Changes in Phenolic Acid Content in Maize during Food Product

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Bioactive Constituents, Metabolites, and Functions

CHANGES IN PHENOLIC ACID CONTENT IN MAIZE DURING FOOD PRODUCT PROCESSING Carrie J. Butts-Wilmsmeyer, Rita H. Mumm, Kent Rausch, Gurshagan Kandhola, Nicole Yana, Mary Happ, Alexandra Ostezan, Matthew Wasmund, and Martin O. Bohn J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b05242 • Publication Date (Web): 16 Mar 2018 Downloaded from http://pubs.acs.org on March 19, 2018

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Journal of Agricultural and Food Chemistry

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CHANGES IN PHENOLIC ACID CONTENT IN MAIZE DURING FOOD PRODUCT

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PROCESSING

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Carrie J. Butts-Wilmsmeyer,1 Rita H. Mumm,1 Kent D. Rausch,2 Gurshagan Kandhola,2,3 Nicole

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A. Yana,1 Mary M. Happ,1,4 Alexandra Ostezan,1,5 Matthew Wasmund,1 and Martin O. Bohn1* 1

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1102 S. Goodwin Avenue, Urbana, IL 61801

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Department of Biological and Agricultural Engineering, the University of Arkansas, 4183 Bell Engineering Center, Fayetteville, AR 72701

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Department of Agronomy and Horticulture, the University of Nebraska-Lincoln, 202 Keim Hall, Lincoln, NE 68583

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Department of Agricultural and Biological Engineering, the University of Illinois at UrbanaChampaign, 1304 West Pennsylvania Avenue, Urbana, IL 61801

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Department of Crop Sciences, the University of Illinois at Urbana-Champaign,

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Institute of Plant Breeding, Genetics and Genomics, the University of Georgia, 111 Riverbend

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Road, Athens, GA, 30602

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*Corresponding author: [email protected]

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Keywords: Maize, Phenolics, Food Processing

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1 ACS Paragon Plus Environment


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ABSTRACT

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The notion that many nutrients and beneficial phytochemicals in maize are lost due to

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food product processing is common, but this has not been studied in detail for the phenolic acids.

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Information regarding changes in phenolic acid content throughout processing is highly valuable

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because some phenolic acids are chemopreventive agents of aging-related diseases. It is

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unknown when and why these changes in phenolic acid content might occur during processing,

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whether some maize genotypes might be more resistant to processing induced changes in

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phenolic acid content than other genotypes, or if processing affects the bioavailability of

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phenolic acids in maize-based food products. For this study, a laboratory-scale processing

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protocol was developed and used to process whole maize kernels into toasted cornflakes. High-

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throughput microscale wet-lab analyses were applied to determine the concentrations of soluble

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and insoluble-bound phenolic acids in samples of grain, three intermediate processing stages, and

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toasted cornflakes obtained from twelve ex-PVP maize inbreds and seven hybrids. In the grain,

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insoluble-bound ferulic acid was the most common phenolic acid, followed by insoluble-bound

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p-coumaric acid and soluble cinnamic acid, a precursor to the phenolic acids. Notably, the ferulic

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acid content was approximately 1,950 ߤg / g, more than ten times the concentration of many

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fruits and vegetables. Processing reduced the content of the phenolic acids regardless of the

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genotype. Most changes occurred during dry milling, due to the removal of the bran. The

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concentration of bioavailable soluble ferulic and p-coumaric acid increased negligibly due to

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thermal stresses. Therefore, the current dry milling based processing techniques used to

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manufacture many maize-based foods, including breakfast cereals, are not conducive for

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increasing the content of bioavailable phenolics in processed maize food products. This suggests


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that while maize is an excellent source of phenolics, alternative or complementary processing

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methods must be developed before this nutritional resource can be utilized.

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INTRODUCTION

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Diets rich in phenolic acids have been linked to the prevention of aging-related diseases

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such as cancer, neurodegenerative diseases, and cardiovascular disease.1-4 Although grains,

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especially maize, tend to possess high concentrations of phenolic acids, these are primarily found

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in the biologically unavailable, insoluble-bound form. Most of the phenolic acids in maize are

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insoluble-bound hydroxycinnamic acids. The hydroxycinnamic acids, when present in their

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soluble state, are especially known for their chemopreventive properties.3, 5 Since maize must be

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processed prior to human consumption, it is of key importance to understand the effects of

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processing on the nutritional value of maize. The effect of different processing techniques, such

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as nixtamalization,6-7 steaming/autoclaving,8-9 and extrusion cooking,7,

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content in maize has been well studied. Dewanto et al.8 showed that thermal processing releases

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insoluble-bound phenolics into their bioavailable, soluble state.

