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Brazilian Archives of Biology and Technology

Print version ISSN 1516-8913

Braz. arch. biol. technol. vol.52 no.spe Curitiba Nov. 2009

https://doi.org/10.1590/S1516-89132009000700003 

AGRICULTURE, AGRIBUSINESS AND BIOTECHNOLOGY

 

Characterization of corn landraces planted grown in the campos gerais region (Paraná, Brazil) for industrial utilization

 

 

Alessandra Teixeira Barbosa PintoI; Joyce PereiraII; Tatiana Roselena de OliveiraI; Rosilene Aparecida PrestesI; Rodrigo Rodrigues MattieloIII; Ivo Mottin DemiateI,*

IUniversidade Estadual de Ponta Grossa; Avenida Carlos Cavalcanti, 4748; 84030-900; Ponta Grossa – PR – Brasil
IICurso de Engenharia de Alimentos, 3 Pós-Graduação em Agronomia

 

 


ABSTRACT

This work has the objective of characterizing twenty corn landraces grown in the Campos Gerais region (Paraná State) in relation to its chemical composition (moisture, ash, protein, ether extract, dietary fiber and starch) and physical properties (weight of 1000 grains, real density, flotation index, granulometry and color).  In addition, also the lab scale processing of the kernels from the varieties was carried out for producing starch; starch purity was evaluated by measuring its protein contamination. Amylose contents and viscoamylograph profile were also evaluated. The results showed that the evaluated landraces have differences in chemical composition as well as in pericarp/endosperm/germ proportions and consequently it should have different industrial applications and interest for plant breeding.

Key words: maize landraces, chemical composition, starch, physical properties, rapid viscoanalyzer


RESUMO

Esse trabalho teve o objetivo de caracterizar vinte variedades de milho crioulo cultivadas na região dos Campos Gerais (Estado do Paraná) em relação a sua composição química (umidade, cinzas, proteína, extrato etéreo, fibra alimentar e amido) e propriedades físicas (peso de 1000 grãos, densidade real, índice de flotação, granulometria e cor) Além disso, foi feito o processamento dos grãos em escala de laboratório para a extração do amido, sendo mensurado o teor de proteína. Foram avaliados os conteúdos de amilose e o perfil viscoamilográfico. Os resultados mostraram que os milhos apresentaram diferentes composições químicas e proporções pericarpo/endosperma/ gérmen e consequentemente podem ter diferentes aplicações industriais e interesse ao melhoramento de plantas.


 

 

INTRODUCTION

Corn (Zea mays, L.) is one of the main cultivated cereals all around the world. Its economic importance is due to many different ways of utilization from animal feeding to high technology industry (Cruz et al., 2006). Although corn kernels have not an expressive importance in direct human diet, several corn products are relevant for people of low income regions.

The main parts of corn kernel are the endosperm, pericarp and the germen. Each fraction presents distinct chemical composition and the quality is dependent from the genetic material as well as from the environment conditions.

The quality of corn for food and feed is different and genetic seems to be the best way of achieving the desired characteristics. The fast evolution of biotechnology made it possible to produce many kinds of hybrids with improved yield and other interesting characteristics (Trindade, 2006). The new biotechnology approach has many advantages in comparison to traditional technologies being able to introduce characteristics that reduce risks in agriculture. As many plant breeding programs are in development, each year several new genetic materials are marketed including dozens of corn hybrids. In Brazil there are many kinds of climatic, soil and environmental conditions due to its continental extension and important differences occur among the different geographical regions, including technical, economical, cultural and social aspects (Schmildt; Krause & Cruz, 2006). In this way, it is essential that plant breeders be very aware to select the correct materials for the distinct national conditions.

In this corn breeding process the landraces are of great interest (Miranda et al., 2007) for identifying the needs of the farmers and exploiting their genetic variability.  The landraces have potential in contributing with desired characteristics of cultivated plants including resistance to diseases and agricultural pests, improving crops and food safety (Fowler & Hodgkin, 2004, Birol; Villalba & Smale, 2007).

Several evidences show the importance of rescuing landraces for knowing their variability in terms of chemical composition of their edible parts and other economical interesting characteristics for industrial utilization as well as for breeding programs.

