# In vitro protein digestibility of gluten-free climate-smart cowpea-based pasta

P. Pinel, M. Robert, A. Putois, Jérémy Claudel, C. Barron, O. Ménard, V.

Micard, Claire Bourlieu-Lacanal

► To cite this version:

P. Pinel, M. Robert, A. Putois, Jérémy Claudel, C. Barron, et al.. In vitro protein digestibility of gluten-free climate-smart cowpea-based pasta. Food Research International, 2025, 208, pp.116100. 10.1016/j.foodres.2025.116100. hal-05238643

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# *In vitro* protein digestibility of gluten-free climate-smart cowpea-based pasta

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5 **Authors:** P. Pinel¹, M. Robert¹, A. Putois¹, J. Claudel¹, C. Barron¹, O. Ménard², V. Micard¹*#, C.

6 Bourlieu-Lacanal¹*#,

7 *The two authors have equal participation to this work

8 #Corresponding authors: claire.bourlieu-lacanal@inrae.fr, valerie.micard@supagro.fr

9 ¹Univ Montpellier, INRAE, Institut Agro Montpellier, JRU IATE, France

10 ²INRAE, Institut Agro Rennes, JRU STLO, France

11 **Keywords:** Teff; Amaranth leaves; Protein network; Gastrointestinal; *i*-PDCAAS

12 **Abstract:**

13
14 Nutritional optimisation of staple food such as pasta with flours from climate-smart crops
15 (i.e. resilient to climatic hazards and requiring minimal inputs) is in line with actual
16 environmental and nutritional challenges. Although the quantity of protein is important, the
17 quality through protein digestibility is essential. The aim of this work was to assess the protein
18 digestibility of four gluten-free climate-smart pasta all based on cowpea flour with or without the
19 addition of teff and/or amaranth leaf flour(s) using two static in vitro methods: static Infogest
20 digestion protocol and Megazyme® enzymatic kit. The effect of both gluten absence and the high
21 fiber content on the in vitro protein digestibility was investigated through the use of three durum
22 wheat semolina pasta controls with increasing fiber content. Statistical analysis were made
23 through ANOVA with p<0.05. Despite structural differences, induced by protein origin and the
24 disruption of the protein network by fibers, there was no significant difference in in vitro protein
25 digestibility between cowpea-based and traditional durum wheat semolina pasta. Protein quality
26 was then approached with the measurement of the in vitro Protein Digestibility Corrected Amino
27 Acid Score (i-PDCAAS) for the two methodologies. Thanks to their balanced essential amino
acid profile, cowpea-based pasta demonstrated *i*-PDCAAS that was twice as high as that of wheat-based pasta, as determined by both by the Infogest (68-86 *versus* 35-44) and enzymatic kit (99-104 *versus* 49-56) methods. In addition, for the first time both methodologies were compared and Infogest protocol appeared more suitable for more detailed studies.

## 32 **Graphical abstract:**

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## 34 **Highlights:**

* Enzymatic digestion kit can be used for initial protein quality assessment

* The Infogest protocol enables a more in-depth analysis of protein digestibility

* Cowpea-based pasta have similar *in vitro* protein digestibility than wheat-based pasta

* Cowpea-based pasta have two times higher *in vitro* PDCAAS than wheat-based pasta

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# 1. Introduction
Current recommendations for public health and sustainable development are driving efforts to enhance the nutritional value of staple foods through the utilization of flours derived from 'climate-smart' crops. The term 'climate-smart' crops refers to varieties that exhibit resilience to diseases and/or climatic hazards, and require minimal inputs such as water, fertilizers and treatments. These crops gather a diverse array of species including teff (gluten-free cereal), cowpea (legume), and amaranth (gluten-free pseudo-cereal) (Achigan-Dako et al., 2014; Emmambux & Taylor, 2013; Ngalamu et al., 2015). Some of these crops are promising candidates to partially or totally replace wheat flour in various staple foods, such as pasta, using not only their grains but also some other parts of the plant, such as leaves.

Indeed, in the recent years, traditional pasta have been optimized by partial or total replacement of durum wheat semolina with whole wheat and/or various cereals and/or legumes. Despite the satisfactory protein content of durum wheat semolina, it is deficient in essential amino acids such as lysine, which can impede protein synthesis (FAO, 2011). Association between different vegetable protein sources such as cereals and legumes allows equilibrating essential amino acids content and increase protein quality, thereby facilitating optimal protein metabolism (as reviewed for instance by Berrazaga et al. (2019)). Furthermore, the addition of whole cereal flours, legumes or other nutritious ingredients such as vegetables, leaves or algae has been shown to complement the low content of fibers and micronutrients of traditional durum wheat semolina (Cárdenas-Hernández et al., 2016; García-Valle et al., 2021). Additionally, in recent years gluten-free products have become increasingly popular, leading to the development of pasta formulations with gluten-free cereals (Bresciani et al., 2022). Therefore, the nutritional optimization of pasta made from gluten-free climate-smart legumes, cereals and leafy vegetable flours could be a solution to address some current prevailing nutritional, social, and ecological challenges.
However, climate-smart gluten-free cereal, legume and leaf flours contain proteins with different biochemical characteristics than durum wheat semolina protein. Osborne (1924) classified seed proteins according to their solubility: Albumins are soluble in water, globulins in dilute salt solutions, glutelins in dilute acid and alkali solutions, and prolamins in hydro-alcoholic solutions. Wheat and gluten-free cereal proteins, such as teff, are mainly composed (80%) of prolamins and glutelins (Schalk et al., 2017; Taylor et al., 2016). Despite this similar protein categorization, prolamins found in gluten-free cereals (sorghum, millet, teff) are classified as kafirin, pennisetin or eragrostin (Adebowale et al., 2011; Taylor et al., 2016), contrasting with the α/β-, γ- and ω-gliadins present in wheat (Schalk et al., 2017). Moreover, albumins and globulins which represent only 20% of total wheat proteins are abundantly found in legume proteins such as cowpea with 50-70% of globulins (7S vicilin type and 11S legumin) and 10-30% of albumins depending on the legume sources (Chi-Wah & Dixon, 1994; Foschia et al., 2017). Proteins from leafy vegetables such as amaranth leaves can be classified into two distinct classes: water-insoluble “green proteins” which include cell wall and membrane proteins (Thornber, 1975), and water-soluble “white proteins” which are composed of RubisCO at 30-50% (Ducrocq et al., 2024; Gerloff et al., 1965). Complementary indicators reflecting the supramolecular structure of the protein network have been proposed using Sodium Dodecyl Sulfate (SDS) and SDS-dithioerythritol (DTE) solubility of proteins (Petitot et al., 2009). These indicators describe the state of protein aggregation with the part of covalent (disulfide bonds and others i.e. isopeptide bonds) vs. weak interactions between proteins.

Despite the growing interest for innovative pasta formulations, there are only few publications addressing the impact of incorporating climate-smart cereals, legumes or other nutritious flours on pasta protein digestibility (reviewed by Pinel et al. (2023)). These pasta are of particular interest in addressing the dietary needs of undernourished populations. In this context,
cowpea appears to be a promising raw matter. However, among publications concerning alternative pasta, only two publications dealing with cowpea pasta, and always mixed with wheat, have determined the protein *in vitro* digestibility (Bergman et al., 1996; Nur Herken et al., 2006). Additionally, the tripartite association of cereal, legume, and leafy vegetable can also be interesting for its application, as it allows the use of local raw matters. In a previous recent study by Pinel, Barron, et al. (2024), pasta were formulated with gluten-free climate-smart raw matters, including cowpea (legume) with or without the addition of teff (cereal) and/or amaranth leaves (leafy vegetable). These formulations were developed and optimized to meet the nutritional recommendations of the FAO in terms of protein (quantity and quality), fiber, iron, zinc, B9 vitamin (and beta-carotene). Following the optimization of the formulations (Pinel, Drogue, et al., 2024a), the subsequent study of their culinary quality and biochemical composition (Pinel, Barron, et al., 2024b), the protein quality and digestibility of these cowpea-based innovative pasta formulations still needed to be further investigated.

Indeed, the quality of protein is based on the essential amino acid composition, and the ability to be digested and absorbed (as reviewed by Berrazaga et al. (2019); Gaudichon (2019)). In addition to the change in essential amino acid profile due to change of protein sources in these innovative pasta formulations, changes in amino acid sequence occur. Since proteases have specific cleavage sites depending on the amino acid sequences in peptide bond (Cheison et al., 2011; Sah et al., 2016), such a change could impact protein hydrolysis (Berrazaga et al., 2020). The nature of protein itself also affects the protein aggregation of pasta protein network, as reported by Laleg et al. (2017) in case of a proportional increase in faba bean protein in durum wheat semolina pasta. Additionally, a high fiber content in pasta results in more fibrous structures, which alter the continuity of the pasta's microscopic structure and can disrupt the pasta protein network at a supramolecular scale (Pinel, Barron et al., 2024). In addition, the presence of fiber can act as a
113 physical barrier, impeding the diffusion of proteases within the matrix (Lin et al., 2019).
114 Consequently, alterations in the structure of pasta, whether it is a change in the continuity of the
115 protein network or a change in the state of protein aggregation, can exert an influence on *in vitro*
116 protein digestibility as suggested by Berrazaga et al. (2020) and Laleg et al. (2019).

117 However, to investigate the protein quality and digestibility of these innovative pasta
118 formulations, it is essential to consider the methodology used to determine pasta protein quality
119 and digestibility. In recent years, there has been a shift toward simulating human digestion
120 through *in vitro* protocols, leading to the proposal of numerous indicators to approach protein
121 digestibility have been proposed (reviewed by Santos-Sanchez et al. (2024)). These indicators
122 gather *in vitro* protein digestibility (protein hydrolysis, 10 kDa ultrafiltration), essential amino
123 acids composition and *in vitro*-Protein Digestibility Corrected Amino Acid Score (i-PDCAAS).
124 Of course, these indicators are more ethically acceptable, less costly and time consuming than *in
125 vivo* protocols. In addition to these numerous indicators, *in vitro* protein digestibility can be
126 measured by numerous protocols involving different enzymes (source, purity, and activity),
127 simulated digestive compartment pH and digestion times (Akeson & Stahmann, 1964; Hsu et al.,
128 1977; Pasini et al., 2001). This significant variation in terms of indicators and digestion protocols
129 makes comparison between studies difficult. In recent years, an internationally standardized static
130 *in vitro* digestion protocol, static Infogest digestion has been developed (Brodkorb et al., 2019;
131 Minekus et al., 2014) which facilitates comparison between studies. On the other hand, enzymatic
132 digestion kits from manufacturers such as Megazyme® offer rapid and simplified protocols for
133 obtaining i-PDCAAS results, including a protein digestibility score and are also widely used.
134 Thus a comparison of the different *in vitro* protein indicators obtained using these two widely
135 used digestion protocols would be of high interest for the international food scientist community.
In this context, the objective of this study was to determine the *in vitro* protein digestibility of innovative and highly nutritious pasta formulations made from gluten-free climate-smart raw matters using these two digestion protocols. To this end, four cowpea-based pasta (with and without teff and/or amaranth leaves) have been compared to three durum wheat semolina based pasta (controls) using two methods, *i.e.* the static Infogest digestion protocol and a commercial enzymatic kit Megazyme®. The study's novel approach incorporated the assessment of protein quality through *i*-PDCAAS calculation for this specific category of pasta. The impact of the absence of gluten and the high fiber content on *in vitro* protein digestibility have been investigated as generic factors influencing protein digestibility in these innovative climate smart based pasta, such approach had never been undertaken previously.

