bread. Figure 4 Contour plots representing the significant (p<0.01) interactive effect of two input variables (third variable at centre point) on the various responses of leavened breads made from pearl millet (A, D, G, J), little millet (B, E, H, K) and kodo millet (C, F, I, L) flours. Figure 5 Leavened breads prepared from (a) Refined wheat (b) Pearl millet (c) Kodo millet (d) Little millet.

Table 1 Ingredients for bread making Ingredients

RWF bread

Millet flour bread

Base flour

40 g

40 g

Water

21 ml

100 ml

1g

1g

Yeast

2.4 g

3g

Sugar

1.25 g

1.25 g

Tapioca starch

NA

60 g

Hydrocolloid

NA

Fixed amount

Baking time

20 min

Salt

Baking temperature Butter

o

195±3 C

As

per

experimental

design

For greasing the baking pan to easily lift the bread

Table 2 Experimental plan and observed values of input variables Actual values

Coded values o

Pt, h

Bt, min

BT, C

1.3

31.6

158

-1.68

2

35

145

-1

3

40

175

0

4

45

185

+1

4.7

48.4

192

+1.68

Experimental design as coded values

No. of experiments

0

0

0

6

±1

±1

±1

8

±1.68

0

0

2

0

±1.68

0

2

0

0

±1.68

2

Total number of experiments

20

Pt - proofing time, Bt - baking time, BT - baking temperature

Table 3 Regression analysis and ANOVA of second order models for the various responses Pearl millet Predi

R1

R2

R3

Little millet

R4

R5

R6

R1

R2

R3

ctor Pt Bt

0.039

0.002

-0.022

-1.380

0.021

*

1.324

0.009

0.019

**

***

*

-0.018 -0.017

-0.060

***

1.962

*

-0.008 0.040

Bt × Pt

0.025 -0.168

***

-0.890

-0.023 0.037

BT × Bt

0.025

0.015 -0.090

Pt × Bt -0.175

***

**

0.050

**

0.019

0.075

-0.001

-0.419

-0.020

2

-0.007 0.043

BT

0.004

***

2.481

***

0.023

***

-0.021

**

-0.024

*

***

0.022 0.046

***

0.002 0.027

0.010

0.075

-0.795

2

Bt

-0.002

** *

-0.026

-0.043

-0.017

0.035

*

0.015

-0.042 -0.070

***

*

2

***

*

**

0.020

-0.013 -0.038

-0.033

3.275

**

*

0.980 -0.037

Pt

R4

R5

R6

R1

R2

R3

R4

R5

R6

Coefficients **

***

BT

Kodo millet

**

-1.001 -0.025

***

0.083

***

-0.119

-0.052

***

**

0.002

-0.073

0.015

0.046

***

0.001

0.025

0.082

*

0.016

*

0.025

***

0.013

0.006 0.020

0.003 -0.068

***

-0.007

-0.005 -3.554

***

-0.034

-0.006 -0.049

***

0.011

0.003

**

-0.005

***

***

-0.004

**

-0.006

***

0.011

0.935 -0.029

***

**

1.246

-

**

0.528

-0.001

-0.055

-0.841 -0.036

-0.125

***

3.822 0.041

0.050

**

**

0.016

-0.005 -8.233

-0.002

0.003

**

0.017

**

-0.015

-0.015

*

-0.032

**

***

0.029

*

***

0.004

**

0.016

***

-0.020

0.035

***

0.033

***`

0.020

-2.281 -0.036

***

***

-0.021

***

-0.045

-9.110

0.016

-0.012

***

-0.037

-0.009

*

**

4.126

*

-0.012 -0.007

-0.175

***

0.024

0.003 0.036

0.441 0.023

-1.615

-0.017

**

0.039

-0.008

***

-1.264

**

***

0.155

*

-0.004

0.020

0.038

***

***

***

-0.001 -0.008

-0.652 -0.035

**

0.054

-1.788

**

0.006 0.018

***

-0.045

-0.042

**

***

***

**

1.209

0.024

*

**

0.002 -0.057

***

***

-0.005 -0.042

***

ANOVA ***

***

7.53

***

5.23

***

16.07

***

7.86

3.71

6.36

6.83

5.51

8.91

9.41

3.47

91.3

94.5

81.8

82.8

87.9

87.2

82.5

93.5

R ,%

8.07

***

19.19

2

4.99

***

F-value 11.67 c.v., %

4.98

***

5.87

***

***

***

***

9.79

8.23

***

10.4

***

5.85

***

12.84

***

8.07

***

***

12.74

11.32

7.53

6.69

4.80

4.47

5.40

9.36

4.36

16.45

6.20

5.51

8.91

84.1

91.9

91.1

89.8

88.1

90.3

84.1

92.4

87.9

87.2

Pt - proofing time, Bt - baking time, BT - baking temperature; R1, Expansion, cm; R2, Specific volume, mL/g; R3, Hardness, N; R4, Resilience; R5, Springiness; R6, Cohesiveness. ***

significant at p< 0.01, **significant at p< 0.05, *significant at p< 0.1

Table 4 Optimum conditions for RWF and millet breads Input variables

RWF bread

Pearl millet bread

Little millet bread

Kodo millet bread

Pt, h

0.67 (40 min)

4.2

3.5

2.0

Bt, min

25

33

48

45

195

180

190

165

Expansion, cm

1.2

1.0

0.9

0.8

Specific volume, mL/g

2.62

1.21

1.16

1.72

Hardness, N

1.6

9.3

3.1

5.3

Resilience

0.38

0.49

0.32

0.32

Springiness

0.97

0.48

0.48

0.38

Cohesiveness

0.80

0.38

0.36

0.35

o

BT, C Responses

Pt - proofing time, Bt - baking time, BT - baking temperature

Table 5 Model testing by using two-tailed t-test for little millet bread Response