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commonly used method for the production of masa, tortillas, and tortilla chips, tends to remove

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phenolics from the final product.6-7 Extrusion cooking, which can be used as an alternative to

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nixtamalization for the production of some products, tends to retain more phenolics than

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nixtamalizataion due to the retention of pericarp and aleurone tissues during processing.7

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on the phenolics

Nixtamalization, the most

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However, little is known about how other processing techniques, such as dry milling,

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influence the phenolics content in maize. The primary product of dry milling are large flaking

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grits. The large flaking grits are then further processed into products such as ready-to-eat

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breakfast cereals (e.g. cornflakes) and snack foods.13 Most phenolics in maize are located in the

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bran14 and are removed with the bran during milling and the production of many processed

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maize-based foods.15 To what degree downstream processing activities (i.e., steaming, rolling,


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toasting) increase the soluble phenolics content or how the bioavailability of the phenolics

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content of maize-based food products is affected by processing is still unknown.

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Research conducted by Butts-Wilmsmeyer et al.16 showed that considerable variability in

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grain phenolic acid content exists among commercial maize inbreds and hybrids. However, little

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is known about how the fate of phenolic acids during processing may differ among genotypes

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that are representative of commercial germplasm. Since the processing stresses encountered

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during the production of toasted cornflakes are similar to those involved in the processing of

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other maize-based foods (Fig. 1a), a better understanding of the genetic characteristics, which

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determine the phenotypic response to processing stresses could lead to the nutritional

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improvement of maize-based processed food products. Thus, even though this study focuses

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specifically on the stresses encountered during dry milling and subsequent processing, many of

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the same processing stresses are encountered during different processing pathways. Processed

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foods could be improved directly by selecting hybrids, which maintain favorable phenolic acid

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concentrations throughout processing. However, if most of the phenolic acids are lost during

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food processing or are still not bioavailable in the final product, alternative methods for

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increasing the phenolic acid content of maize-based food products must be explored if more

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nutritious processed food products are to be created.

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The main goal of this study was to determine if 19 genetically and phenotypically diverse

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maize inbreds and hybrids differed in regards to the fate of their phenolic acids when processed

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into maize-based food products, specifically breakfast cereals and other dry-milled products. The

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specific objectives were to (1) develop a highly efficient processing pipeline that allows for

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beginning, intermediate, and final food products to be sampled, (2) determine the concentration

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of the phenolics in these products, (3) determine when changes in phenolics content is occuring



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during maize food product processing, and (4) determine if some maize genotypes produced

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more nutritious processed food products than others.

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processed maize food products is an ongoing research theme in our laboratories and builds

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directly on the research of Macke et al,17 Butts-Wilmsmeyer and Bohn,18 and Butts-Wilmsmeyer

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et al.16

Improving the nutritional value of


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MATERIALS AND METHODS

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Plant Materials

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All grain and flaking grit materials used in this study were acquired from the work of

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Macke et al.17 Available data, which included weather data,19 grain quality characteristics,17

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genotypic information,20 and phenolics content obtained from a preliminary wet-lab analysis,

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were used in a multi-stage sampling approach to identify the most genetically and phenotypically

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diverse subset of inbreds and hybrids. The overall goal of this multi-stage sampling approach

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was to reduce the number of samples analyzed without losing the genetic and phenotypic

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diversity of the materials used in Macke et al.17 Upon examination, it was noted that 2009 and

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2010 had similar mild weather conditions. This is in contrast to 2011, which was characterized

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by very hot and dry weather conditions during flowering, pollination, and seed set.19 Therefore,

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to capture the phenotypic variability due to non-genetic effects while minimizing the number of

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samples to be analyzed, we focused on only samples from 2009 and 2011 for this study. Three

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replications for each of 2009 and 2011 were used. All 12 inbreds used in Macke et al,17 were

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used in this study. Of the 66 hybrids used in Macke et al,17 13 hybrids were initially selected for

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preliminary analyses based upon their dry milling efficiency, as reported in Butts-Wilmsmeyer et

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al.16 Of these 13 hybrids, seven hybrids were selected based on their combined phenotypic and

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genetic diversities (for more information, see Macke et al,17 van Heerwaarden et al,20 and the

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“Statistical Analyses” section). A description of the preliminary wet-lab protocols and the

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protocols used for determining the grain quality characteristics are given in the supplementary

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information.

