Classifying Fruit By Internal Quality Biology Essay

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ABSTRACT

The fruit industry requires rapid, economical, and non destructive method for classifying fruit by internal quality. This research studied on the development of nondestructive method would enable to control the of quality fruits. Near Infra Red Spectroscopy (NIRS) was used to assess total soluble solid content (SSC), %Brix. Soluble solid content (SSC) can describe as sugar or glucose level content in papaya. The voltage measured was taken from 4 different position which is 20%,40%,60% and 80% from the length of the papaya and the sugar level content is obtain in % Brix. From the experiment, the value was expected to obtain for the level sweetness of papaya is in the range below 5.45V which contain 7% of sugar and value above 5.45V which contain 5% of sugar. High correlation was expected to obtain between the soluble solid content (SSC) and NIR Spectroscopy using the average value for all the papaya.

INTRODUCTION

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During the last few decades extensive research has been carried out on the development of non-destructive sensors .None of the proposed particular approaches seems to provide all the information necessary to characterize fruit maturation and quality. Consequently different measuring principles addressing fruit flesh firmness, fruit sweetness, but also volatile compounds and pigment contents of fruit are recently used in parallel to improve the available information concerning the fruit maturity and quality (Di Natale et al., 2002). A trained person can sense these parameters, but currently requires a destructive measurement method. Consumer demand for high-quality products raises the need for a reliable, rapid, nondestructive, non-invasive technique for maturity determination. Non-destructive methods for measuring those fruit parameters would be beneficial to ascertain the quality of an increased number of fruits individually as well as to monitor the fruit maturity and quality on individual fruit. Fruit flesh firmness relates to texture properties, which can be judged either by humans or more objectively by mechanical tests. Destructive mechanical tests of texture include puncture, compression and shear tests, whereas nondestructive tests are related to impact, sonic and ultrasonic methods.

Near-infrared spectroscopy has gained wide acceptance in quality assessment of agricultural products and its applications include quantitative determinations of plum[5, 9] ,tomatoes[10], apples [8, 13], mango [11], watermelon [2], peach[6], and Satsuma Mandrin [3].Different techniques of measurement is been introduced for obtaining the NIR spectra. There are proof that the transmittance method was used successfully to determine the Soluble solid Content (SSC) of apples [1],watermelons[2] and Satsuma mandarin [3]. In transmittance method the light source is positioned opposite to the detector [4]. On the other hand, transmission measurements need very high light intensities which can easily burn the fruit surface and alter its spectral properties. Also, the transmitted light carries information about the skin and the core of the fruit which might or might not be relevant, depending on the application[4].

OBJECTIVE

To implement the non-invasive method for papaya sweetness determination using NIR Full-Transmittance Technique

To classify and modelling the level of sweetness in papaya based on infrared characteristic via full transmittance method.

PROBLEM STATEMENT

Currently, quality detection of the fruits is based on experience by looking at the skin colour therefore it is subjective with the possibility of deficiencies and errors. Many of current techniques are based on spectral analysis while measurement of voltage as shall be carried out in this research could ease the analysis and measurement process of classifying the sweetness of papaya.

This project only consider papaya because even though the colour of the papaya indicates that it is ripe, it does not guarantee its sweetness and a qualitative method that can determine the sweetness of the papaya has yet to exist.

LITERATURE REVIEW

A trained person can sense maturity parameters such as the fruit flesh color, fruit shape, fruit size, skin color, but currently requires a destructive measurement method. As for the internal quality like the sweetness, firmness or the content of the organic acids of the fruits are normally perceived by the senses of taste, smell and touch. Consumer demand for high-quality products raises the need for a reliable, rapid, nondestructive, non-invasive technique for maturity determination. During the last few decades extensive research has been carried out on the development of non-destructive sensors[1-7].[2] Reported that measurement of the optical properties of fruits and vegetables has been one of the most successful nondestructive techniques for assessing its quality property, such as sugar content, titratable acidity and vitamin content. .