 

MATERIALS AND METHODS

Material

Representative samples of 20 corn landraces (Table 1) were grown in randomized blocks with four repetitions. The experiment was conducted at the School Farm of Universidade Estadual de Ponta Grossa, in Ponta Grossa, Paraná. The sowing was made in November/2006 and the harvest in March/2007. The sowing fertilization was made with 300 kg ha-1 of the 5-25-25 (NPK) formulation. A complimentary fertilization was made 45 days after germination with urea (100 kg ha-1 of nitrogen). The corn kernels were milled in a rotor mill (Tecnal model TE-633, Piracicaba, SP, Brazil) adjusted for fine milling and the granulometry of the milled product was evaluated with a Bertel (Caieiras, SP, Brazil) system of vibrating sieves.

Chemical composition

The chemical characterization of corn kernels included the following analyses: moisture content (AOAC, 2000, 925.10), protein (AOAC, 2000, 920.87), ash (AOAC, 2000, 923.03), lipids (IAL, 1985), starch (Demiate et al., 2001) and dietary fiber (AOAC, 2000, 985.29).

Physical properties

The weight of 1000 kernels of each sample was made as described by Mauricio et al., 2004).

The real density was evaluated as described by Mizuma, Kiyokawa & Wakai (2008), by using a pycnometer of known mass that was completely filled with xylene and weighed. A pre established corn kernel weight was put into the pycnometer and xylene was used for completely filling the empty spaces among the kernels. The total weight was registered and used for calculations.

The flotation index was evaluated (Lojano-Alejo et al., 2007) by using a sodium nitrate solution (41 g in 100 mL of water) with a known density of 1.25 g dm-3 at 23 °C. The kernels were put in this solution that was stirred. After resting for one minute, the floating kernels were counted.  The hardness classification was based on a scale proposed by Salinas; Bustos & Gómez (1992), with floating index (FI) between 0 and 12 % for very hard, 13 to 37% for hard, 38 to 62% for intermediary hard, 63 to 87 % for soft and higher than 87 % for very soft kernels.

Starch extraction

The starch extraction was made following the method of Ji, Seetharaman & White (2004), with some adaptations. For extracting starch, 100 kernels were used, being 25 of each block. There was removal of impurities and damaged kernels. Steeping started when the kernels were put into 40 mL of a 1 % sodium metabisulphite solution at 45°C for 72 h, followed by manual pericarp and germen removal. The endosperm fraction was put into 30 mL of distilled water and finely ground. This suspension was centrifuged for 10 min at 3,200 rpm for accelerating starch separation. The pellet was recovered and mixed with excess of a 0.1 % NaOH solution, in graduated cylinders for making precipitation fast. These cylinders were cooled to around 4 ºC for 24 h. The sediment was passed through a 325 mesh sieve, washing with distilled water. For neutralizing the sediment starch, addition of a 0.1 % HCl solution was made followed by distilled water washings until pH reached 6.0 - 7.0. The purified starch was then recovered by using a vacuum filtration system. The starch was dried for 24 h in a circulating oven at 45 °C until constant weight.

Starch characterization

All starch samples extracted from the corn kernels were stored in a dessicator for moisture stabilization. The analyses were made with two repetitions.

Properties of the starch pastes

The starch pastes of the 20 different starch samples were made by employing a Rapid Viscoanalyzer (RVA 4, Newport Scientific, Warriewood, Australia) using the STD1 profile of the software Thermocline. The data shown in the results are average of two repetitions. Starch slurries at 8.0 % (14.0 % moisture basis) were analyzed, considering a final slurry weight of 28 g.

Statistical analysis

The results were analyzed by the ANOVA followed by the Tukey test at 95 % confidence level. These analyses were made using the ASSISTAT version 7.1 beta software (Silva, 2004). A correlation matrix was also built up in order to better discuss the results, employing the Statistica version 5.0 software, considering 95 % confidence level. The principal component analysis (PCA) was employed in order to extract information from the results, using the Pirouette version 4.11 software (Infometrix). The auto scaling processing of the data was used for producing better results.