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The rationale for the selection of seven hybrids was as follows: the set of 13 hybrids used

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in Butts-Wilmsmeyer et al.16 could be grouped into three phenotypic clusters following the



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cluster analysis detailed in the “Statistical Analyses” section, as indicated by a large jump in the

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Root Mean Square Error (RMSE) score when comparing the RMSE values for two clusters

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versus three clusters. These clusters separated hybrids primarily based upon their soluble

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phenolics content and dry milling efficiency (Table S1). These clusters could be characterized as

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Cluster 1: moderate test weight, whole kernel soluble phenolics content, and flaking grit soluble

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phenolics content; Cluster 2: high test weight and low soluble phenolics content at both the

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whole kernel and flaking grit processing stages; and Cluster 3: low test weight and high soluble

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phenolics content at both the whole kernel and flaking grit processing stages. Key hybrids were

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selected from each of these phenotypic clusters so that the genotypic diversity of the inbred

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parents was also represented. Therefore, while replicates of only two years and seven hybrids

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and 12 inbreds were used in this study, these 19 entries collectively represented a considerable

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portion of the genetic and phenotypic variability (Table S2) in current commercial maize

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germplasm.21-22

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Processing

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Whole kernels and large flaking grit materials were available at the beginning of the

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study. The process used was described in Rausch et al.13 and was modified by Macke et al.17 to

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produce a large flaking grit material stream and a stream containing small endosperm particles,

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bran, and germ. The large flaking grit material was processed into cornflakes using a modified

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version of the protocol described by Kandhola.23 Details of this protocol can be found in the

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supplementary information under “Laboratory-Scale Processing Protocol.” Small samples were

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taken after the pressure cooking (cooked grits), baking (baked grits), and toasting (toasted


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cornflakes) portions of this processing work (Fig. 1b). All samples were dried at 65°C for at least

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eight hours and then ground to a fine powder using a coffee grinder.

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Extraction and Quantification of Soluble and Insoluble-Bound Phenolics

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The soluble phenolic acids were extracted and quantified using the procedure as outlined

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in Butts-Wilmsmeyer et al.16 Following the extraction of the soluble phenolic acids, the

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insoluble-bound phenolic acids were extracted and quantified using the protocol, with ߙ-amylase

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digestion, as outlined in Butts-Wilmsmeyer and Bohn18 and as modified by Butts-Wilmsmeyer et

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al.16

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Statistical Analysis

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Cluster Analysis for Multi-Stage Sampling Approach

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To determine the phenotypic dissimilarity between the 13 hybrids used in Butts-

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Wilmsmeyer et al,16 hierarchical clustering was conducted using Ward’s Minimum Variance

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Approach in SAS (version 9.3). Phenotypic traits used in hierarchical clustering were test weight,

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dry milling efficiency, whole kernel soluble phenolic content, flaking grit soluble phenolic

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content, moisture, oil, starch, and protein content. Test weight and dry milling efficiency

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measures for each of the entries were obtained from Macke et al.17 All of these traits are related

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to grain composition and may influence the concentration of other beneficial phytochemicals.

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SAS (version 9.3) PROC MEANS was used to calculate the mean of each phenotypic trait for

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each genotype. Plot phenotypic means were used in the calculations of the genotypic (entry)

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means. These means were used in the construction of a dendrogram in PROC CLUSTER. Since

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Ward’s Minimum Variance Approach was used, the distance between two clusters can be



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defined as “the ANOVA sum of squares between two clusters added up over all the variables.”24

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The arithmetic means of each trait for each cluster was calculated using PROC TREE and PROC

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MEANS. Genotypic data reported in van Heerwaarden, et al.20 and hierarchical clustering were

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used to create a dendrogram of the genetic distance of the twelve parental inbreds. A total of

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45,997 SNPs were used to calculate the genetic distance (Roger’s W Coefficient) between

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individuals in SIMGEND. A dendrogram was created using SAHN and the UPGA clustering

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method and was provided by Dr. Mark Mikel, University of Illinois. Representative hybrids were

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selected from each of the three phenotypic clusters generated with the condition that the parental

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inbreds of the hybrids selected collectively represented most of the genetic diversity in the total

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set of 12 parental inbreds.