## 2. Material and Methods

### 2.1. Chemicals and analytical reagents

All chemicals used for biochemical characterization of pasta and digesta were of analytical grade were obtained from Sigma-Aldrich. All solutions were prepared with deionized water of resistivity not less than 18.2 MΩ cm⁻¹.

### 2.2. Raw materials

Wholegrain Teff (white), cowpea white (*Bechuana*) and amaranth leaf flours were provided by Birkuta (UK), the University of Pretoria (South Africa) and Makerere University (Uganda), respectively. All these suppliers are part of H2020 European Innofood Africa project (https://innofoodafrica.eu/). Durum wheat semolina, whole durum wheat semolina and durum wheat bran were supplied by La semoulerie de Bellevue (Marseille, France), Markal (Saint Marcel lès Valence, France) and Alpina Savoie (Chambéry, France), respectively.

### 2.3. Pasta production
Four cowpea-based pasta which allow to cover the FAO nutritional recommendations in 159 proteins (quantity and quality), fibers, zinc, beta-carotene and B9 vitamin for adult women were 160 formulated by linear programming (Pinel, Drogue, et al., 2024a) as follows: 161

* 100% cowpea flour (CW) 162

* 90% cowpea flour and 10% amaranth leaf flour (CW-AL) 163

* 60% cowpea flour and 40% teff flour (CW-TEF) 164

* 55% cowpea flour, 35% teff flour and 10% amaranth leaf flour (CW-TEF-AL) 165

Since these pasta are formulated to respond to nutritional needs, they contain a high amount of 166 proteins (17 to 22%, Table 1) and fibers (16 to 24%). 167

In order to compare them to adequate controls, wheat-based pasta with increasing 168 amounts of fibers were produced to differentiate the impact of fibers from the other structural 169 parameters on digestibility. Wheat-based pasta formulations were as follows (Pinel, Barron, et al, 170 2024): 171

* 100% durum wheat semolina (S, 4.5% fibers in cooked pasta) 172

* 100% whole durum wheat semolina (WS, 11.2% fibers) 173

* 74.5% durum wheat semolina + 24.5% durum wheat bran (HFS, 18.9% fibers) 174

S pasta had fiber and protein content far from cowpea-based pasta whereas HFS pasta had a 175 lower protein content but a similar fiber content compared to cowpea-based pasta which 176 facilitated comparisons. 177

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<table><caption>179 Table 1 Summary of biochemical characteristics of wheat-based and cowpea-based cooked pasta according to Pinel, Barron, et al.</caption><thead><tr><th rowspan="2"></th><th colspan="3">Wheat-based pasta</th><th colspan="4">Cowpea-based pasta</th></tr><tr><th>S</th><th>WS</th><th>HFS</th><th>CW</th><th>CW-AL</th><th>CW-TEF</th><th>CW-TEF-AL</th></tr></thead><tbody><tr><td>Protein (g/100g d.b.)</td><td>13.0 ± 0.0<sup>g</sup></td><td>12.5 ± 0.1<sup>h</sup></td><td>13.1 ± 0.1<sup>g</sup></td><td>22.1 ± 0.0<sup>a</sup></td><td>21.4 ± 0.1<sup>b</sup></td><td>17.0 ± 0.2<sup>e</sup></td><td>16.9 ± 0.3<sup>e</sup></td></tr><tr><td>(conversion Factor)</td><td>(5.88)</td><td>(5.78)</td><td>(5.73)</td><td>(5.24)</td><td>(5.25)</td><td>(5.37)</td><td>(5.37)</td></tr><tr><td>Starch (g/100g d.b.)</td><td>76.3 ± 0.9<sup>a</sup></td><td>69.8 ± 1.6<sup>c</sup></td><td>59.9 ± 1.2<sup>d</sup></td><td>46.8 ± 0.5<sup>h</sup></td><td>41.4 ± 0.6<sup>ij</sup></td><td>55.3 ± 0.2<sup>f</sup></td><td>50.0 ± 0.8<sup>g</sup></td></tr><tr><td>Fiber (g/100g d.b.)</td><td>4.5 ± 1.2</td><td>11.2 ± 2.0</td><td>18.9 ± 2.0</td><td>20.9 ± 2.0</td><td>23.6 ± 2.0</td><td>16.3 ± 2.0</td><td>19.7 ± 2.0</td></tr><tr><td>(% insoluble fiber)</td><td>(84%)</td><td>(88%)</td><td>(94%)</td><td>(92%)</td><td>(97%)</td><td>(90%)</td><td>(90%)</td></tr><tr><td>Phytic acid<br>(g/100g d.b.)</td><td>0.35 ± 0.02<sup>g</sup></td><td>0.67 ± 0.02<sup>f</sup></td><td>0.87 ± 0.01<sup>c</sup></td><td>0.81 ± 0.03<sup>d</sup></td><td>0.72 ± 0.02<sup>e</sup></td><td>0.82 ± 0.03<sup>d</sup></td><td>0.82 ± 0.02<sup>d</sup></td></tr><tr><td>TIA<br>(mg/100g d.b.)</td><td>&lt; DL<sup>f</sup></td><td>&lt; DL<sup>f</sup></td><td>&lt; DL<sup>f</sup></td><td>624 ± 31<sup>a</sup></td><td>630 ± 38<sup>a</sup></td><td>397 ± 20<sup>b</sup></td><td>413 ± 1<sup>b</sup></td></tr><tr><td>Oxalates<br>(mg/100g d.b.)</td><td>45 ± 3<sup>g</sup></td><td>56 ± 6<sup>fg</sup></td><td>69 ± 6<sup>ef</sup></td><td>24 ± 3<sup>h</sup></td><td>307 ± 32<sup>c</sup></td><td>77 ± 8<sup>e</sup></td><td>418 ± 21<sup>a</sup></td></tr></tbody></table>

180 (2024)

181 Means with the same letter within a row are not significantly different (p < 0.05); Mean ± standard deviation of three repetitions; Proteins obtained by Kjeldahl method; Fiber contents were obtained by external laboratory and are given with Mean ± standard deviation; TIA = trypsin inhibitor activity; S = durum wheat semolina pasta; WS = whole durum wheat semolina pasta; HFS = durum wheat semolina enriched with bran pasta; CW = 100% cowpea; CW-AL = 90% cowpea + 10% amaranth leaf pasta; CW-TEF = 60% cowpea + 40% teff pasta; CW-TEF-AL = 55% cowpea + 35% teff + 10% amaranth leaf pasta; <DL = below detection limit

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All cowpea and wheat-based pasta were produced by low temperature extrusion (40°C) and drying (55°C) in PLANET platform of JRU IATE (Montpellier, France) on a lab-scale single screw pasta extruder (Sercom, Montpellier, France) according to Pinel, Barron, et al. (2024). Particle size distribution of dry and cooked pasta samples were analyzed by laser diffraction particle size analyzer Coulter LS 13320XR (Beckman Coulter Inc., Fullerton, USA) in dry mode with a laser diffraction refractive index of 1.54. The particle sizes were described by a distribution curve expressed in volume and the corresponding median diameter D50. Dry pasta samples (before cooking) were obtained by grinding dry pasta to a close particle size (D50 = 539 ± 21) and were used in protein extractability to highlight the protein denaturation and aggregation induced by cooking. Additionally, each pasta formulation was cooked at their respective optimal cooking time (OCT) (Pinel, Barron, et al., 2024), freeze-dried and ground to reach a close particle size distribution (D50 = 253 ± 24 µm, Figure 1). These OCT cooked freeze-dried pasta samples of cowpea and wheat-based pasta were used for biochemical composition, protein extractability and in vitro protein bioaccessibility using several complementary indicators.

## 2.4. <u>Biochemical composition</u>

The biochemical composition of cooked pasta samples (Aminograms, fibers, lipids, starch, sugar, vitamins, minerals, phytic acid, trypsin inhibitor activity (TIA) and oxalates) was reported in Pinel, Barron, et al. (2024b) according to Pinel, Drogue, et al. (2024a), and summarized in Table 1. Proteins were analyzed by Kjeldahl (NF V03-050, 1970) and Dumas protein analyzer systems (externalized). Analyses were performed in triplicate for all cowpea and wheat-based pasta.

## 2.5. <u>Pasta structure</u>

### 2.5.1. *Light microscopy*
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Pasta were freshly cooked at their respective OCT and cross sections (8 µm thick) were cut at -16°C using a cryomicrotome (Microm HM 520, Walldorf, Germany) with a cryoprotector (Cellpath, Newtown, UK) (Pinel, Barron, et al., 2024). Pasta sections were then colored with fast green solution at 1% (Sigma-Aldrich Co., USA) during 10 min, followed by 5 min with Lugol's solution (fluka, Buchs, Switzerland) diluted 1:16 (v/v) to stain proteins and starch granules respectively. Bright field images were acquired using a Ti2 microscope (Nikon, Japan) equipped with a color digital camera (Fi3, Nikon, Japan). Observations were made with a plan Apo 10x objective (Nikon, Japan). NIS-Element Viewer (version 5.21.00, Nikon, Japan) was used to approximate starch granule size of samples.

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### 2.5.2. Extractability of protein from dry and cooked pasta

Two protein extractions on dry and cooked cowpea and wheat-based pasta were performed in triplicate according to Pinel, Barron, et al. (2024). The first extraction was in SDS buffer to extract weakly-bonded proteins (i.e. SDS-soluble, linked by hydrogen bonds). The second extraction was in DTE buffer to extract weakly-bonded and disulfide-bonded proteins (SDS + DTE soluble proteins). Disulfide-bonded proteins (DTE-soluble) were then obtained by subtraction between 'SDS + DTE soluble proteins' and 'SDS-soluble proteins'. The remaining protein fraction, insoluble in SDS-DTE (non-extractable) represents proteins linked by covalent bonds other than disulfides. The protein content of each extraction was performed by measuring nitrogen amount by Kjeldahl method (NF V03-050, 1970) according to Pinel, Barron, et al. (2024). All protein fractions were expressed in percentage of total proteins contained in the pasta.