 

RESULTS AND DISCUSSION

The raw results are presented in the Table 2. The results showed that for moisture and ash contents, there were no significant differences at 95 % of confidence. The average values of moisture ranged from 10.29 % (Milho Grande nº52) to 11.45 % (Milho Encantilado nº 59). Other published papers (Luchin; Barcaccia and Parrini, 2003; Gonçalves et al., 2003) revealed results of ash of 1.56 % and 1.27 % in corn landraces and hybrids, respectively. The ANOVA showed significant difference for the protein levels among the varieties. The variety Crioulo Oito Carreiras nº 41 had the higher protein level (12.41%), whereas the variety Caiano Rajado nº16 had the lower (10.26 %). In the literature some authors reported that the protein contents for corn landraces were between 10.47 to 12.17 % (Câmara, 2005), and in hybrids from 7.77 to 13.84 % (Jiang et al., 2007). The average value found for dietary fiber was of 13.0 % and for starch this value was of 60.54 %. Other reports stated that starch contents in corn landraces were from 67.2 % (Câmara, 2005) to more than 70.0 % (Seetharaman et al., 2001).

Starch extraction

Table 3 shows the proportions of the morphological parts of corn kernel. The pericarp fraction varied from 3.73 to 7.38 %, whereas the germ fraction was between 7.05 to 12.92 %. In other reports where commercial corn hybrids were evaluated the germ percentages were of 5.75 % (Dowd, 2003), 6.20 % (Fox et al., 1992) and 6.97 % (Lopes-Filho, 1997). The Milho Paiol nº49 had the higher endosperm percentage (86.97 %) and high starch extraction yield (39.87 %). On the other hand, the Asteca nº60 had the lower value (81.50 %) and one of the lowest starch extraction yield (20.22 %).

Starch characterization

In the Table 4 are shown the results of the analyses of extracted starch. The average protein content for the extracted starches was of 1.0 %, with a minimum of 0.52 % (Milho Palha Roxa nº 72) and a maximum of 1.42 % (Milho Amarelo Antigo nº 71). Ji; Seetharaman, White (2004) found protein values for corn starches extracted in laboratory in the range of 2.82 to 3.65 % and it should explain the higher extraction yields related in their report. The apparent amylose contents of corn landrace starches did not differ at 95 % confidence level and the average value was of 17.66 %, in a range from 13.14 % (Milho Paiol nº49) to 21.51 % (Milho Astequinha Sabugo Fino nº70). In the case of total amylose, there was statistical difference among the starches. The average amylose content was of 25.59 %, in a range of 19.10 % (Roxo Índio I nº 60) to 33.86 % (Milho Palha Roxa nº 72).

The viscoamylographic pattern is presented in Table 4 with the main points of the analysis (viscosity peak, hot paste viscosity, final viscosity, breakdown, setback and gelatinization temperature). The profile is typical for most of the starch samples, the final viscosity is high due to retrogradation and the paste is relatively stable to stirred cooking, when comparing with cassava starch (Schoch & Maywald, 1968; Cereda et al., 2001), for example.

For some samples there were lower values of final viscosities when compared to viscosity peaks. The samples that had this viscoamylographic pattern were Milho Palha Roxa nº 72, Caiano nº 63, Milho Amarelo Antigo nº 71 and Crioulo Pururuca nº 38.

For the Amarelo Antigo nº 71 and Crioulo Pururuca nº 38 varieties, this pattern should be associated with the low levels of total amylose  (23.85 and 21.91 %, respectively) that reduce final viscosity (Salgo & Juhász, 2008; Blazek, 2008). The Milho Palha Roxa nº 72 and Caiano nº 63 varieties had high lipid complexed amylose levels (13.18 and 10.14 %, respectively), what have direct influence on viscosity. As written by Nelles et al., (2000), a small amount of lipids or phospholipids in starch affects the paste properties. Starch has free fatty acids and phospholipids in amounts directly related with amylose, distributed asymmetrically in the granules.

Correlation analysis

In the Table 5 the correlations among results are shown. The protein content had a negative correlation with starch content (r= -0.66, at 95 % confidence level), in the same way as reported by Chander et al. (2008). Fox et al. (1992) also found this correlation for corn hybrids (r= -0.63; p<0.01).

The hardness, as estimated by the flotation index, did not have correlation with the protein content, although some authors found positive correlation (Narváez-González et al., 2006), attributed to strong association between starch granules and protein with absence of empty intergranular spaces in the endosperm (Gibbon; Wang & Larkins, 2003, Gibbon & Larkins, 2005). Pereira et al. (2008) reported that corn kernels with hard or dent endosperms have abundance of organized protein bodies what explain the compact of these endosperms.