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Perception of fruit quality depends on the sweetness and this can be correctly represented by soluble solid content. Soluble solid content (SSC) is used as the main indicator of fruit quality in several fruits including watermelon [2], apples[1, 8], plums [5, 9],tomatoes[10],mangoes [7, 11] and Satsuma Mandarin [3].Soluble Solid Content (SSC) and titratable acidity (TA), are two of the most important internal quality parameters for tomato flavor[10] and apples flavor[8].The Sugar content and tissue firmness are the most relevant to consumer perceptions of maturity, and are the factors most closely related to the stage of maturity in plum fruits[9, 12]. Mitchell report that SSC increases with ripening. Nevertheless, Crisosto suggests that SSC can be considered a good quality index[5]. Kader et al. (1978) report that high-quality fruits, i.e. fruits with the best flavor, are those with an SSC of over 3% and a TA value of 0.32%[10].[1] Reported that fruit SSC can non-destructively be determined with spectral-optical methods. Optical properties of fruit are based on reflectance, transmittance, absorbance, fluorescence or scatter of light by the product. The light recorded by means of light-protected glass fiber using a partial transmission mode is altered by extinction at various wavelengths due to absorption of responding molecules (Birth, 1978; Kawano, 1994; Olsen, Schomer, & Bartram, 1969). Within the visible wavelength range the major absorbers in intact apples are the pigments: chlorophylls, carotenoids, and anthocyanins (Knee, 1972; Merzlyak, Gitelson, Chivkunova, & Rakitin, 1999; Zude-Sasse, Herold, & Geyer, 2000).

Horticulturists tend to define firmness as the maximum force attained in the popular destructive Magness-Taylor (MT) penetrometer test. For six decades now, different non-destructive techniques have been developed for fruit excitation and signal analysis (Abbott, 1999; Chen, 1993; De Baerdemaeker, 1988; Finney, 1970)[1]. Fruit firmness is an important measurement of maturity and ripeness in many fruits. Firmness measurement has been based primarily on a destructive test like Magness-Taylor penetrometry for more than eighty years (Magness and Taylor, 1925). Several methods of nondestructive firmness measurement have been developed, and commercial on-line systems for automated firmness sorting are available (e.g., Aweta, 2008; Greefa, 2008; Sinclair, 2008). Current on-line firmness measurements are based upon either the acceleration response (Chen et al., 1985) or the acoustic signal (Cooke, 1972) issued as a result of a low energy elastic impact. García-Ramos et al. (2005) published a review paper that describes the existing nondestructive techniques for measuring fruit firmness with bench top and on-line systems[7].