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## 2.6. *In vitro* protein digestibility
In vitro protein digestion of cooked cowpea and wheat-based pasta was performed using two methods: The static Infogest in vitro digestion (Brodkorb et al., 2019; Minekus et al., 2014), and a commercial enzymatic kit K-PDCAAS (Megazyme 2019). Both protocols are detailed in 2.6.1 and 2.6.4 sections below and a comparison of their experimental conditions is detailed in Figure 2.

## 2.6.1. *Static in vitro Infogest digestion protocol*

The enzyme activities of salivary amylase, pepsin and pancreatin were measured in triplicate as described in Brodkorb et al. (2019). Pepsin and pancreatin were diluted in water or simulated intestinal fluid and kept in stirred ice-bath for 5 or 30 minutes, respectively, before being added to the digestion tube to limit enzyme autolysis. The first step was the hydration with ultrapure water (Merck, Fontenay-sous-bois) of 100 mg of cooked, freeze-dried and ground pasta (1:4 w/w, sample/water) to obtain a dough. Then, in vitro digestion was carried out in an incubator with rotary shaking at 37 °C as follows: The oral phase consisted of 2 min of mixing of pasta and human salivary amylase (182 U/mg, A1031, Sigma, St Louis, US; 75 U/mL in final digestion mixture) leading to a 1:1 meal to secretion ratio at pH 7. The second phase, gastric phase lasted 60 min and consisted of a mix of the oral phase and the porcine pepsin (1763 U/mg, P6887, Sigma, St Louis, US; to get 2000 U/mL in final gastric mixture) leading to a final ratio of a 0.25:0.75 meal to secretion and adjusted to pH3. A 60 min gastric phase was chosen, following the study of Berrazaga et al. (2020) who performed a 60 min gastric phase of Infogest digestion for legume-based pasta, as there was little additional proteolysis observed on pasta between 60 to 120 min. The last step, intestinal phase lasted 120 min, consisted of a mix of the gastric mixture with porcine pancreatin (5.9 U of trypsin/mg pancreatin, P7545, Sigma, St Louis, US, 100 U/mL in final digestion mixture), porcine bile (1.9 mmol/g, B8631, Sigma, St Louis, US, 10mM in the
final mixture) to a final ratio of a 0.125:0.87.5 meal to secretion and adjusted to pH7. The *in vitro*
protein digestion was performed in quadruplicate for each cowpea and wheat-based pasta.
Sampling were realized at the beginning of the digestion (T0), at the end of oral phase (O2), after
5 min (G5) and 60 min (G60) of gastric phase and after 2 (I2) and 120 (I120) min in of intestinal
phase. Each tube per sampling time was performed. Inhibition of salivary amylase was performed
by freezing the sample. Then, proteolysis was stopped by adding pepstatin A (P5318, Sigma, St
Louis, US, 50 µL/mL of digesta) in the gastric samples and by adding pefabloc 0.1M (76307,
Sigma, St. Louis, US, 50 µL/mL of digesta) in the intestinal samples. Digesta were then
centrifuged at 10000 rpm for 15 min at 4°C and the respective supernatants and pellets were deep
frozen in liquid nitrogen before further analysis.

Three blank digestions were performed. Blank 1 consisted of pepsin and pancreatin
diluted as mentioned above and following their respective preparation time only. Blank 2 was
obtained by replacing the pasta sample by 100 mg of potato starch during all the digestion
protocol and contained the same quantity of enzymes as for pasta samples. Blank 3 contained no
enzyme and was based only on the undigested samples diluted in the same ratio as the gastric and
intestinal steps with the appropriate simulated digestive fluid. The 3 controls were performed in
triplicate, and blank 2 and 3 were made for each kinetic point.

2.6.2. Protein degree of hydrolysis

Free amino group content in the supernatants of all the samples were determined with a
ninhydrin assay according to Prochazkova et al. (1999) with some modifications. Briefly, 200 µL
of ninhydrin 2% (N7285, Sigma, St Louis, US) was added to 200 µL of sample or leucine
calibration range. Samples were heated in boiling water-bath during 30 min, and cooled 5 min in
ice-bath. The samples were then diluted with 1 mL of 50% (v/v) ethanol/water. The absorbance
was measured at 570 nm on a microplate reader (Spark Tecan, Tecan Trading, Ldt., Switzerland).
The protein hydrolysis degree were calculated based on the amount of free amino groups released at each kinetic points ([NH₂]t) corrected by dilution factors, as compared to the total amino groups of the different pasta ([NH₂]TOT determined after total hydrolysis with HCl 6N for 24h at 105°C) and corrected by the different blank digestions: a digestion without enzyme ‘blank 3’ ([NH₂]blank3) and auto-proteolysis ([NH₂]et) for each kinetic point according to the Equation 1. [NH₂]et is the average of free amino groups released in blanks 1 and 2.

$$ \text{Protein hydrolysis degree} = \frac{[\text{NH}_2]_t - [\text{NH}_2]_{\text{blank3}} - [\text{NH}_2]_{\text{et}}}{[\text{NH}_2]_{\text{TOT}} - [\text{NH}_2]_{\text{blank3}}} * 100 (\%) \quad \text{Eq (1)} $$

$$ \text{With } [\text{NH2}]_{\text{et}} = \frac{[\text{NH2}]_{\text{blank1}} + [\text{NH2}]_{\text{blank2}}}{2} $$

### 2.6.3. Apparent in vitro protein digestibility

The apparent *in vitro* protein digestibility of cowpea and wheat-based pasta was estimated on the supernatant of the digestion samples at 1120, and consisted of the proportion of the soluble nitrogen after 10 kDa filtration to the total nitrogen reported by Cave (1988). Briefly, 750 µL of sample supernatants were diluted twice in ultrapure water (Merck, Fontenay-sous-bois) and were ultrafiltered three times using a 10 kDa Vivaspin® Polyethersulfone centrifugal filter (Vivaspin® 500, 10 kDa MWCO, PES, Sartorius Stedim Biotech GmbH, Goettigen, Germany) for 20 minutes at 8 000 rpm. The three filtrates were combined and frozen. Total soluble nitrogen content in sample and the 10 kDa fractions were analysed by Kjeldahl method (NF V03-050, 1970). The apparent *in vitro* digestibility were calculated according to following Equation 2:

$$ \text{Apparent in vitro Digestibility} = \frac{N_{<10 \text{ kDa}}}{N_{\text{Total}}} * 100 (\%) \quad \text{Eq (2)} $$
Where $N_{<10kDa}$ corresponds to the amount of nitrogen in the fraction below 10 kDa (in g/100g pasta), and $N_{Total}$ corresponds to the total amount of nitrogen in the soluble fraction at the end of intestinal phase (in g/100g pasta) (Ducrocq et al., 2024).

### 2.6.4. Protein in vitro digestibility by enzymatic kit

In a second time the *in vitro* protein digestibility was determined using Megazyme® enzymatic K-PDCAAS kit by following manufacturer's protocol (Megazyme 2019). For the sake of comparison, the enzyme activities of pepsin and trypsin at pH 2 and 7.4 respectively, were measured in triplicate as described in Infogest digestion protocol although such enzyme activity measurements were not required in the Megazyme® protocol. The kit is composed of six protein standards (from A to F) and of a casein control sample. The enzymatic kit digestion is divided in two phases, both carried out in an incubator with rotary shaking at 37°C. With the kit, the first phase corresponded to 'gastric phase' at pH 2 during 60 min using pepsin (11.7 U/mL in final digestion mixture). The second phase was the 'intestinal phase' at pH 7.4 during 4 hours using trypsin and chymotrypsin (1.2 U/mL and 0.1 U/mL in the final digestion mixture, respectively). At the end of intestinal phase, proteolysis was stopped by heating in a boiling water-bath the samples. The *in vitro* protein digestion by enzymatic kit was realized in triplicate on each cowpea and wheat-based pasta, on Megazyme® standards and on casein control. Again, free amine groups released during digestion were measured with Ninhydrin assay similarly to 2.5.2 section but compared to a calibration curve of glycine this time. This glycine calibration curve was required in Megazyme (2019) protocol. This amine group concentration was then corrected as explained in the Megazyme® kit by the concentration of proline, lysine, histidine and arginine according to the patent N°US9738920B2 (Plank, 2017) to obtain the 'corrected amine group concentration'. The corrected amine group concentration of the six Megazyme® standards and
casein control have been indeed correlated with the corresponding protein digestibility literature
values of rat in vivo model which leads to a linear regression equation (Equation 3). Protein in
vitro digestibility (based on this in vivo rat model correlation) of pasta samples were then
calculated using their ‘corrected amine group concentration’ in the Equation 3 previously
obtained:

$$
331 \quad \text{Megazyme}\text{®} \text{ protein in vitro digestibility} = A \times \text{Corrected amine group concentration} + B (\%) \quad (\text{Eq 3})
$$

332 Where A is the slope (0.58 in our study) and B the y intercept (75.80 in our study) of the linear
333 regression.

2.7. *I*-PDCAAS calculation

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*I*-PDCAAS (*i*-PDCAAS) of pasta were calculated from Infogest digestion and

Megazyme® protocols following the Equation 4 and 5, respectively. Infogest *i*-PDCAAS was
calculated from the apparent *in vitro* digestibility according to Le Roux et al. (2020) whereas

Megazyme® *i*-PDCAAS was calculated from Megazyme® protein *in vitro* digestibility score as
described in Megazyme® protocol. The two *i*-PDCAAS of pasta sample were thus obtained by
multiplying apparent Infogest digestion *in vitro* digestibility or Megazyme® protein *in vitro*
digestibility of pasta with their Chemical Score (CS):

$$
342 \quad \text{Infogest } i - \text{PDCAAS} = \text{Apparent in vitro digestibility} \times \text{CS}_I \, (\text{Eq 4})
$$

$$
343 \quad \text{Megazyme}\text{®} \ i\text{-}\text{PDCAAS} = \text{Megazyme}\text{®} \ \text{in vitro digestibility score} \times \text{CS}_M \ (\text{Eq 5})
$$

with $CS_I$ and $CS_M$ which are calculated as follows (Equation 6):

$$
345 \quad CS = \frac{\text{Content of limiting eaa}}{\text{Content of this eaa in the reference protein of FAO 2011}} \quad (\text{Eq 6})
$$
With CS=Chemical Score, eaa= essential amino acid, the Content of limiting essential amino acid is expressed in g/100g protein and Content of this essential amino acid in the reference protein of FAO 2011 is also expressed in g/100g protein. Kjeldahl or Dumas methods were used respectively for the total protein content for the Chemical score Infogest noted hereafter "chemical scoreI" and the Chemical score Megazyme noted hereafter "Chemical scoreM".