A positive correlation was observed between lipid content and kernel real density (r = 0.67, at 95 % of confidence). Although not expected this could be explained by a study for wheat of Scott (1951) cited by Posner (1985). The author reported that wheat germen had a real density of 1.34 g cm-3, very close to that of the whole grain, of 1.36 g cm-3. In the germ, beyond lipids, there are important levels of protein and sugars, which explain the data reported by Posner (1985). Furthermore the studied corn landraces presented high percentage of germ from 7.0 to 12.0 %. As expected the germ percentage and lipid content were positively correlated (r= 0.51, 95 % of confidence).

An expected negative correlation was found between flotation index and real density (r= -0.74, at 95 % of confidence); this fact was already reported by Salinas; Bustos & Gómez (1992), that found r= -0.94, at 95 % of confidence.

The granulometric profile evaluated by the percentage of coarse, intermediary and fine particles produced by corn kernels milling, revealed a negative correlation between coarse and intermediary particles (r= -0.93, at 95 % of confidence). The hardness classification of the grains allows understanding of this correlation. The hard endosperm kernels had higher percentage of coarse particles (retained in the 850 µm and 600 µm sieves) (Milho Pérola nº 65) and the kernels classified as intermediary that had particles between 250 µm and 180 µm of diameter (Milho Grande nº 52). In this way, we expected to have a significant correlation between hardness and the particle size distribution, but this fact did not happen.

In the processing of corn grains for starch extraction, the correlations confirmed the expected results. There were negative correlations between germ and endosperm percentages and endosperm and pericarp percentages (r= -0.85 and r= -0.55, respectively, at 95 % of confidence).

Starch extraction yield had a positive correlation with endosperm percentage (r= 0.50, at 95 % of confidence) and negative with germ percentage (r= -0.49, at 95 % of confidence).

The apparent viscosity profile (viscoamylography) of the starches was influenced by some of the studied parameters. The flotation index correlated negatively with peak viscosity (r= -0.48, at 95 % of confidence) and also with the final viscosity (r= -0.51, at 95 % of confidence). Corn varieties with low flotation index, classified in this work as hard corn (Salinas, Bustos & Gómez, 1992), presented higher average values of final viscosity (1799 cP), breakdown (772 cP) and peak viscosity (1719 cP). Seetharaman et al. (2001) when comparing starch paste properties of starches from corn with different hardness concluded that only very soft (floury) endosperms produced pastes with distinct characteristics. The starches from floury endosperms had higher gelatinization temperatures and lower values of peak viscosity, final viscosity, breakdown and setback. Due to this report, it would be expected that hard endosperms presented higher values for peak and final viscosity, breakdown and setback. The real density results confirmed this expectation as there was a positive correlation with viscosity peak (r= 0.50), final viscosity (r= 0.56), breakdown (r= 0.48) and setback (r= 0.60), always at 95 % of confidence level. Almeida-Domingues; Suhendro & Rooney (1997) reported that hard endosperm particles need more time for hydration and starch gelatinization for resulting in viscous pastes.

In relation to complexed amylose, negative correlations were found with final viscosity (r= -0.45) and setback (r= -0.46). This is discussed in other papers (Ribeiro & Seravalli, 2004) that mention that lipids affect the setback as they form complexes with helicoidal amylose and make difficult water absorption in the granules. Jane et al. (1999) reported that the reduction in the viscosity peak is due to lipids and phospholipids complexation with amylose.

Wickramasinghe et al. (2009) studying starches from tuberous crops observed the influence of the granular swelling on peak viscosity and breakdown. These authors correlated positively breakdown with granular swelling and viscosity peak and stated that the bigger granules swollen more intensively. During stirred cooking, on the other hand, apparent viscosity dropped drastically. The corn starches from landraces of our study also presented a positive correlation between viscosity peak and breakdown (r= 0.90), similar to the correlation found by Hou et al. (2008) (r= 0.89; P<0.01).

Other points of the viscoamylograms were correlated as peak and final viscosities (r= 0.70, at 95 % of confidence). This was expected as these points are interdependent.

The viscosity peak and the setback were positively correlated (r= 0.56, at 95 % of confidence) due to amylose liberation during the starch granules swelling. Also the setback and the breakdown and the breakdown and the final viscosity were positively correlated (r= 0.55 and r= 0.49, respectively). Breakdown is an indicative of granular disruption related with amylose liberation. High concentrations of free amylose become available in the polymer solution and re-associate increasing the final viscosity (setback).