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Identification of Processing Stages where Changes in Phenolics Content Occurred

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Phenolic acid means of each hybrid were plotted against the processing stage. An

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apparent lack of change in phenolic acid content, as indicated by a horizontal plateau in the plot,

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was further investigated using a split-plot in an RCBD where the whole plot unit was the field

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plot from which grain was harvested, and the subplot unit was processing stage. Model 1 was

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used to analyze both insoluble-bound ferulic acid and p-coumaric acid. Soluble phenolics were

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not of immediate concern due to their overall low concentrations and the small change in their

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concentrations after steaming (cooking). Two hundred samples (40 whole plots and 200

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subplots) were analyzed as part of this portion of the study, and all of these came from 2009. The

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following mixed linear model was applied:

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‫ݕ‬௜௝௞ = ߤ + ܴ௜ + ߙ௝ + ߝଵ௜௝ + ߬௞ + ߙ߬௝௞ + ߝଶ௜௝௞ [1]

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where ‫ݕ‬௜௝௞ is the observed concentration of the phenolic compound under observation, ߤ is the

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grand population mean, ܴ௜ is the random effect of the ݅ ௧௛ field replication, NID(0, ߪோଶ ), ߙ௝ is the

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ଶ fixed effect of the ݆ ௧௛ genotype, ߝଵ௜௝ is the random whole plot error term, NID(0, ߪ௘ଵ ), ߬௞ is the

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fixed effect of the ݇ ௧௛ processing stage, ߙ߬௝௞ is the fixed interaction between the ݆ ௧௛ genotype

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ଶ and the ݇ ௧௛ processing stage, and ߝଶ௜௝௞ is the random subplot error term, NID(0, ߪ௘ଶ ). At least

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two replications of each hybrid and each inbred were analyzed. Model 1 was used separately for

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hybrids and inbreds.

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Multi-degree of freedom contrasts and slice statements were used to test the difference in

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processing stages if genotype × processing stage interactions were significant. The ANOVA as

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described above was conducted in PROC MIXED of SAS (version 9.3). The assumptions of the

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ANOVA were verified as described below.

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Phytochemical Persistence Through Processing

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A split-plot in an RCBD was used to analyze the dynamics in phenolic acid content

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through processing, where the whole plot unit was the field plot from which grain was harvested,

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and the subplot unit was processing stage. The following mixed linear model was used

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‫ݕ‬௜௝௞௟ = ߤ + ܻ௜ + ܴሺ௜ሻ௝ + ߙ௞ + ܻߙ௜௞ + ߝଵ௜௝௞ + ߬௟ + ܻ߬௜௟ + ߙ߬௞௟ + ܻߙ߬௜௞௟ + ߝଶ௜௝௞௟ [2]

203 204

where ‫ݕ‬௜௝௞௟ is the observed concentration of the phenolic compound under observation, ߤ is the

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grand population mean, ܻ௜ is the random effect of the ݅ ௧௛ year, NID(0, ߪ௒ଶ ), ܴሺ௜ሻ௝ is the random

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effect of the ݆ ௧௛ rep nested within the ݅ ௧௛ year, NID(0, ߪோଶ ), ߙ௞ is the fixed effect of the ݇ ௧௛

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genotype, ܻߙ௜௞ is the random interaction between the ݅ ௧௛ year and the ݇ ௧௛ genotype, NID(0,

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ଶ ଶ ߪ௒ఈ ), ߝଵ௜௝௞ is the whole plot error term, NID(0, ߪ௘ଵ ), ߬௟ is the fixed effect of the ݈ ௧௛ processing



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stage, ܻ߬௜௟ is the random interaction between the ݅ ௧௛ year and the ݈ ௧௛ processing stage, NID(0,

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ଶ ߪ௒ఛ ሻ, ߙ߬௞௟ is the fixed interaction between the ݇ ௧௛ genotype and the ݈ ௧௛ processing stage, ܻߙ߬௜௞௟

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is the random three-factor interaction between the ݅ ௧௛ year, the ݇ ௧௛ genotype, and the ݈ ௧௛

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ଶ processing stage, and ߝଶ௜௝௞௟ is the subplot error term, NID(0, ߪ௘ଶ ). In both Models 1 and 2, the

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effect of genotype is considered fixed because the genotypes were selected specifically. Model 2

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was used for all traits measured as part of the evaluation of the changes in phytochemical content

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through processing. Inbreds and hybrids were analyzed separately.

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The ANOVA as described above was conducted in PROC MIXED using SAS (version

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9.3). Additionally, R was used to create an interaction plot (profile plot) of the interaction

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between hybrid genotype and processing stage using the interaction.plot command. Multi-degree

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of freedom contrasts and slice statements were used to test the difference in processing stages if a

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significant interaction between genotype and processing stage occurred.