NIR spectroscopy was first used in agricultural applications by Norris (1964) to measure moisture in grain. Since then it has been used for rapid analysis of mainly moisture, protein and fat content of a wide variety of agricultural and food products (Davies and Grant, 1987; Gunasekaran and Irudayaraj, 2001). Early applications in horticulture focussed on dry matter content of onions (Birth et al., 1985), soluble solids content (SSC) of apples (Bellon-Maurel, 1992) and water content of mushrooms (Roy et al., 1993), but since then many other applications have followed[4]. Near-infrared spectroscopy has gained wide acceptance in quality assessment of agricultural products and its applications include quantitative determinations of plum[5, 9] ,tomatoes[10], apples [8, 13], mango [11], watermelon [2], peach[6], and Satsuma Mandrin [3].NIRS instruments have undergone radical changes; they are much more versatile in terms of the infrared region in which measurements can be made, more portable, and better adapted to hostile working areas .However, before this technology can be successfully transferred to the fruit industry and, especially, implemented on a large scale, further research is required into the interaction of NIRS radiation from different regions of the near-infrared with intact fruits, with a view to optimizing instruments depending on the reflected or transmitted radiation is measured. While the radiation penetrates the product, its spectral characteristics change through wavelength dependent scattering and absorption processes[4, 5].When light comes in contact with a biological material, the photons of light can interact with the material at the molecular level. Light is characterized by its wavelength, with visible light having wavelengths in the 400 nanometer (nm) to 700 nm region and the near infrared (NIR) region having wavelengths between 700 nm and 2500nm. The wavelength of light is inversely related to its energy level with visible light having more energy than near infrared light. Molecules have discrete energy states and light can cause a molecule to change from one energy state to another if the energy in the photon matches the energy required to elevate the molecule from one energy state to another. Thus when light comes in contact with a molecule, it can either be absorbed (because the energy level of the light matches the energy level required to excite the molecule to a higher energy state) or reflected from or transmitted through the molecule. The wavelength of the light absorbed by the molecule indicates the type of molecule (e.g. water, sugar, starch, fat, pigment, etc.) due to the unique relationship between the energy of the light and the energy states of the molecule[7]. NIRS diode array instrument with a broad spectral range (400-1700 nm) could provide suitable calibrations for the prediction of SSC and firmness[5]. Near infrared (NIR) radiation covers the range of the electromagnetic spectrum between 780 and 2500 nm [4]. The spectrometer had a spectral range of 300_/1140 nm[13].[9] Reported that NIR in wavelengths between 700-1100 nm were used that promising and more useful for intact foods. In this Near-infrared spectroscopy (NIRS) technique, information about the internal quality of the product by measuring the absorption of near-infrared light by functional groups and scattering at specific wavelength is obtained (Banwell, 1983 )[8].Near-infrared reflectance spectroscopy (NIRS) technology shows considerable promise for the non-destructive analysis of food products, and is ideally suited to the requirements of the agro food industry in terms of both quality control: it requires little or no sample preparation; it is both flexible and versatile (applicable to multiproduct and multicomponent analysis); it generates no waste, is less expensive to run than conventional methods, and can be built into the processing line, enabling large-scale individual analysis and real-time decision making (Osborne et al., 1993; Shenk and Westerhaus, 1995a; Garrido, 2000) [10].In the NIR region the organic substances (like glucose, fructose and sucrose) absorb the electromagnetic radiation. The bonds of organic molecules change their vibrational energy when irradiated by NIR frequencies and exhibit absorption peaks through the spectrum[6].Lastly the advantage of NIR is that NIR creates a faster, safer working environment and does not require chemicals[5, 9].

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For measurements via NIRS, a tungsten halogen lamp is usually used as the light source[3, 9, 11, 13].The light source consisted of a 12V/100W tungsten halogen lamp[9]. 12V:75-W tungsten halogen lamp (Osram 5662)[11] and 250 W, 12 V DC tungsten halogen lamp[13] with infrared spectrum which infrared sensor can receive the signal. Photo diode array[9] use as the detector of the Infra Red pattern. [9] Reported that the calibration of the lamp, using a plate made of BaSO4, was done twice during reflectance measurements of each variety, to guarantee the stability of the lamp. The light passed through a bundle of optical fibers to the fruit, and the reflected light was transferred to a photo diode array (PDA) detector through another bundle of fiber optics. A holder was designed to support the plums and direct the light at a 45degree angle to the plums (to avoid specular reflectance), and maintain a distance of 1 cm between the probe and the plums. The integration time (time needed for a spectrum tobe acquired) was 181 ms (milliseconds). Each reflectance spectrum used in multivariate analysis was an average of the three spectra obtained for each plum. When Infra Red Radiation hits the sample, the incident light may be reflected, absorbed or transmitted and the relative contribution of each phenomenon depends on the chemical constitution and physical parameters of each sample. Present study use Infrared sensor as a detector to detect the infrared radiation pattern.