The gelatinization temperature and the breakdown presented a negative correlation (r= -0.49, at 95 % of confidence), what could be due to the energetic demand for complete swelling of the granules. As the gelatinization temperature rises the granular swelling becomes difficult and limited and then the breakdown is lower. It is important to clarify that in this work we used the STD1 RVA profile and analysis is very short, taking only 13 min to be completed.

Principal component analysis (PCA)

The PCA was used to explore the variability of samples considering the selected physicochemical and physical aspects of the grains and of their starches. For an initial analysis, all the variables were considered to check the degree of explained variance. By using ten factors the explained variance reached 92.29 %.  The two first PC were responsible for explaining 36.06 % (PC1 = 22.42 % and PC2 = 13.66 %) of total variance of the original data. For improving the variance explanation of the model, some variables were excluded: moisture, thousand kernels weight, color, total amylose, fine particles percentage and setback. With this next data the PCA with ten factors explained 96.22 % of the total variance. The two first PCs explained 41.52 % (PC1 = 25.58 % and PC2 = 16.84 %) of total variance of the original data. The samples were grouped in the same manner as in the first PCA, with all variables.

The positive PC1, in the right side (Fig 1), is associated with the percentage of germ, lipids, real density, protein, intermediary size particles, breakdown, peak and hot paste viscosities and gelatinization temperature. In the left side of the PC1 are the variables starch, ash, dietary fiber, percentage of endosperm and of pericarp, starch yield and flotation index. This PC should be considered a dimension of endosperm density and hardness as the samples presenting higher real densities and lower flotation indexes are located in the positive side of the component. On the other hand, the less dense kernels presenting higher flotation indexes are located in the negative side of the PC1.

 

 

The PC2 was characterized by the particle size distribution, staying in one side that of coarse and in the other of intermediary granulometry. The grains that after milling produced higher amounts of coarse particles are located in the negative side of PC2 and the samples with higher amounts of intermediary size particles are in the positive side. As a consequence, these two variables allow a separation among grains with different hardness, as the varieties with proportionally more coarse particles have their endosperms classified as hard.   In this way, the interaction of flotation index, real density, coarse and intermediary particles were responsible for the separation of the varieties in four groups (Fig 1) identified with numbers from 1 to 4, in decreasing order of endosperm hardness. The group 1 is classified as low-intermediary hardness, as the samples presented higher flotation indexes, lower densities and higher percentage of intermediary particles. The group 4, on the other hand, includes grains with higher densities, lower flotation indexes and higher percentage of coarse particles, being classified as hard.

Another grouping showed in Fig 1 includes the grains that presented higher percentage of germ and lipids in the positive side of PC1. This fact explains the correlation between real density and lipid content (r = 0.67 at 95 % of confidence).

Another PCA analysis was carried out considering only the main physicochemical results (protein, dietary fiber, lipids and starch contents) and the morphological fractions (endosperm, pericarp and germ percentages) of the corn landraces. In the Fig 2 the results clearly show that in the endosperm fraction is located the great part of starch, in the pericarp the fiber fraction and in the germ is rich in lipids and protein. This analysis allows the identification of two main groups in the corn landraces studied (Fig 3). The first group includes samples that have more endosperm and starch and are located at the negative side of the PC1 (varieties marked as 3 and 4). The second group (varieties marked as 2, 6, 12 and 18) is characterized by kernels with higher percentage of germ and consequently with more protein and lipids. The variety identified as 16 stayed between the two groups due to its intermediary chemical composition. The varieties with the higher levels of dietary fiber are those located in the center of the graph. The variety coded as 20 had higher percentage of pericarp and due to that is isolated in the upper part of the graph. The other samples, 8, 11 and 13 are in between the groups separated by dietary fiber, lipids, protein and germ presenting intermediary values for these parameters.

 

 

 

 

CONCLUSION

The corn landraces presented relatively high germ percentage and consequently high lipid contents. The physical properties of corn grains like flotation index, real density and particle size distribution are important parameters for classifying endosperm hardness that was correlated with physicochemical characteristics. Grains with hard endosperms tend to present higher real density, lower flotation index and higher percentage of coarse particles after milling. The opposite pattern was met for intermediary hard kernels.

 

AKNOWLEDGMENTS

The financial resources for the conduction of this study were supported by the project BioAgroPar financed by FINEP, SETI/PR, and Fundação Araucária/PR; and by CNPq/Brazil.The authors thank to the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) for scholarships.

 

 

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