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Verification of ANOVA Assumptions

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In each model described above, residuals were obtained from the MIXED procedure and

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then analyzed using the UNIVARIATE procedure to check the assumption of normality. The

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Brown-Forsythe modification of the Levene test was used to check the assumption of

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homogenous variances among the stage and genotype treatment combinations. If the assumptions

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of normality or homogenous variances were violated, then the appropriate data transformation or

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outlier removal was performed. The QQ-plots and histograms of the residuals were used in the

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evaluation of whether outlying observations should be removed. Observations whose residuals

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significantly deviated from the normal line in the QQ-plot and that appeared to be drastically

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skewing the distribution of the residuals in the histogram were deleted.


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RESULTS AND DISCUSSION

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Identification of Processing Stages Where Significant Changes in Phenolic Acid Content

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Occur

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To identify key processing stages that should be monitored for changes in phenolic acid

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content, we examined the phenolic acid content in whole kernels and toasted cornflakes as well

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as three intermediate processing stages using samples from 2009. We noted that only three

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processing stages were necessary to characterize the change in phenolic acid content throughout

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processing. Plots showed that the soluble ferulic acid, p-coumaric acid, and cinnamic acid

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content remained relatively stable between the cooked grit and the final toasted cornflake stage.

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There was a slight decrease in the concentration between baked grits and the final toasted

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cornflakes, but the overall change was negligible. Plots of insoluble-bound ferulic acid and p-

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coumaric acid content through the five different processing stages showed a drastic decrease

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between the whole kernel and flaking grit stage and then a small decrease after the flaking grit

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stage before stabilizing for the remainder of processing (Fig. 2 and S4). There was also a

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decrease in the concentration of soluble cinnamic acid following dry milling before nearly

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stabilizing between the cooked grit and toasted cornflake processing stages (Fig. S4c). These

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results indicated that whole kernels and flaking grit materials should be analyzed for their

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phenolic acid content. Since the plots of the phenolic acid content by processing stage indicated

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that there might not be a significant change between the cooked grit and the final toasted

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cornflake product, multi-degree of freedom contrasts were constructed to test whether the change

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between the cooked grit and the final toasted cornflake were significant for any of the hybrids.

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Multi-degree of freedom contrasts indicated that the change in insoluble-bound phenolic acid

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content between the cooked grit and final toasted cornflake was not significant, regardless of the



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genotype under study (Table S3). Therefore, only the whole kernel, large flaking grit, and toasted

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cornflake stages were used for subsequent phytochemical analyses.

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These results are in agreement with the available literature. Adom and Liu25 and Yadav et

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al.26 noted that most of the phenolic acids in maize are in their insoluble-bound form. Yadav et

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al.26 also found that the most predominant phenolic acids in maize were insoluble-bound ferulic

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acid and insoluble-bound p-coumaric acid. Considering that most of the phenolic acids are

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located in the bran and that the bran is removed during dry milling, it is not surprising that the

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overall concentration of the phenolic acids decreased after dry milling. Furthermore, while some

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of the insoluble-bound phenolic acids were released into the soluble state, most likely due to

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thermal stresses during cooking and baking, it does not appear that the concentration of the

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insoluble-bound phenolic acids fluctuated much following dry milling. These findings suggest

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that the structure of the phenolic acids, particularly when they are esterified to arabinoxylans,

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inhibits degradation of the phenolic acids when exposed to thermal stresses. However, during

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rolling and toasting, it appears that some of the soluble phenolic acids were degraded. The

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degradation of the soluble phenolic acids is possible because, unlike their insoluble-bound

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counterparts, the soluble phenolic acids are not bound to arabinoxylans and are not as protected

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from thermal stress. However, this change in the soluble phenolic content is small.

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Phenolic Acid Content Throughout Processing

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Having identified the most important processing stages at which changes in phenolic

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acids occur during the production of toasted cornflakes, the 19 entries were analyzed for their

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phenolic acid content in the whole kernels, in the flaking grit materials, and also in the final

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toasted cornflakes using samples from both 2009 and 2011. The phenolic acids were almost


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exclusively composed of hydroxycinnamic acids, as expected. Insoluble-bound ferulic acid was

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the most prevalent (average concentration of 1,948.4 ߤg / g in the hybrid whole kernels),

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followed by insoluble-bound p-coumaric acid (176.4 ߤg / g) and then soluble cinnamic acid

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(63.7 ߤg / g). These results are in agreement with the limited information available in the

282

literature.26-28 However, this study analyzed a much broader germplasm base than previous

283

studies, and our results are directly pertinent to maize grown in the U.S. Cornbelt. For instance,

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Serratos et al.28 analyzed only four maize entries (three local populations from Belize and one

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double-cross hybrid), and Yadav et al.26 and Adom and Liu25 did not analyze individual

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genotypes in their studies. Therefore, our research extends the findings in the literature to a

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significantly broader germplasm base that is directly tied to U.S. commercial maize germplasm.