Different techniques of measurement is been introduced for obtaining the NIR spectra. In reflected mode[5, 9],the light source and detector are mounted under a specific angle. The scattering depend on the size, the shape and microstructure of the particle. There are restrictions in between the reflectance measurement techniques and one of that is the limitation in penetration depth of the reflectance method in detecting the internal defects and decrease the accuracy of NIR based measurement of internal quality attributes of thick-skinned fruit. There are proof that the transmittance method was used successfully to determine the Soluble solid Content (SSC) of apples [1],watermelons[2] and Satsuma mandarin [3]. In transmittance method the light source is positioned opposite to the detector [4]. On the other hand, transmission measurements need very high light intensities which can easily burn the fruit surface and alter its spectral properties. Also, the transmitted light carries information about the skin and the core of the fruit which might or might not be relevant, depending on the application[4]. Moreover, many of the instruments used work in the transmittance mode, which hinders their incorporation in processing lines and also requires greater light intensity, which might damage fruit by overheating. This is particularly true of thin-skinned fruits such as plums, for which the reflectance mode is more suitable, since light penetration is not markedly impeded by skin thickness, as would be the case in thick-rind fruits [5].[4] Reported that three different measurement setups for obtaining near infrared spectra are shown in Fig. 1. In reflectance mode (Fig. 1a), light source and detector are mounted under a specific angle, e.g., 45â-¦, to avoid specular reflection. In transmittance mode the light source is positioned opposite to the detector, while in interactance mode the light source and detector are positioned parallel to each other in such a way that light due to specular reflection cannot directly enter the detector. This can be achieved by means of a bifurcated cable in which fibers leading to the source and detector are parallel to each other and in contact with the product, or by means of a special optical arrangement

Fig. 1. Setup for the acquisition of (a) reflectance, (b) transmittance, and (c) interactance spectra, with (i) the light source, (ii) fruit, (iii) monochromator detector, (iv) light barrier, and (v) support. In interactance mode, light due to specular reflection is physically prevented from entering the monochromator by means of a light barrier.

METHODOLOGY

Malaysia papayas were used in this experiments that were purchased from fruit stall in greenwood. The papayas ripeness is selected randomly. Defective papayas were eliminated. The papayas were stored at room temperature 30 ⁰C for calibration before the experiment. A total of 30 papayas were used for this experiments. Form this experiments, samples were divided into two batches which is unripe and ripe papaya. Various size, weight and diameter of the papaya were collected as the sample's characteristics. Different sizes in papaya yield different result in voltage reading and sweetness. Four sensors were used for this experiment means that each sensor are at 20% positioned to each other from the length of papaya. The data were collected at points 20%, 40%, 60% and 80% from the length of papaya. The data collected is considering all the aspects including the surrounding, effect of light, weight of the papayas, size of the papayas, ripeness of the papayas and daylight. The process began with measuring the characteristics of the papaya including weight, length, diameter and ripeness. The information gathered from the papaya was collected. Make sure that the laboratory environment had around 60% relative humidity. Higher relative humidity means that the air is dominated by water which can cause water highly absorbs near infrared radiation. As a result the spectrum may further be complicated by wavelength dependent scattering effect, tissue heterogeneities, instrument noise, ambient effects and other sources of variability. A 150 watts of halogen lamp was used in the experiment for the purposed of avoiding a skin burn to the papaya which could effecting the papaya quality. A high watts of halogen lamp used very high light intensities which can easily burn the fruit surface and alter its spectral properties thus, affecting the sample quality. The transmitted light carries information about the skin and the core of the fruit which might or might not be relevant in the data collection. This halogen lamp is use because it transmits the light with infrared spectrum which infrared sensor can receive the signal. The penetrated light from the halogen lamps through the skin surface and papaya's content was measured by the infrared sensors which placed below the papaya. In transmittance mode the light source is positioned opposite to the detector. So, the papaya will be positioned between the 150W halogen light and the infrared sensors. The approximate distance from the halogen lamp to the papaya is about 10 cm while the distance from the infrared sensors to the papaya is about 0.05 cm. The distance obtained is fixed for the purposed of avoiding error in reading. For better results the infrared sensors is covered with solid material because it is a very sensitive sensor and it can detect light with infrared spectrum near to its range. For one papaya, the data taken is divided into four parts which is 20%, 40%, 60% and 80% from the length of the papaya. The papaya measurement setup was design adjustably so that it can reach the four parts where the data need to be collected. For each part, the data was taken three times to get the most comprehensive average value with each value collected is up three decimal points for each value. The same process continues for the next 49 papayas till the results show a pattern.