Predicted

Actual value@

Standard

Mean

% Variation

tcal

value (µo)

(µ1) ± SD

error

difference

Expansion, cm

0.9

0.82± 0.08

0.037

0.08

11.11

2.14

Specific volume, mL/g

1.16

1.26± 0.14

0.061

0.1292

10.37

2.12

Hardness, N

3.10

3.46± 0.34

0.154

0.06

1.73

0.39

Resilience

0.32

0.33± 0.09

0.040

0.012

2.26

0.30

Springiness

0.48

0.51± 0.06

0.027

0.01

1.96

0.37

Cohesiveness

0.36

0.382± 0.05

0.022

0.042

7.34

1.89

ho: µo = µ1, tcal
L

L’

Expansion (cm) = L’- L Figure 1

Figure 2

7

Hardness, N Resilience

6

Springiness Cohesiveness

5

Specific Volume, ml/g 4 3 2 1 0 1g RWF Bread

1.5g

2g

Arabic

2.5g

1g

1.5g

2g

2.5g

1g

Guar

1.5g

2g

Tragacanth

Hydrocolloid(s) level Values are average of triplicates and error bars represent standard deviation.

Figure 3

2.5g

1g

1.5g

2g

Xanthum

2.5g

Expansion

Expansion

50.00

1.10 0.32

0.46

Baking time, min

0.58

40.00

0.58 0.84 0.32 0.06

45.00

0.65 0.59

40.00

0.46 0.72 0.33

1.10

2.00

3.00

4.00

5.00

1.00

2.00

3.00

A

4.00

1.13

1.00

2.00

200.00

3.00

4.00

5.00

Proofing time, hr

B

C Specific Volume

200.00

1.845

1.837

Baking temperature, oC

0.738

o

Baking temperature, C

0.87

0.35

35.00

5.00

Specific Volume

1.801

1.446 1.092

1.326

175.00

1.326 1.446 162.50

0.61

Proofing time, hr

Specific Volume

187.50

40.00

30.00

Proofing time, hr

200.00

0.61

0.09

30.00

1.00

45.00

0.20

30.00

0.35

0.87

0.59

35.00

Expansion 1.13

0.65

1.092

1.801

Baking temperature, oC

Baking time, min B: Baking time

0.84 45.00

35.00

50.00

0.33

Baking time, min

50.00

1.652 1.466

187.50

1.393

1.466 175.00

1.281 1.652 162.50

1.837

1.096

1.660 1.475

187.50

1.417 1.475

175.00

1.290

1.660 162.50

1.845

1.105

2.155 150.00

150.00

150.00 2.00

3.00

4.00

1.00

5.00

2.00

3.00

D

0.614 0.549

40.00

0.483 0.483 0.549 0.614

0.600 0.58

45.00

0.52 0.40 0.46

40.00

0.41 0.41

0.46 35.00

0.369

45.00

0.542 0.484

40.00

0.427 0.427 0.484

35.00

0.542

0.40

0.679

0.600 30.00 2.00

3.00

4.00

5.00

0.58

1.00

Proofing time, hr

30.00 2.00

G

4.00

0.578

0.503

175.00

0.40 0.46

0.503 0.468

0.41

0.46 0.40

162.50

0.578 0.652

0.58

3.00

4.00

5.00

0.379

0.510

0.444

1.00

0.415

0.444

0.415 0.510 0.576 0.379

0.34 150.00

150.00

Proofing time, hr

0.576

162.50

0.52

0.429 150.00

0.313

175.00

0.41

5.00

187.50

0.52

175.00

0.468

4.00

Springiness

200.00

0.58

187.50

0.429

3.00

I

0.34

o

0.652

Baking temperature, C

0.355

J

2.00

Proofing time, hr

Springiness

200.00

187.50

2.00

1.00

5.00

H

Springiness

200.00

3.00

Proofing time, hr

Baking temperature, oC

1.00

Baking temperature, oC

5.00

F

0.52

30.00

1.00

4.00

Springiness

50.00

0.34

Baking time, min

Baking time, min

0.679

162.50

3.00

Proofing time, hr

Springiness

50.00

0.418

35.00

2.00

E

Springiness

45.00

1.00

5.00

Proofing time, hr

Proofing time, hr

50.00

4.00

Baking time, min

1.00

2.00

3.00

4.00

Proofing time, hr

K Figure 4

5.00

1.00

2.00

3.00

4.00

Proofing time, hr

L

5.00

(a)

(b)

(c)

(d) Figure 5



Leavened bread can be made from pearl, little & kodo millet.



Xanthum gum was observed to be the best suited to introduce leavening.



Optimum condition for leavened bread made using millets has been reported.



Millet bread has lesser loaf volume, harder, less springy than traditional bread.

Conflict of Interest and Authorship Conformation Form Please check the following as appropriate:

o

All authors have participated in (a) conception and design, or analysis and interpretation of the data; (b) drafting the article or revising it critically for important intellectual content; and (c) approval of the final version.

o

This manuscript has not been submitted to, nor is under review at, another journal or other publishing venue.

o

The authors have no affiliation with any organization with a direct or indirect financial interest in the subject matter discussed in the manuscript

o

The following authors have affiliations with organizations with direct or indirect financial interest in the subject matter discussed in the manuscript:

Author’s name

Affiliation Agro Produce Processing Division, ICAR - Central

Subir Kumar Chakraborty

Institute of Agricultural Engineering, Bhopal, India

Nachiket Kotwaliwale

Agro Produce Processing Division, ICAR - Central Institute of Agricultural Engineering, Bhopal, India

Surekha Ashok Navale

College of Agricultural Engineering and Technology, DBS Konkan Agricultural University, Dapoli, India