Aminograms (NF EN ISO 13903) were determined by CAPINOV laboratory (Landerneau, France) (Pinel, Barron, et al., 2024b).

## 2.8. Statistical analysis

Results are expressed as means ± standard deviation. Variance analysis (ANOVA) with Fisher's least significant difference (LSD) test, and a Pearson correlation matrix were used to compare means at the 5% significance level by using XLStat (Addinsoft, v 2022, Paris, France).

Means with significant difference at p<0.05 are represented with different letters.

# 3. Results

## 3.1. Multi-scale study of pasta structure and granulometry of pasta before digestion

### 3.1.1. Microscopic structure

Bright field light microscopy was used to observed the microscopic structure of cooked pasta. Figure 3 2 showed central region views of cooked S, CW and CW-TEF pasta which were representative of wheat-based and cowpea-based pasta. Starch granules (in blue-violet) were entrapped in a protein network (green) in cowpea-based and S pasta, with a more heterogeneous repartition in cowpea-based pasta compared to S. Lower starch granules density was observed in cowpea-based compared to wheat-based pasta. Starch granule shapes were also different with
small spherical starch granules observed for cowpea-based pasta (diameter around 15 µm, n=30 starch granules), whereas elongated oval starch granules were observed in wheat-based pasta (8 µm × 25-30 µm, n=30). Among cowpea-based pasta, the addition of teff seemed to lead to starch granules that were more diffuse and entrapped into the protein network.

Before being digested, to normalize the mesoscopic state of the pasta meal, the pasta were lyophilized and ground at a similar D50 of 253 ± 24 µm (Figure 1). Clinical data obtained by Hoebler et al. (1998) on masticated spaghetti during oral phase showed that the mode of the particle size of chewed spaghetti particles is around 1.4 mm, thus well above our values for freeze-dried and ground cooked pasta. The choice of solid meal pretreatments (freeze-drying and fine-particle grinding) ahead of *in vitro* digestion protocol had an impact on digestibility by increasing in particular specific surface area of pasta samples. In our case, we observed an increase of *in vitro* starch digestibility with the use of these pretreatments (results not shown). However, it was the most reasonable and convenient way to standardize water content, stabilize matrices and ease comparisons between matrices.

### 3.1.2 Supramolecular structure of the pasta protein network

Results of protein extractability of wheat-based and cowpea-based pasta are presented in Figure 4. Covalent-bonded proteins (DTE-soluble and non-extractable proteins) were 1.5 to 2.3 times lower in cooked cowpea-based pasta compared to wheat-based pasta, with 2 to 3 times lower proteins bonded by disulfide bonds (DTE-soluble, Figure 4). These results pointed out the weaker protein network of cowpea-based pasta compared to wheat-based. Regarding wheat-based pasta, a linear decrease of disulfide-bonded proteins from 87 to 71% was observed between S and HFS cooked pasta considering the increase of fibers in wheat-based pasta (R²= 0.9574, Figure
393 4B). Regarding cowpea-based pasta, formulations containing teff (CW-TEF and CW-TEF-AL) had lower SDS-soluble protein than other CW and CW-AL (47% vs. 61%), and higher DTE-soluble and non-extractable proteins (total of these two parameters= 52% vs. 38%), resulting in a higher state of the protein aggregation. Linear decrease in DTE-soluble and increase in SDS-soluble proteins with an increasing sulphur amino acid content were observed in cowpea-based pasta (R²= 0.95 and 0.96 respectively, Figure 4C). However, no significant linear relationship was found with fiber content of cowpea-based (results not shown) whereas a linear decrease in DTE soluble proteins with fiber content was observed in wheat-based pasta (R²= 0.96, Figure 4B).

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### 3.2. Kinetics of the protein hydrolysis degree during in vitro digestion

404 Protein hydrolysis degree obtained during oral, gastric and intestinal in vitro digestion (Infogest digestion model) of cowpea-based and wheat-based pasta are presented in Figure 5. At 405 the end of gastric phase proteolysis reached 3-6%, with a lower protein hydrolysis for S pasta. As 406 expected, the most significant part of proteolysis occurred during the intestinal phase, with the 407 protein hydrolysis degree range around 53-73% at the end of this phase (I120). It was 408 characterized by a rapid rate with half of the protein hydrolysis degree (32-42%) taking place 409 within the two first minutes, as already reported by Berrazaga et al. (2020). Despite this broad 410 distribution, there was no significant difference in the protein hydrolysis degree between cowpea- 411 based and wheat-based pasta at the end of the intestinal phase (Figure 5). Among wheat-based 412 pasta, HFS stood out with a protein hydrolysis degree 30 to 35% higher than WS and S, whereas 413 there was no significant difference of protein hydrolysis degrees (60-69%) among cowpea-based 414 pasta. 415
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### 3.3. Protein *in vitro* digestibility indicators at the end of intestinal phase and *i*-PDCAAS

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Protein *in vitro* digestibility indicators (i.e. apparent digestibility from Infogest digestion and Megazyme® digestibility score) and the corresponding *i*-PDCAAS are presented in Figure 6. Infogest apparent digestibility of pasta ranged from 60 to 78% with no significant difference between cowpea-based pasta and S and HFS. Among wheat-based pasta there was no linear relationship between fiber content and Infogest apparent digestibility (R² = 0.0165, Figure 6). WS stood out with a Infogest apparent digestibility 15% higher than S and HFS, and was the only one to have a Infogest apparent digestibility 10 to 22% higher than cowpea-based pasta. Concerning cowpea-based pasta, CW-AL differed significantly from the others with a 14% higher Infogest apparent digestibility. Megazyme® digestibility scores ranged from 83 to 92% with this time lower scores for cowpea-based pasta (83-85%) compared to wheat-based pasta (90-92%). Among wheat-based pasta, Megazyme® digestibility scores linearly decreased with the increase of fiber content (R² = 0.9402, Figure 6). For cowpea-based pasta, the addition of teff (CW-TEF) decreased slightly but significantly Megazyme® digestibility scores. This decrease was even more pronounced with the combined addition of amaranth leaf. However, the addition of amaranth leaves alone (CW-AL) did not impact the Megazyme® digestibility score.

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The *i*-PDCAAS is based on the chemical score of protein (i.e. resulting of the essential amino acid content, cf Eq 6) and its *in vitro* digestibility. In our study, the *in vitro* digestibility corresponds to either Infogest apparent digestibility or Megazyme® digestibility score, according to the protocol used. The *i*-PDCAAS of cowpea-based pasta was twice higher than *i*-PDCAAS of wheat-based pasta, regardless of the digestion protocol and the protein *in vitro* digestibility

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indicator used in the calculation. This was attributed to the chemical score of cowpea-based pasta being twice higher compared of wheat-based pasta (Table 2). Similar or slight increase of *i*-PDCAAS values were observed for WS and HFS compared to S pasta, depending on the protocol used. There was no difference in *i*-PDCAAS among cowpea-based pasta in either protocol, except for a higher *i*-PDCAAS for CW-AL, which was only observed with the Infogest digestion method.

<table><caption>**Table 2** Chemical scores of Infogest and Megazyme® method for cooked wheat-based and cowpea-based pasta (Pinel, Barron, et al., 2024b)</caption><thead><tr><th></th><th>Chemical Score<sub>I</sub></th><th>Chemical Score<sub>M</sub></th></tr></thead><tbody><tr><td>S</td><td>53 ± 7</td><td>53 ± 7</td></tr><tr><td>WS</td><td>57 ± 7</td><td>57 ± 7</td></tr><tr><td>HFS</td><td>63 ± 8</td><td>63 ± 8</td></tr><tr><td>CW</td><td>117 ± 10</td><td>116 ± 10</td></tr><tr><td>CW-AL</td><td>123 ± 11</td><td>122 ± 11</td></tr><tr><td>CW-TEF</td><td>112 ± 15</td><td>112 ± 15</td></tr><tr><td>CW-TEF-AL</td><td>118 ± 15</td><td>119 ± 15</td></tr></tbody></table>

Chemical score<sub>I</sub> and Chemical score<sub>M</sub> were calculated by using Kjeldahl or Dumas method respectively

Concerning differences between Infogest digestion and Megazyme® methods, absolute values of protein *in vitro* digestibility indicators and consequently *i*-PDCAAS were 17 to 42% higher for Megazyme® than for Infogest digestion protocol. In addition, standard deviations obtained with Megazyme® were much lower than those obtained with the Infogest digestion method, which resulted in more significant differences between samples compared to the Infogest digestion method.

### 3.4. Factors influencing *in vitro* protein hydrolysis and digestibility indicators
A Pearson correlation matrix was set up and resumed in Table 3 to highlight positive or negative correlations between intrinsic properties (proteins, fibers, TIA, phytic acid, DTE-soluble proteins, particle size) of cowpea-based and wheat-based pasta samples and their *in vitro* protein hydrolysis and digestibility indicators.