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Furthermore, this indicates that maize whole kernels are considerably more concentrated than

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other plant sources in terms of their ferulic acid content. For instance, Mattila et al.29 reported

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that rhubarb, blueberries, and cherries have ferulic acid contents of 20.0, 12.9, and 4.6 ߤg / g,

291

respectively. Unlike these other plant sources, however, maize must be processed prior to

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human consumption, and the phenolics in maize are largely in the insoluble-bound form.

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The largest loss of phenolic acids, particularly insoluble-bound ferulic acid and insoluble-

294

bound p-coumaric acid, occurred during dry milling (Fig. 3). The large loss in phenolic acid

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content at this stage was expected, mainly because the majority of phenolic acids in maize

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kernels are located in the bran,14 and the bran and germ are removed during dry milling.30 While

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hybrid maize kernels had an average of 1,948.4 ߤg / g of insoluble-bound ferulic acid and 176.4

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ߤg / g of insoluble-bound p-coumaric acid at the whole kernel processing stage, the average

299

concentration of insoluble-bound ferulic acid and insoluble-bound p-coumaric acid dropped to

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980.0 ߤg / g and 74.5 ߤg / g at the flaking grit stage before stabilizing at approximately 900 ߤg /



301

g and 55 ߤg / g for the remainder of processing, respectively. In comparison, the average soluble

302

ferulic acid and p-coumaric acid content in the hybrids increased from only 1.5 ߤg / g and 1.8 ߤg

303

/ g to 7.3 ߤg / g and 7.0 ߤg / g during processing, respectively. Additionally, the soluble

304

cinnamic acid content decreased from 71.2 ߤg / g to 26.7 ߤg / g. A similar result was observed

305

among the inbreds (Table 1).

306

The variance in phenolic acid content among hybrids and inbreds decreased throughout

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processing. In regards to insoluble-bound ferulic acid, the phenotypic variance among hybrid

308

genotypes dropped from 82,811.6 ቀ ௚ ቁ to 54,447.6 ቀ ௚ ቁ between the whole kernel and final

309

toasted cornflake. Similarly, the phenotypic variance among hybrid genotypes for their p-

310

coumaric acid content dropped from 1,899.2 ቀ ௚ ቁ to 636.0 ቀ ௚ ቁ between the whole kernel and

311

final toasted cornflake. Similar trends were recorded for the inbreds used in this study (Table 1).

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These results, taken in conjunction with the results of Rumpagapom,14 indicate that not only are

313

most of the insoluble-bound hydroxycinnamic acids located in the bran, but most of the

314

variability in hydroxycinnamic acid content is also localized in the bran. Since plant

315

improvement through plant breeding occurs via the exploitation of phenotypic variability, the

316

loss of variability in both insoluble-bound ferulic and p-coumaric acid indicates that increasing

317

the phenolic acid content of processed maize food products may be difficult.

ఓ௚ ଶ

ఓ௚ ଶ

ఓ௚ ଶ

ఓ௚ ଶ

318

Furthermore, the rank of a particular hybrid at the whole kernel processing stage in

319

regards to its phenolic acid content was not indicative of the rank of that hybrid in later

320

processing stages (Fig. S5). Since the rank of the hybrids changed throughout processing, the

321

concentration of insoluble-bound hydroxycinnamic acids in the whole kernels can not be used to

322

predict the concentration at other processing stages. This conclusion is supported by the

323

significant interaction between genotype and processing stage (Tables S4 and S5). Therefore, to 16 ACS Paragon Plus Environment

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324

improve the concentration of hydroxycinnamic acids in toasted cornflakes and other maize-based

325

processed foods, the final processed product must be analyzed. In a plant breeding setting, this is

326

laborious, time-consuming, and requires large laboratory space for processing.

327

Regardless of the genotype, most of the phenolic acids present in the whole kernel were

328

not contained within the flaking grit materials or the final toasted cornflake product. Most

329

importantly, those phenolic acids that remained were primarily present in their least bioavailable

330

form as insoluble-bound hydroxycinnamic acids. Adam et al. (2002) found that the insoluble-

331

bound hydroxycinnamic acids tended not to be absorbed. Rather, these compounds serve as

332

cross-linkages between arabinoxylan fibers and exhibit negligible chemopreventive properties in

333

regards to the prevention of cancer or neurodegenerative diseases. These results, taken in

334

conjunction with the knowledge that the production and wet-lab analysis of multiple processing

335

stages during this project were very time-consuming, indicates that improving the concentration

336

of bioavailable hydroxycinnamic acids by selecting for hybrids which maintain positive

337

phytochemical attributes throughout processing is not feasible. Therefore, in order to improve the

338

phenolic acid content of processed maize food products, either current food product processing

339

methods could be changed, which may be impractical or impossible, or phenolic acids removed

340

during dry milling could be added back to the processed food product.

