International Journal of Advanced Engineering Research and Science (IJAERS) [Vol-5, Issue-11, Nov- 2018] https://dx.doi.org/10.22161/ijaers.5.11.13 ISSN: 2349-6495(P) | 2456-1908(O) www.ijaers.com Page | 79 Influence of Altitude on the indirect Analysis of α-amylase Content on Wheat Flours Luiz Cláudio Garcia 1* , Felipe Augusto Rogrigues Vaurof 1 , Alisson Fogaça 1 , Pedro Henrique Weirich Neto 1 , Carlos Hugo Rocha 1 , Jaime Alberti Gomes 1 , Ivo Mottin Demiate 1 , Polyana Elvira Tobias Pinto Christmann 1 , Janaine Ritter 1 , Sérgio Roberto Piaskowski 2 , Evandra Fátima Webber 2 1 Department of Soil Science and Agricultural Engineering, State University of Ponta Grossa, Campus Uvaranas - Av. General Carlos Cavalcanti, 4748 – CEP 84030-900, Ponta Grossa (PR) Brazil. E-mail: lcgarcia@uepg.br, felipevaurof@gmail.com, alifogaca@hotmail.com, lama1@uepg.br, chrocha@uepg.br, jagmtp@gmail.com, demiate@yahoo.com, polyanaelvira@gmail.com, janaineritter@hotmail.com. 2 CONAB - Companhia Nacional de Abastecimento, Rod BR-376, km 510, Colônia Dona Luíza - CEP: 84046-000, Ponta Grossa, PR, Brazil. srp@netpar.com.br; evandra.webber@conab.gov.br. Abstract — The objective of this study was to verify the influence of altitude on the indirect analysis of α-amylase content on wheat flours. The experimental designused was completely randomized, with eight treatments and three repetitions. The treatments consisted of the analysis of the falling number from flours of four wheat classes (basic, domestic, bread and improver) on the elevations zero, 412, 540, 761, 934, 975, 1,040 and 1,095 meters. After the trial results, under the correction of the averages above 600 meters of elevation, it was verified that there was a significant difference between the results of distinct altitudes, for the four wheat classes. When a polynomial regression is applied, for the values without correction, it was obtained that aquadratic regression equation correlates the falling number values with altitude; however, the coefficient of determination was very low, highlighting the major influence of the different equipments that were used to measure the falling number instead of the different altitudes. Keywords— falling number, food analysis, food composition, flours, wheat classes. I. INTRODUCTION Wheat (Triticum aestivum) is a major cereal cropworldwide. Wheat flour is the basic ingredient to produce many foods, including breads, pasta, biscuits/cookies, cakes, among others. Even though,with the estimated production of 4.6 millionmetric tons of wheat(2018harvest season), Brazil is unable to supply its demand, standing as a huge importer country (CONAB, 2018). Wheat flour is qualified by its physical, chemical, rheological, and nutritional characteristics, considering its large use inbakeries. The exigence on technological attributes has been increasingly consideredby the consumer markets when buying wheat and wheat flour. Therefore, reaching the required quality is a key-factor for the success of planting, commercializing and processing wheat (Pinnow et al., 2013; Finck et al., 2015). In Brazil, the classification of wheat is ruled by the Normative Instruction n.º 38, from November 30,2010. The wheat group II(destined to milling, and other ends) is divided into five classes according to the values obtained of gluten strength, stability and falling number. To be classified in the “Improver”, “Bread”, “Domestic”, “Basic, and Others Uses classes the falling number must present the minimum values of 250, 220, 220 and 200 s, respectively. For the “Other Uses” class, the falling number minimum value is not established (BRASIL, 2010). Falling number is based on the α-amylase capacity to hydrolyze the starch gel. The intensity of the activity of the α-amylase enzyme in the wheat grain and in the wheat flour is estimated indirectly using the equipment called Falling Number ® , which measures the starchypaste (like a porridge) liquefaction of the grinded wheat grain suspension warmed in a boiling water bath, with the result being expressed in seconds (AACC, 2010; Mohler et al., 2014; Ral et al., 2015). Starting from the assumption that at low atmospheric pressures the boiling temperature in the water bath will decrease, Lorenz and Wolt (1981) proved that the falling number determination method suffers from influence of altitude. Thus, the falling number values increase with the elevation of altitude; because of a lower temperature, the sample in the test tube will be cooler and the activity of the α-amylase enzyme will be lower, therefore, increasing the falling number.