Protein hydrolysis degree (at 120 min of intestinal phase, I120) and Infogest apparent digestibility were not significantly correlated with any intrinsic parameters (protein, fiber, phytic acid, TIA), nor with physical parameters (D50) nor protein network parameter (DTE-soluble protein) entered in the correlation matrix. Only a trend of a positive correlation between protein hydrolysis degree at I120 and fiber content was observed (0.696, p= 0.082). On the other hand, Megazyme® digestibility score was positively correlated with DTE-soluble protein content (0.966) and negatively correlated with TIA (-0.934) of samples. Additionally, a trend of negative correlations between protein or fiber content, and Megazyme® digestibility score was noticed. Concerning *i*-PDCAAS of samples, they are correlated positively with protein and fiber contents, TIA, and negatively correlated with DTE-soluble proteins. There was also strong positive correlation between *i*-PDCAAS obtained by both methods (0.972), which could be expected.
<table><caption>472 Table 3 Correlation matrix between parameters in cooked wheat-based and cowpea-based pasta</caption><thead><tr><th>Variables</th><th>Protein (%)</th><th>Fiber (%)</th><th>Phytic acid (%)</th><th>TIA (%)</th><th>D50 (µm)</th><th>DTE-soluble proteins (%)</th><th>Protein hydrolysis degree (%)</th><th>Infogest Apparent digestibility (%)</th><th>Megazyme® digestibility score (%)</th><th>i-PDCAAS Infogest</th><th>i-PDCAAS Megazyme®</th></tr></thead><tbody><tr><td>Protein (%)</td><td>1</td><td>0.737</td><td>0.377</td><td><strong>0.927</strong></td><td>-0.444</td><td><strong>-0.890</strong></td><td>0.241</td><td>-0.439</td><td>-0.754</td><td><strong>0.885</strong></td><td><strong>0.897</strong></td></tr><tr><td>Fiber (%)</td><td></td><td>1</td><td><strong>0.845</strong></td><td>0.721</td><td>-0.156</td><td><strong>-0.826</strong></td><td>0.696</td><td>-0.236</td><td>-0.747</td><td><strong>0.818</strong></td><td><strong>0.781</strong></td></tr><tr><td>Phytic acid (%)</td><td></td><td></td><td>1</td><td>0.477</td><td>0.192</td><td>-0.636</td><td>0.626</td><td>-0.211</td><td>-0.649</td><td>0.541</td><td>0.543</td></tr><tr><td>TIA (%)</td><td></td><td></td><td></td><td>1</td><td>-0.323</td><td><strong>-0.979</strong></td><td>0.185</td><td>-0.578</td><td><strong>-0.934</strong></td><td><strong>0.938</strong></td><td><strong>0.987</strong></td></tr><tr><td>D50 (µm)</td><td></td><td></td><td></td><td></td><td>1</td><td>0.276</td><td>0.309</td><td>-0.481</td><td>0.154</td><td>-0.467</td><td>-0.317</td></tr><tr><td>DTE-soluble proteins (%)</td><td></td><td></td><td></td><td></td><td></td><td>1</td><td>-0.318</td><td>0.515</td><td><strong>0.966</strong></td><td><strong>-0.961</strong></td><td><strong>-0.991</strong></td></tr><tr><td>Protein hydrolysis (%)</td><td></td><td></td><td></td><td></td><td></td><td></td><td>1</td><td>-0.162</td><td>-0.277</td><td>0.339</td><td>0.290</td></tr><tr><td>Infogest apparent digestibility</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>1</td><td>0.569</td><td>-0.331</td><td>-0.530</td></tr><tr><td>Megazyme® digestibility score (%)</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>1</td><td><strong>-0.909</strong></td><td><strong>-0.960</strong></td></tr><tr><td>i-PDCAAS Infogest</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>1</td><td><strong>0.972</strong></td></tr><tr><td>i-PDCAAS Megazyme®</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>1</td></tr></tbody></table>

473 Values in bold or in blue are considered as significant with p<0.05 or p<0.1 respectively; Protein, fiber, phytic acid and TIA values used in this

474 correlation matrix come from Pinel, Barron, et al. (2024); Protein hydrolysis degree = Free amino group released at the end of intestinal phase
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# 4. Discussion

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The first objective of this study was to determine the *in vitro* protein digestibility of nutritionally balanced and gluten-free innovative cowpea-based pasta in comparison to wheat-based pasta. As two different *in vitro* digestion protocols, Infogest digestion protocol and Megazyme® enzymatic kit, were used, we were able for the first time to compare and discuss these two internationally-used methods on these innovative cowpea-based pasta. The harmonized Infogest digestion protocol, which more closely mimics human physiology compared to the Megazyme® enzymatic kit, and is recognized for its suitability in evaluating protein digestibility (Santos-Sanchez et al., 2024), was selected for specific investigation of the link between pasta formulations, their structure (at microscopic and supramolecular levels), and *in vitro* protein digestibility. The impact of protein nature, fiber content and the addition of amaranth leaves on pasta structure and *in vitro* digestibility were therefore explored and discussed.

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## 4.1. *Impact of in vitro protein digestion protocols and methods on protein digestibility indicators and i-PDCAAS*

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Infogest digestion and Megazyme® protocols exhibited analogous trends when comparing *in vitro* protein digestibility indicators and *i*-PDCAAS of both wheat-based and cowpea-based pasta (Figure 6). A 5-7% or 7-9% decrease in Infogest apparent protein digestibility or Megazyme® digestion score was observed between wheat-based and cowpea-based pasta, with the exception of CW-AL pasta. This decrease was not significant for Infogest apparent protein digestibility. In addition, the *i*-PDCAAS were found to be twice as high in cowpea-based pasta compared to wheat-based pasta, irrespective of the utilized protocol nor calculation method. However, the comparison of the *in vitro* protein digestibility indicator or *i*-PDCAAS among cowpea-based pasta or among wheat-based pasta varied, depending on the
protocol used. Indeed, the addition of amaranth leaves and/or teff to cowpea-based pasta, or the impact of increasing fiber content in wheat-based pasta, resulted in opposite effects between Infogest digestion and Megazyme® protocols and indicators.

Additionally, the absolute value of the *in vitro* protein digestibility indicator, and therefore the *i*-PDCAAS as resulting from the multiplication with the chemical score (Table 2) of the sample were both 17-42% higher with Megazyme® than with Infogest digestion protocol. Given the number of samples that were tested, it was not possible to establish a precise conversion factor between the main indicators of both protocols.

Differences observed between the Infogest and Megazyme® *in vitro* protein digestibility indicators and *i*-PDCAAS can be probably linked to the differences reported between the two protocols. The Infogest digestion protocol (Brodkorb et al., 2019; Minekus et al., 2014) and the Megazyme® enzymatic kit (Megazyme 2019), both static *in vitro* digestion protocols, have been correlated on a limited number of food matrices to the results obtained *in vivo* in humans (milk proteins; Sanchon et al. (2018)) or in rats (cereal and legume flours, cereal-based products; Megazyme (2019)), respectively. The Infogest digestion protocol is designed to approximate *in vivo* digestion during *in vitro* protocol with the presence of proteases, amylases (alpha-amylase and pancreatic amylase), pancreatic lipase and bile salts. The enzyme activities in the Infogest protocol are closely aligned with *in vivo* conditions. The pH is adjusted according to the matrix involved and the protocol utilizes oral, gastric and intestinal simulated fluids. Conversely, although *in vitro* conditions differ more from human gastrointestinal luminal conditions, correlation with *in vivo* digestion is taken into account for the Megazyme® enzymatic kit downstream of the protocol, during the calculation phase with the fitting with rat *in vivo* results. For instance, in our study, the amount of proteases presents in the Megazyme® protocol was considerably lower than in the Infogest digestion protocol. However, this discrepancy appeared to
be corrected by the *in vivo* rat fitting proposed in the Megazyme® protocol. The rat model is widely used as an animal model due to its correlation with human protein digestibility values. Nevertheless, the digestibility of poorly digestible proteins was overestimated in the rat model compared to the human model (Deglaire & Moughan, 2012), which can lead to higher absolute values of *in vitro* protein digestibility indicators.

In addition, the Infogest digestion protocol is more complex than the Megazyme® protocol, which results in higher standard deviations. This contributes to fewer significant differences among Infogest apparent digestibility measurements compared to those of Megazyme® digestibility scores. The very low standard deviations obtained with the Megazyme® protocol enabled the observation of significant differences between closely clustered Megazyme® digestibility scores. Indeed, while *in vitro* digestibility indicator values of both protocols (Infogest digestion and Megazyme®) exhibited a comparable decrease between wheat-based and cowpea-based pasta (5-9%), the cowpea-based pasta demonstrated slight but significant lower *in vitro* digestibility indicators using the Megazyme® protocol and compared to wheat-based pasta. However, this difference was not statistically significant when using the Infogest digestion protocol and indicators were employed.

Another potential explanation for the differences observed between Infogest and Megazyme® digestibility indicators may reside in the method used to obtain them. Infogest apparent digestibility is defined as the fraction of soluble nitrogen contained in molecules with a molecular weight of less than 10 kDa. This parameter has been shown to be a reliable predictor of *in vivo* protein digestibility (Cave, 1988), although several questions remain to be deepened to establish robust protein *in vivo/in vitro* correlations (Menard et al., 2023). Indeed, this parameter, due to ethical constraint has taken over from the evaluation of *in vivo* digestibility and has been widely employed on various ranges of protein of different origin. Menard et al. (2023) have
established recent *in vitro/in vivo* correlation and have reported apparent digestibility of 135, 92 and 71% for model meal with 4, 8 and 16% dietary protein (casein and gluten), with significant effect of protein level. In a similar trend, Ducrocq et al. (2024) reported an apparent digestibility of 57-60% for dough containing 20% of proteins (wheat and RubisCO, gluten and pea proteins).
Conversely, the Megazyme® *in vitro* protein digestibility indicator is based on the detection of free amino groups at the end of the intestinal phase without any distinction of size of the released molecules. This parameter has been shown to be somewhat more distant and less robust in establishing *in vitro/in vivo* correlations when compared to the apparent digestibility. Tavano et al. (2016) conducted systematic comparison of several *in vitro* digestibility parameters with *in vivo* ones, and reported significant differences between *in vitro* digestibility based on free amino groups released (i.e. hydrolysis degree) and true digestibility obtained with *in vivo* rat model.
Indeed, a hydrolysis degree of 42-49% was reported for chickpea flour after *in vitro* gastrointestinal digestion, whereas a true digestibility of 78% was observed in the rat model. This indicates that a limited number of peptide bond cleavages does not directly correlate with low protein digestibility *in vivo*. The difference between Infogest and Megazyme® *in vitro* protein digestibility indicators appears to be mainly linked to variations of protocol used rather than to the distinct methods employed for indicator calculation. Specifically, this is because the *in vivo* model was not taken into account during digestion protocol but afterwards, through calculation.
This difference was linked to the higher absolute values and lower standard deviations observed in Megazyme® *in vitro* protein digestibility scores, resulting in divergent interpretations compared to Infogest apparent digestibility.

*In vivo* PDCAAS is calculated by multiplying *in vivo* true digestibility with the chemical score. Despite its reported limitations (i.e. use of amino acid pattern based on minimum requirement instead of optimum intake, or the use of true faecal nitrogen digestibility instead of
ileal), PDCAAS remains widely used for the evaluation of protein quality (Schaafsma, 2012).
Tavano et al. (2016) compared *in vitro* and *in vivo* (rat model) PDCAAS on differently processed
chickpea flours against reference proteins (casein, albumin, total globulin). They concluded that
although no correlation was found between *in vitro* protein digestibility indicators such as
hydrolysis degree and *in vivo* true digestibility, i-PDCASS based on the hydrolysis degree (close
to the Megazyme® digestibility indicator method) showed good correlation with the *in vivo*
model. However, the Infogest and Megazyme® i-PDCAAS ranged from 68 to 86 and from 94 to
104, respectively (Figure 6). The Megazyme® i-PDCAAS were comparable to casein in Tavano
et al. (2016) (PDCAAS = 92), and align with the 99-125 range for soluble milk protein reported
by Tessier et al. (2021) in a rat model. Given the established high digestibility of casein and
soluble milk proteins, the observed values for Megazyme® i-PDCAAS might be considered an
overestimation, while Infogest i-PDCAAS appears more realistic.