341

In summary, to the authors’ knowledge, this is the first holistic study that concurrently

342

considers the disciplines of commercial plant breeding, human nutrition, and bioprocessing. We

343

envision that the results of this study will prove useful to the practical and efficient development

344

of high quality crops that meet both nutritional and processing standards. Specifically, we

345

developed a highly efficient processing and analytical pipeline that allows for the

346

characterization of processing and nutritional parameters. While this pipeline may be of little use



347

in large plant breeding studies, it could prove useful in both human nutrition and bioprocessing

348

applications. Furthermore, we found that maize typical of the U.S. Cornbelt does contain high

349

concentrations of phenolics, but these are typically removed with coproducts during dry-milling.

350

The remaining phenolics in the toasted cornflakes after processing were still bound to the cell

351

wall hemicellulose.

352

products with a higher concentration of phenolic acids, especially soluble phenolic acids, may be

353

with an all-natural food additive: phenolic acids extracted from the coproducts of common

354

milling procedures.

Therefore, the most efficient method of biofortifying processed food

355


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ABBREVIATIONS USED

356 357

NSS – Non-Stiff Stalk

358

SSS – Stiff Stalk Synthetic

359

RMSE - Root Mean Square Error

360

ACKNOWLEDGEMENTS

361 362

The authors would like to thank Tom Patterson and the Analytical Technologies Team at Dow

363

AgroSciences for the use of their laboratory facilities and for their mentorship.

364

FUNDING SOURCES

365 366

This work was funded in part through gifts from the Kellogg Company and Dow AgroSciences

367

and through USDA Hatch Grant, award ILLU-802-354. Student support was provided by the

368

Illinois Distinguished Fellowship and the William B. and Nancy L. Ambrose Fellowship in Crop

369

Sciences.

370

CONFLICT OF INTEREST

371 372

The authors declare no competing financial interest.

373

SUPPORTING INFORMATION

374 375

•

Laboratory scale processing protocol.

376

•

Protocols for the preliminary analysis of nutritional traits for phenotypic cluster analysis.

377

•

Table of means of preliminary phenotypic traits by cluster.

378

•

Table of efficacy of multistage sampling technique in maintaining phenotypic variance.



379

•

hydroxycinnamic acid content in the cooked grits, baked grits, and toasted cornflakes.

380 381

Table of multi-degree of freedom contrasts testing the difference in insoluble-bound

•

Table of the significance of the genotype-by-processing stage interaction by compound and hybrid/inbred generation.

382 383

•

Table of the ANOVA summary.

384

•

Table of the contrasts to test the significance of the stage main effect for given levels of another factor in the case of a significant two-factor interaction between terms.

385 386 387

•

Additional figures which are not necessary for the understanding of research results but which provide information for additional understanding.


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9. Randhir, R.; Kwon, Y.-I.; Shetty, K., Effect of thermal processing on phenolics, antioxidant activity and health-relevant functionality of select grain sprouts and seedlings. Innovative Food Science & Emerging Technologies 2008, 9 (3), 355-364.



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11. Wang, T.; He, F.; Chen, G., Improving bioaccessibility and bioavailability of phenolic compounds in cereal grains through processing technologies: A concise review. Journal of Functional Foods 2014, 7, 101-111.

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12. Asami, D. K.; Hong, Y. J.; Barrett, D. M.; Mitchell, A. E., Comparison of the total phenolic and ascorbic acid content of freeze-dried and air-dried marionberry, strawberry, and corn grown using conventional, organic, and sustainable agricultural practices. Journal of Agricultural and Food Chemistry 2003, 51 (5), 1237-1241.

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13. Rausch, K. D.; Pruiett, L. E.; Wang, P.; Xu, L.; Belyea, R. L.; Tumbleson, M. E., Laboratory Measurement of Yield and Composition of Dry-Milled Corn Fractions Using a Shortened, Single-Stage Tempering Procedure. Cereal Chemistry 2009, 86 (4), 434-438.

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16. Butts-Wilmsmeyer, C. J.; Mumm, R. H.; Bohn, M. O., Concentration of Beneficial Phytochemicals in Harvested Grain of US Yellow Dent Maize (Zea mays L.) Germplasm. Journal of Agricultural and Food Chemistry 2017, 65 (38), 8311-8318.