Refractrometer is a device to obtain the exact sugar lever or glucose level in term of degree of Brix (⁰Brix) in percentage. Refractrometer is equipment that used a same concept as implementing the infrared sensors and halogen light because its operation is based on the index of refraction. The index of refraction is calculated from Snell's law and can be calculated from the composition of the material using the Gladstone-Dale relation. This equipment is available at Level 5 Faculty of Chemical Engineering. There are two types of Refractrometer which is one of that is called handheld Refractrometer that can measure papayas in solid form and in liquid while another is the Abbe-Refractrometer that only measure in liquid form. Comparing this both types of refractrometer, Abbe-Refractrometer has high accuracy compared to others. Infrared radiation used an electromagnetic radiation whose wavelength is longer than the visible light (400-700nm), but shorter than that of terahertz radiation (100μm-1mm) and microwaves (30,000μm). Infrared radiation can be divided into 3 subdivisions which are near infrared radiation, mid-wavelength radiation, and long-wavelength radiation. Its wavelength is about 0.715 - 1.4μm. In this experiment, the process where measuring the Brix with refractrometer required the sample in liquid form. The juice from the papaya was extracted until it is in liquid form so that it will be available for the measurement process. When measuring the percentage Brix for the papaya, the refractrometer is required to zero first. By using a couple of drops of distilled water dropped into the refractrometer, the zeroing process began. Later, the papaya juice that has been extracted was dropped into the refractrometer. The result will eventually appeared in term of percentage Brix.

The collected data were then tabulated in graphical method form using Microsoft Excel 2007. The tabulated data will provide an understanding and pattern in the results. The data will show in relationship between the voltage readings with the percentage Brix. The data then were plotted in a form of graph. The voltage reading will be verified against the refrectrometer which will give direct indication of sweetness in terms of Brix. There is graph average voltage (V) versus percentage Brix (%) at 20%, 40%, 60% and 80% position. These graph plotted is to identify the difference in voltage reading between every of the sensors position. There are also graph average voltages for all the papaya versus the position of the sensors for ripe and unripe papaya. The purposed of these graphs is to identify the threshold voltage for the papaya based on its sweetness and to identify the pattern and relationship between the voltages measured with the sweetness level of the papaya. The graph also indicates the error of the readings. Finally, another experiment whereby adding plain water with sugars is carried out for the purposed of identifying the amount of sugar was supposed to be for the value of Brix collected. This type of experiment is the auxiliary experiment to the previous experiment for the purposed in proving the exact amount of sugar available in the papaya other than in Brix percentage. The result from this auxiliary experiment was performed in graphical view to achieve the most accuracy value from it. The amount of water content is approximately 10ml for any amount of tea spoon of sugar added. Thus, in the result obtained the value for any amount of sugar in Brix should include the percentage Brix for the amount of plain water.

PLAN SCHEDULE (GANTT CHART)

GANTT CHART

Year 1

2010

2011

Jul

Aug

Sept

Oct

Nov

Dec

Jan

Feb

Mar

Apr

May

1

Literature Review

2

Data Collection

3

Data analysis (Correlation between %Brix and Voltage)

4

Development of portable papaya sweetness classification device

5

Experimental verification and validation

6

Documentation and report

MILESTONES

Year 1

2010

2011

Jul

Aug

Sept

Oct

Nov

Dec

Jan

Feb

Mar

Apr

May

1

Completion of Data Collection

2

Completion of Data analysis

3

Completion of Development of portable papaya sweetness classification device

4

Completion of Experimental verification and validation

5

Documentation and report

CONCLUSION

From project proposal, I had learned so many skills. The literature review is the most important part to understand the overview of the project or the scope of the project, the method currently available the problem and the proposed approach to be implemented in the project. On the other hand, simple word can describe as to know what the main reason of this project is and know how to do it. This literature review can help to built methodology in the easy to understand and very comprehensive. The methodology may involve with simulation, design, hardware construction, analysis and proposed field test. Moreover in project proposal we learn how to plan the schedules for this semester and next semester using Gantt chart. Hopefully this information learned is helpful for some future applications to real life situation.