## 4.2. Application of the Infogest digestion protocol to compare the protein quality and digestibility of cowpea-based vs. wheat-based pasta: does the structure of cowpea proteins at various scales result in difference of digestibility?

Protein quality is based on the essential amino acid composition, and the ability of the
protein to be digested and absorbed by the body (Berrazaga et al., 2019; Gaudichon, 2019; Leser,
2013)). The protein quality of pasta could be impacted by the origin of reserve proteins which
affects the organization levels of proteins (from primary sequence to ternary structure) and their
structuration in a homogeneous network surrounding partially gelatinized starch granules (Joye,
2019).

Concerning cowpea-based pasta, the essential amino acid composition of their proteins
allowed to obtain a chemical score of all cowpea-based pasta above 100 and twice higher than
wheat-based pasta (Table 2).
Pepsin preferentially cleaves peptide bonds involving leucine, phenylalanine, tryptophan and tyrosine residues (Sah et al., 2016). In contrast trypsin prefers cleaving at the carboxyl side of arginine or lysine residues, which are not linked to proline residue (Cheison et al., 2011). Focusing on comparison with S, all cowpea-based pasta contained 1.2 to 1.3 times more leucine, phenylalanine, tryptophan and tyrosine, and 1.5 to 2.8 times more arginine and lysine. Regarding the primary protein structure, their amino acid composition could therefore explain the slightly higher protein hydrolysis degree during gastric phase. However, this primary structure effect leveled off during the intestinal phase with similar hydrolysis degree and apparent digestibility (N <10 kDa) between cowpea-based and S pasta. Additionally, Bergman et al. (1996) reported a 4 to 7% decrease in *in vitro* protein digestibility at the end of intestinal phase when 10 to 30% cowpea flour was added to soft wheat pasta.

In addition to the primary sequence, other structural levels of proteins may have an impact on digestibility, especially during the intestinal phase. In our case the secondary structure of cowpea which has been deeply investigated in other studies could explain a lower digestibility compared to the one predicted by primary sequence only. The secondary structure of legumes such as cowpea is generally composed of β-sheets, β-strands and β-turns, with fewer α-helix. The prevalence of β-sheets has been associated with a decrease of protein digestibility due to limited access for proteases in various legume sources. Additionally, heat treatment such as cooking can cause β-sheets to aggregate, further reducing digestibility (reviewed by Shevkani et al. (2019)).

Thus considering the protein network structure in pasta, rather than focusing only on the protein structure itself is important. Cooked cowpea-based pasta exhibited a lower state of protein aggregation compared to wheat-based pasta. This was induced by lower covalently bond proteins and in particular the DTE-soluble proteins which were positively correlated with sulfur amino acid contents (Figure 4). Cowpea proteins reacted similarly to other legume proteins, showing a
similar proportion of protein linked by disulfide bonds in cooked pasta (30-36%) compared to 620 100% lentil or fava bean pasta (25-30% of DTE-soluble proteins) (Laleg et al., 2016). Cowpea- 621 based pasta presented a lower ability to cross-link and form disulfide bonds due to their lower 622 sulfur amino acid contents (1.5 times lower than in wheat-based) during cooking compared to 623 wheat proteins (Laleg et al., 2016; Petitot et al., 2010). This lower state of protein aggregation in 624 cowpea-based pasta, compared to wheat-based pasta, favors in vitro protein digestibility by 625 providing better accessibility of digestive enzymes to the proteins. 626

Both the structural levels of proteins and the state of protein aggregation within protein 627 significantly influence in vitro protein digestibility, sometimes conflicting ways: In our study, the 628 primary sequence and the state of protein aggregation had a favorable impact on in vitro protein 629 digestibility, while the secondary structure had a negative impact. The resultant is therefore in 630 favor of digestibility with cowpea addition in the pasta. However, the similar in vitro hydrolysis 631 degree at 1120 and apparent digestibility between cowpea-based and S pasta suggested that 632 another parameter may influence the protein digestibility of cowpea-based pasta. 633

### 4.3. A significant factor affecting digestibility: fiber content

The impact of fiber content can be explored in wheat-based pasta in which formulation 635 have increasing fiber content of 4.5, 11.2 and 18.9% (84 to 94% insoluble fibers, Pinel, Barron, et 636 al. (2024) for S, WS and HFS, respectively. In contrast, cowpea-based pasta, which have a high 637 fiber content (16.3-23.6%, Table 1), do not allow systematic observation of the impact of fiber 638 content on in vitro protein digestibility, as nature of fibers (from cowpea, teff or amaranth leaves) 639 and protein content (17 to 22%, Table 1) are variable between the four cowpea-based pasta. In 640 this study, the increase of fiber content was correlated with a decrease in DTE-soluble proteins 641 (i.e. a decrease of disulfide bonds; -0.826, Table 3) in cooked cowpea-based and wheat-based 642
pasta. Additionally, Pinel, Barron, et al. (2024) reported significantly higher fibrous structures at microscopic level with the increasing fiber content among wheat-based pasta, which intertwined with the protein network of pasta (Laleg et al., 2016) and created cracks and holes. This may explain the observed trend of a positive correlation between fiber content and protein hydrolysis degree (0.696) since a lower state of protein aggregation and disrupted protein network facilitate protease accessibility (Laleg et al., 2019). Tudorica et al. (2002) also reported a protein matrix disruption with the addition of 7.5% pea fiber in wheat pasta resulting in highly porous pasta structure. Regarding wheat-based pasta only, the increasing fiber content from 4.5 to 11.2% (S to WS) or from 4.5 to 18.9% (S to HFS) in cooked pasta did not have the same effect on protein digestibility. Indeed, the increase of fiber content from 4.5 to 18.9% had significantly positive impact on protein hydrolysis degree compared to the increase from 4.5 to 11.2%. The disruption of protein network and lower state of protein aggregation in wheat-based pasta induced by the increase of fibers had therefore no significant impact on the protein hydrolysis degree up to a threshold placed between 11 and 19% of fibers. On the other hand, 18.9% of fibers (HFS) decreased the apparent protein digestibility compared to 11.2% fibers (WS). Lin et al. (2019) reported that the presence of fiber increased the viscosity of the gastrointestinal tract contents, slowing proteases access to their substrate. From 11% fiber, the negative impact of fiber content offset the increase of protease accessibility induced by fibers, which led to similar apparent protein digestibility between HFS and S.

Additionally, fiber content is positively correlated with i-PDCAAS (0.818) thanks to the higher chemical score. The impact of fibers on chemical score is not very intuitive but can be explained by the fact that fibers were not added as a pure ingredient. Indeed, they contain proteins from the outer layer of the wheat kernel (bran, aleurone). Barton-Wright and Moran (1946) also reported a higher chemical score with increased fiber content, which can be explained
667 by the amino acid composition of the outer layer of wheat kernel used to produce whole wheat
668 flours.

669 4.4. Amaranth leaf flour: A promising ingredient for enhancing pasta protein quality

670 Regarding cowpea-based pasta, the addition of 10% amaranth leaf alone tended towards
671 an increase in the *in vitro* protein hydrolysis degree at I120, which was confirmed by the
672 significant increase in apparent protein digestibility. Additionally, the use of 10% amaranth leaf
673 flour in cowpea-based pasta led to a 1.2 times higher *i*-PDCAAS (86 vs. 70) (Figure 6). The
674 addition of amaranth leaves associated with teff flour in cowpea-based pasta resulted at the
675 opposite to a decrease in apparent protein digestibility and *i*-PDCAAS.

676 The addition of amaranth leaves to cowpea-based pasta did not impact the pasta and
677 protein network structure (Pinel, Barron, et al., 2024 and Figure 4), and did not lead to higher
678 pepsin or trypsin theoretical cleavage. However, amaranth leaf proteins, primarily RuBisCO, are
679 richer in essential amino acids, which increased the chemical score (Table 2) and thus *i*-PDCAAS. Ducrocq et al. (2024) reported a higher chemical score and *i*-PDCAAS in wheat
680 dough with 10% RuBisCO enrichment.
681

682 The high fiber content of amaranth leaf flour (46%, Pinel, Drogue, et al. (2024)) may also
683 impact positively protein digestibility of pasta by inducing a difference of density in the pasta
684 network and defects through which proteases can diffuse.

685 Proteins and fibers alone did not fully explain the impact of amaranth leaves addition on
686 *in vitro* protein digestibility. Pinel, Drogue, et al. (2024) reported 4.6 times lower phytic acid
687 content in amaranth leaf flour compared to cowpea flour which resulted in a reduction of phytic
688 acid content in pasta containing cowpea and 10% amaranth flour (CW-AL). This reduction in
689 phytic acid may also contribute to improved protein hydrolysis in CW-AL compared to CW, as
phytic acid is known to reduce protein digestibility by competing for mineral cofactors needed to activate protease and by direct interactions with proteins (Samtiya et al., 2020).

## 5. Conclusion

In conclusion, the determination of protein *in vitro* digestion by two internationally recognized methods have allowed us to observe 17 to 42% higher absolute values of *in vitro* digestibility score and thus i-PDCAAS for pasta samples with the enzymatic kit Megazyme® than with the Infogest digestion protocol and indicator. These difference seemed to be more related to the protocol variation than to the method used to obtain the protein *in vitro* digestibility indicators (free amino groups vs. N <10 kDa). However, ranking of the pasta was quite consensual. The enzymatic kit Megazyme®, which is cheaper and faster than the Infogest protocol, is suitable for preliminary research, however, the Infogest protocol, which is closer to human digestive physiology, is better suited to more advanced research. Concerning *in vitro* protein digestion of pasta samples, in addition to their higher nutritional composition, cowpea-based pasta maintained similar protein digestibility (protein hydrolysis degree at I120 and apparent protein digestibility) compared to traditional durum wheat semolina pasta, with a two times higher i-PDCAAS thanks to the essential amino acid composition. The addition of amaranth leaves in cowpea-based pasta had a higher impact than teff addition, with an improved apparent protein digestibility as well as the i-PDCAAS, making amaranth leaves an interesting ingredient for pasta nutritional optimisation. These results have shown that the *in vitro* protein digestibility of cowpea-based pasta was not only governed by protein origin, which impact protease cleavage sites and their accessibility to the substrate, but was also influenced by other factors such as fibers and antinutritional factor contents.

## Acknowledgment
713 The authors thank the PLANET facility (https://doi.org/10.15454/1.5572338990609338E12) run
714 by the IATE joint research unit for providing process experiment supports

715 **Funding**

716 This work was supported by Institut Agro Montpellier in the framework of Innofood Africa
717 project funded by the EU Horizon 2020 [Grant No 862170, 2020]. PhD funding for Pauline Pinel
718 was provided by Institut Agro Montpellier and La Région Occitanie, France.