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17. Macke, J. A.; Bohn, M. O.; Rausch, K. D.; Mumm, R. H., Genetic Factors Underlying Dry-Milling Efficiency and Flaking-Grit Yield Examined in US Maize Germplasm. Crop Science 2016, 56 (5), 2516-2526.

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22. Mikel, M. A., Availability and analysis of proprietary dent corn inbred lines with expired US plant variety protection. Crop Science 2006, 46 (6), 2555-2560.

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27. Arnason, J. T.; Gale, J.; Debeyssac, B. C.; Sen, A.; Miller, S. S.; Philogene, B. J. R.; Lambert, J. D. H.; Fulcher, R. G.; Serratos, A.; Mihm, J., Role of Phenolics in Resistance of Maize Grain to the Stored Grain Insects, Prostephanus truncatus (Horn) and Sitophilus zeamais (Motsch). Journal of Stored Products Research 1992, 28 (2), 119-126.

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FIGURE CAPTIONS Figure 1. Processed maize food product production. (a) Processing steps involved in the production of many maize-based food products. The three major categories of maize food product processing are alkaline hydrolysis, wet milling, and dry milling. The toasted cornflakes production pipeline is shown in red. The various stresses that are encountered during the production of various maize-based food products are also shown. (b) Cornflake production pipeline, including pre-processing steps such as plant breeding and grain production. Marketable grain products are indicated by large yellow circles. All processes involved in the production of toasted cornflakes, including pre-processing steps, are indicated by blue rectangles. Figure 2. Change in ferulic acid content by processing stage – all five processing stages. Means from the same hybrid are represented by the same color in each processing stage. Hybrids are color-coded as follows: Red = B73×Mo17, Green = B73×PHG47, Blue = LH1×Mo17, Black = PHJ40×LH123HT, Gray = PHJ40×Mo17, Purple = PH207×PHG47, and Tan = PHG39×PHZ51. Processing stages are abbreviated as follows: WK = Whole Kernel, FG =Flaking Grit, CG = Cooked Grit, BG = Baked Grit, and TO = Toasted Cornflake. (a) The insoluble-bound ferulic acid content drastically decreased between the whole kernel processing stage and the large flaking grit and then again by the end of processing. However, the insolublebound ferulic acid content remained relatively stable between the cooked grit and toasted flake processing stages. (b) While the soluble ferulic acid content increased during processing, the magnitude of that increase is very small, especially in comparison to the amount of insolublebound ferulic acid lost during processing. Figure 3. Change in insoluble-bound phenolic acid content throughout processing using two years and seven hybrids to analyze key processing stages. Means from the same hybrid are shown in the same color in each of the processing stages. Hybrids are color-coded as follows: Green = LH1×Mo17, Blue = B73×Mo17, Brown = PHG39×PHZ51, Black = PHJ40×LH123HT, Red = B73×PHG47, Orange = PHJ40×Mo17, and Purple = PH207×PHG47. Processing stages are abbreviated as follows: WK = Whole Kernel, FG = Flaking Grit, TO = Toasted Cornflake. (a) Change in insoluble bound ferulic acid content throughout processing. (b) Change in insoluble-bound p-coumaric acid content throughout processing.



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TABLES Table 1. Mean and standard deviations (SD) of phenolic acids and cinnamic acid at different processing stages

Soluble Processing Stage

Generation

Cinnamic Acid

Ferulic Acid

Insoluble-Bound p-Coumaric Acid

————————— µg/g ————————

Ferulic Acid

p-Coumaric Acid

————— µg/g —————

Whole Kernels HYBRIDS Mean SD

63.67 43.34

1.50 0.51

1.81 0.44

1,948.41 287.77

176.40 43.58

INBREDS Mean SD

90.87 68.15

1.78 0.55

2.42 0.81

2,004.42 374.13

223.08 81.62

Large Flaking Grits HYBRIDS Mean SD

34.77 28.42

2.17 0.46

2.13 0.66

980.03 273.79

74.54 34.99

INBREDS Mean SD

31.86 41.38

2.35 0.57

2.21 0.75

787.05 234.30

63.81 38.49

HYBRIDS Mean SD

26.70 21.73

7.28 1.98

7.03 2.52

902.83 233.34

56.48 25.22

INBREDS Mean SD

27.32 30.31

7.13 2.32

8.10 3.03

786.92 273.04

50.50 32.81

Toasted Cornflakes


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FIGURE GRAPHICS

a

b



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a

b


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a

b



GRAPHIC FOR TABLE OF CONTENTS


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Changes in Phenolic Acid Content in Maize during Food Product

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