719

720 **References**

721 Achigan-Dako, E. G., Sogbohossou, O. E. D., & Maundu, P. (2014). Current knowledge on
722 Amaranthus spp.: research avenues for improved nutritional value and yield in leafy amaranths in
723 sub-Saharan Africa. *Euphytica*, *197*(3), 303-317. https://doi.org/10.1007/s10681-014-1081-9

724 Adebowale, A.-R. A., Emmambux, M. N., Beukes, M., & Taylor, J. R. N. (2011). Fractionation
725 and characterization of teff proteins. *Journal of Cereal Science*, *54*(3), 380-386.
726 https://doi.org/10.1016/j.jcs.2011.08.002

728 Akeson, W. R., & Stahmann, M. A. (1964). A Pepsin Pancreatin Digest Index of Protein Quality Evaluation. *The Journal of Nutrition*, *83*. https://doi.org/10.1093/jn/83.3.257

731 Barton-Wright, E. C., & Moran, T. (1946). The microbiological assay of amino acids. II. The distribution of amino acids in the wheat grain *The Analyst*, *71*(843), 279-282.

734 Bergman, C., Gualberto, D. G., & Weber, C. W. (1996). Nutritional evaluation of high
temperature dried soft wheat pasta supplemented with cowpea. *Archivos latinoamericanos de
nutrition*, *46*(2), 146-152.

738 Berrazaga, I., Bourlieu-Lacanal, C., Laleg, K., Jardin, J., Briard-Bion, V., Dupont, D., Walrand, S., & Micard, V. (2020). Effect of protein aggregation in wheat-legume mixed pasta diets on their in vitro digestion kinetics in comparison to "rapid" and "slow" animal proteins. *PLoS One*, *15*(5), e0232425. https://doi.org/10.1371/journal.pone.0232425

743 Berrazaga, I., Micard, V., Gueugneau, M., & Walrand, S. (2019). The Role of the Anabolic
744 Properties of Plant- versus Animal-Based Protein Sources in Supporting Muscle Mass
745 Maintenance: A Critical Review. *Nutrients*, *11*(8). https://doi.org/10.3390/nu11081825
747 Bresciani, A., Pagani, M. A., & Marti, A. (2022). Pasta-Making Process: A Narrative Review on
748 the Relation between Process Variables and Pasta Quality. *Foods*, *11*(3).
749 https://doi.org/10.3390/foods11030256

751 Brodkorb, A., Egger, L., Alminger, M., Alvito, P., Assuncao, R., Ballance, S., Bohn, T.,
752 Bourlieu-Lacanal, C., Boutrou, R., Carriere, F., Clemente, A., Corredig, M., Dupont, D., Dufour,
753 C., Edwards, C., Golding, M., Karakaya, S., Kirkhus, B., Le Feunteun, S., Lesmes, U.,
754 Macierzanka, A., Mackie, A. R., Martins, C., Marze, S., McClements, D. J., Menard, O.,
755 Minekus, M., Portmann, R., Santos, C. N., Souchon, I., Singh, R. P., Vegarud, G. E., Wickham,
756 M. S. J., Weitschies, W., & Recio, I. (2019, Apr). INFOGEST static in vitro simulation of
757 gastrointestinal food digestion. *Nature Protocols*, *14*(4), 991-1014.
758 https://doi.org/10.1038/s41596-018-0119-1
759

760 Cárdenas-Hernández, A., Beta, T., Loarca-Piña, G., Castaño-Tostado, E., Nieto-Barrera, J. O., & 761 Mendoza, S. (2016). Improved functional properties of pasta: Enrichment with amaranth seed 762 flour and dried amaranth leaves. *Journal of Cereal Science*, 72, 84-90. 763
764 https://doi.org/10.1016/j.jcs.2016.09.014

765 Cave, N. A. (1988). Bioavailability of amino acids in plant feedstuffs determined by in vitro 766 digestion, chick growth assay, and true amino acid availability methods. *Poultry Science*, 67(1), 767 78-87. https://doi.org/10.3382/ps.0670078

769 Cheison, S. C., Lai, M.-Y., Leeb, E., & Kulozik, U. (2011). Hydrolysis of β-lactoglobulin by 770 trypsin under acidic pH and analysis of the hydrolysates with MALDI-TOF-MS/MS. *Food 771 Chemistry*, 125(4), 1241-1248. https://doi.org/10.1016/j.foodchem.2010.10.042

773 Chi-Wah, C., & Dixon, P. R. (1994). Amino Acid composition and subunit constitution of 774 protein fractions from cowpea seeds. *Journal of Agricultural and Food Chemistry*, 42 (9), 1857- 775 1860.
776

777 Deglaire, A., & Moughan, P. J. (2012). Animal models for determining amino acid digestibility 778 in humans - a review. *British Journal of Nutrition*, 108 *Suppl 2*, S273-281.
779 https://doi.org/10.1017/S0007114512002346

781 Ducrocq, M., Boire, A., Bourlieu-Lacanal, C., Barron, C., Nawrocka, A., Morel, M. H., Anton, 782 M., & Micard, V. (2024). In vitro protein digestibility of RuBisCO-enriched wheat dough: a 783 comparative study with pea and gluten proteins. *Food Function*, 15(9), 5132-5146.
784 https://doi.org/10.1039/d3fo05652j
785

786
787 Emmambux, M. N., & Taylor, J. R. N. (2013). Morphology, physical, chemical, and functional
788 properties of starches from cereals, legumes, and tubers cultivated in Africa: A review. *Starch*
789 **Stärke**, 65(9-10), 715-729. https://doi.org/10.1002/star.201200263

790 FAO. (2011). Dietary protein quality evaluation in human nutrition. Report of an FAO Expert
791 Consultation Auckland, New Zealand
792

793 Foschia, M., Horstmann, S. W., Arendt, E. K., & Zannini, E. (2017). Legumes as Functional
794 Ingredients in Gluten-Free Bakery and Pasta Products. *Annual Review of Food Science and
795 Technology*, 8, 75-96. https://doi.org/10.1146/annurev-food-030216-030045
796

797 Garcia-Valle, D. E., Bello-Pérez, L. A., Agama-Acevedo, E., & Alvarez-Ramirez, J. (2021).
798 Structural characteristics and in vitro starch digestibility of pasta made with durum wheat
799 semolina and chickpea flour. *Lwt - Food Science and Technology*, 145.
800 https://doi.org/10.1016/j.lwt.2021.111347
801

802 Gaudichon, C. (2019). Les critères de qualité des protéines ont-ils évolué ? *Médecine des
803 Maladies Métaboliques*, 13(3), 235-239. https://doi.org/10.1016/s1957-2557(19)30067-7
804

805 Gerloff, E. D., Lima, I. H., & Stahmann, M. A. (1965). Leaf proteins as foodstuffs - Amino acid
806 composition of leaf protein concentrates *Journal of Agricultural and Food Chemistry*, 13 (2),
807 139-143. https://doi.org/10.1021/jf60138a012
808

809 Hoebler, C., Karinthi, A., Devaux, M. F., Guillon, F., Gallant, D. J., Bouchet, B., Melegari, C., &
810 Barry, J. L. (1998). Physical and chemical transformations of cereal food during oral digestion in
811 human subjects. *British Journal of Nutrition*, 80(5), 429-436.
812 https://doi.org/10.1017/s0007114598001494
813

814 Hsu, H. W., Vavak, D. L., Satterlee, L. D., & Miller, G. A. (1977). A Multienzyme Technique for
815 Estimating Protein Digestibility. *Journal of food science*, 42(5), 1269-1273.
816 https://doi.org/10.1111/j.1365-2621.1977.tb14476.x
817

818 Joye, I. (2019, Jun 8). Protein Digestibility of Cereal Products. *Foods*, 8(6).
819 https://doi.org/10.3390/foods8060199
820

821 Laleg, K., Barron, C., Cordelle, S., Schlich, P., Walrand, S., & Micard, V. (2017). How the
822 structure, nutritional and sensory attributes of pasta made from legume flour is affected by the
823 proportion of legume protein. *LWT - Food Science and Technology*, 79, 471-478.
824 https://doi.org/10.1016/j.lwt.2017.01.069
825

826
827 Laleg, K., Cassan, D., Barron, C., Prabhasankar, P., & Micard, V. (2016). Structural, Culinary, Nutritional and Anti-Nutritional Properties of High Protein, Gluten Free, 100% Legume Pasta.
828 PLoS One, 11(9), e0160721. https://doi.org/10.1371/journal.pone.0160721
829

830 Laleg, K., Greffeuille, V., Walrand, S., & Micard, V. (2019). La structure des pâtes influence-t-elle leurs propriétés nutritionnelles ? *Cahiers de Nutrition et de Diététique*, 54(3), 151-163.
831
832
833 https://doi.org/10.1016/j.cnd.2019.02.005

834 Le Roux, L., Menard, O., Chacon, R., Dupont, D., Jeantet, R., Deglaire, A., & Nau, F. (2020). Are Faba Bean and Pea Proteins Potential Whey Protein Substitutes in Infant Formulas? An In Vitro Dynamic Digestion Approach. *Foods*, 9(3). https://doi.org/10.3390/foods9030362

838 Leser, S. (2013). The 2013 FAO report on dietary protein quality evaluation in human nutrition: Recommendations and implications. *Nutrition Bulletin*, 38(4), 421-428.
839
840
841 https://doi.org/10.1111/nbu.12063

842 Lin, Y., Chen, K., Tu, D., Yu, X., Dai, Z., & Shen, Q. (2019). Characterization of dietary fiber from wheat bran (Triticum aestivum L.) and its effect on the digestion of surimi protein. *Lwt - Food Science and Technology*, 102, 106-112. https://doi.org/10.1016/j.lwt.2018.12.024

846 Menard, O., Chauvet, L., Henry, G., Dupont, D., Gaudichon, C., Calvez, J., & Deglaire, A. (2023). The use of (15)N-labelled protein to account for the endogenous nitrogen contribution to in vitro protein digestibility measurement. *Food Research International*, 173(Pt 1), 113242.
847
848
849
850 https://doi.org/10.1016/j.foodres.2023.113242

851 Minekus, M., Alminger, M., Alvito, P., Ballance, S., Bohn, T., Bourlieu, C., Carriere, F., Boutrou, R., Corredig, M., Dupont, D., Dufour, C., Egger, L., Golding, M., Karakaya, S., Kirkhus, B., Le Feunteun, S., Lesmes, U., Macierzanka, A., Mackie, A., Marze, S., McClements, D. J., Menard, O., Recio, I., Santos, C. N., Singh, R. P., Vegarud, G. E., Wickham, M. S., Weitschies, W., & Brodkorb, A. (2014). A standardised static in vitro digestion method suitable for food - an international consensus. *Food Function*, 5(6), 1113-1124.
852
853
854
855
856
857
858 https://doi.org/10.1039/c3fo60702j

859 Ngalamu, T., Odra, J., & Tongun, N. (2015). Cowpea production handbook.
860

861 Nur Herken, E., İbanoglu, Ş., Öner, M. D., & İbanoglu, E. (2006). The in vitro protein digestibility, microbiological quality and gelatinization behaviour of macaroni as affected by cowpea flour addition. *Food Chemistry*, 98(4), 664-669.
862
863
864
865 https://doi.org/10.1016/j.foodchem.2005.06.042

866 Osborne, T. B. (1924). *The vegetable Proteins*. Longmans green and co.
867
868 Pasini, G., Simonato, B., Giannattasio, M., Peruffo, A. A. B., & Curioni, A. (2001).
869 Modifications of Wheat Flour Proteins during in Vitro Digestion of Bread Dough, Crumb, and
870 Crust: An Electrophoretic and Immunological Study. *Journal of Agricultural and Food
871 Chemistry*, 49, 2254-2261. https://doi.org/10.1021/jf0014260

873 Petitot, M., Boyer, L., Minier, C., & Micard, V. (2010). Fortification of pasta with split pea and
874 faba bean flours: Pasta processing and quality evaluation. *Food Research International*, 43(2),
875 634-641. https://doi.org/10.1016/j.foodres.2009.07.020

877 Petitot, M., Brossard, C., Barron, C., Larré, C., Morel, M.-H., & Micard, V. (2009). Modification
878 of pasta structure induced by high drying temperatures. Effects on the in vitro digestibility of
879 protein and starch fractions and the potential allergenicity of protein hydrolysates. *Food
880 Chemistry*, 116(2), 401-412. https://doi.org/10.1016/j.foodchem.2009.01.001

882 Pinel, P., Drogue, S., Amiot-Carlin, M. J., Vannier, C., Bourlieu-Lacanal, C., & Micard, V.
883 (2024a). Nutritional optimization through linear programming of climate-smart and gluten free
884 pasta. *Lwt - Food Science and Technology*, 197. https://doi.org/10.1016/j.lwt.2024.115899

886 Pinel, P., Barron, C., Cassan, D., Robert, M., Bourlieu-Lacanal, C., & Micard, V. (2024b).
887 Culinary properties, nutritional quality, and in vitro starch digestibility of innovative gluten-free
888 and climate smart cowpea-based pasta. *Lwt - Food Science and Technology*, 211.
889 https://doi.org/10.1016/j.lwt.2024.116917

891
892
893 Pinel, P., Emmambux, M. N., Bourlieu, C., & Micard, V. (2023, Nov 8). Nutritional
894 contributions and processability of pasta made from climate-smart, sustainable crops: A critical
895 review. *Critical Reviews in Food Science and Nutrition*, 1-31.
896 https://doi.org/10.1080/10408398.2023.2271952

897
898 Plank, D. W. & Golden Valley, M.N. (2017). *In vitro method for estimating in vivo protein digestibility*, United States Patent No. US 9,738,920 B2
899

900 Prochazkova, S., Varum, K. M., & Ostgaard, K. (1999). Quantitative determination of chitosans by ninhydrin. *Carbohydrate Polymers* 38, 115-122. https://doi.org/10.1016/S0144-8617(98)00108-8

904 Sah, B. N. P., McAinch, A. J., & Vasiljevic, T. (2016). Modulation of bovine whey protein
905 digestion in gastrointestinal tract: A comprehensive review. *International Dairy Journal*, 62, 10-
906 18. https://doi.org/10.1016/j.idairyj.2016.07.003

908
909 Samtiya, M., Aluko, R. E., & Dhewa, T. (2020). Plant food anti-nutritional factors and their reduction strategies: an overview. *Food Production, Processing and Nutrition, 2*(1).
911 https://doi.org/10.1186/s43014-020-0020-5

912 Sanchon, J., Fernandez-Tome, S., Miralles, B., Hernandez-Ledesma, B., Tome, D., Gaudichon, C., & Recio, I. (2018). Protein degradation and peptide release from milk proteins in human jejunum. Comparison with in vitro gastrointestinal simulation. *Food Chemistry, 239*, 486-494.
915 https://doi.org/10.1016/j.foodchem.2017.06.134

917 Santos-Sanchez, G., Miralles, B., Brodkorb, A., Dupont, D., Egger, L., & Recio, I. (2024). Current advances for in vitro protein digestibility. *Frontiers in Nutrition, 11*, 1404538.
920 https://doi.org/10.3389/fnut.2024.1404538

921 Schaafsma, G. (2012). Advantages and limitations of the protein digestibility-corrected amino acid score (PDCAAS) as a method for evaluating protein quality in human diets. *British Journal of Nutrition, 108* *Suppl 2*, S333-336. https://doi.org/10.1017/S0007114512002541

925 Schalk, K., Lexhaller, B., Koehler, P., & Scherf, K. A. (2017). Isolation and characterization of gluten protein types from wheat, rye, barley and oats for use as reference materials. *PLoS One*, 12(2), e0172819. https://doi.org/10.1371/journal.pone.0172819

929 Shevkani, K., Singh, N., Chen, Y., Kaur, A., & Yu, L. (2019, Jun). Pulse proteins: secondary structure, functionality and applications. *Journal of Food Science and Technology*, 56(6), 2787-2798. https://doi.org/10.1007/s13197-019-03723-8

933 Tavano, O. L., Neves, V. A., & da Silva Junior, S. I. (2016, Nov). In vitro versus in vivo protein digestibility techniques for calculating PDCAAS (protein digestibility-corrected amino acid score) applied to chickpea fractions. *Food Research International, 89*(Pt 1), 756-763.
937 https://doi.org/10.1016/j.foodres.2016.10.005

938 Taylor, J. R. N., Taylor, J., Campanella, O. H., & Hamaker, B. R. (2016). Functionality of the storage proteins in gluten-free cereals and pseudocereals in dough systems. *Journal of Cereal Science, 67*, 22-34. https://doi.org/10.1016/j.jcs.2015.09.003

942 Tessier, R., Calvez, J., & Gaudichon, C. (2021). Les « dessous » du PD-CAAS et du DIAAS, deux critères en apparence simples de qualité nutritionnelle des protéines. *Cahiers de Nutrition et de Diététique, 56*(2), 102-110. https://doi.org/10.1016/j.cnd.2021.02.002

946 Thornber, J. P. (1975). Chlorophyll-Proteins: Light-Harvesting and restion center components of plants. *Annual review of plant physiology*, 26 (1), 127-158.
949 https://doi.org/10.1146/annurev.pp.26.060175.001015
950
951 Tudorica, C. M., Kuri, V., & Brennan, C. S. (2002). Nutritional and physicochemical
952 characteristics of dietary fiber enriched pasta. *Journal of Agricultural and Food Chemistry, 50*
953 (2), 347-356. https://doi.org/10.1021/jf0106953

954

955 Web references

956 Canadian Nutrition File. (2022). Retrieved from https://food-nutrition.canada.ca/cnf-fce/index-
957 eng.jsp; Accessed May 20th 2024.

958 H2020 European Innofood Africa project (2024). Retrieved from https://innofoodafrica.eu/
959 Accessed July 15th 2024.

960 Megazyme (2019) Protein digestibility assay procedure – Animal-Safe Accurate Protein Quality
961 Score for determination of the Protein Digestibility Amino Acid Score (PDCAAS). Retrieved from
962 https://www.megazyme.com/documents/Assay_Protocol/K-PDCAAS_DATA.pdf. Accessed April
963 18th 2024.

964
<figure><img src="image_3.png" /><figcaption>**Figure 1** Particle size distribution of cooked pasta samples (i.e. cooked freeze-dried and ground)</figcaption></figure>

S = durum wheat semolina pasta; WS = whole durum wheat semolina pasta; HFS = durum wheat semolina enriched with bran pasta; CW = 100% cowpea; CW-AL = 90% cowpea + 10% amaranth leaf pasta; CW-TEF = 60% cowpea + 40% teff pasta; CW-TEF-AL = 55% cowpea + 35% teff + 10% amaranth leaf pasta
<figure><img src="image_4.png" /><figcaption>**Figure 2** Static *in vitro* digestibility by infogest and Enzymatic kit Megazyme® methods</figcaption></figure>

¹Adapted from Minekus et al. (2014) and Brodkorb et al. (2019)

970

971

972

973
<figure><img src="image_5.png" /><figcaption>**Figure 3** Light microscopy of traditional durum wheat semolina pasta S (A), CW (B) and CW-TEF (C) central regions (i.e. cross sections of freshly cooked pasta)</figcaption></figure>

*Field of view = 300 µm×300µm; Proteins were stained with Fast Green (green on the image) and starch granules with lugol (blue-violet in the image);*
A

<figure><img src="image_6.png" /></figure>

B

<figure><img src="image_7.png" /></figure>

C

<figure><img src="image_8.png" /></figure>

980

Figure 4 Protein solubility in Sodium Docetyl Sulfate (SDS) and dithioerythritol (DTE) of cooked wheat-based and cowpea-based pasta (A), and their relation to the fiber content in wheat-based pasta (B) and to the sulfur amino acid content in cowpea-based pasta (C)

Bars with the same letter within a same fraction are not significantly different (p < 0.05); Mean ± standard deviation of three repetitions;

986

987
<figure><img src="image_9.png" /><figcaption>**Figure 5** Kinetics of protein hydrolysis degree during *in vitro* digestion of cowpea-based and wheat-based pasta</figcaption></figure>

Same letter within a same kinetic point are not significantly different (p <0.05); Mean ± standard deviation of four repetitions; O2 = 2 min of the oral phase (end); G5 = 5 min of gastric phase; G60 = 60 min of the gastric phase (end); I2 = 2 min of intestinal phase; I120 = 120 min of the intestinal phase (end);
<figure><img src="image_10.png" /></figure>

In vitro digestibility indicators: i-PDCAAS:

<figure><img src="image_11.png" /></figure>

Infogest apparent digestibility

<figure><img src="image_12.png" /></figure>

Infogest protocol

<figure><img src="image_13.png" /></figure>

Megazyme®kit protocol

B

<figure><img src="image_14.png" /></figure>

995

**Figure 6** *In vitro* protein digestibility indicators at the end of intestinal phase and *in vitro* Protein Digestibility Amino Acid Score (i-PDCAAS) of wheat-based and cowpea-based pasta (A), and the relation between *In vitro* digestibility indicators and fiber content for wheat-based pasta (B)

996

997

998

Same letter within a same indicator and protocol are not significantly different (p <0.05); Mean ± standard deviation of three repetitions;

999

1000

1001