بررسی انرژی گسیختگی ارقام مختلف سیب زمینی در مرحله برداشت با دستگاه سنتام

Introduction
Potato is an important vegetable that grows all over the world and is considered as an
important product in developing and developed countries for human diet as a source of
carbohydrates, proteins, and vitamins. This product is native to South America and its origin
is from Peru, and after wheat, rice and corn, it is the fourth product in the food basket of
human societies. According to the statistics of the Food and Agriculture Organization of the
United Nations, the area under cultivation of this crop in Iran in 2017 was 161 thousand
hectares and the crop harvested from this area is about 5.1 million tons. Traditional methods
of determining potato varieties were based more on morphological features, but with the
production of new products, there was a need for methods that were faster and more
recognizable. Meanwhile, the high-performance artificial neural network can be used to
classify cultivars. An artificial neural network can classify and detect cultivars, is flexible and
is used in most agricultural products. Azizi conducted a study on 120 potatoes in 10 different
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cultivars using a visual and image processing machine with a MATLAB R2012 software
toolbox to detect texture, shape parameters and potato cultivars. First, potato cultivars were
classified usithe ng LDA method, which obtained 66.7% accuracy. This method also erred in
distinguishing the two cultivars Agria and Savalan and also classified the two cultivars
Fontane and Satina in other classes. They also used artificial neural networks to classify
potato cultivars, in which the network was 82.41% accurate with one hidden layer and 100%
accurate with two hidden layers. In this study, it was found that different types of potatoes
can be identified and identified with a very high level of accuracy using the three color
characteristics, textural and morphological features extracted by the visual machine and the
use of a non-linear classifier artificial neural network. Categorized.
In another study that was conducted using neural networks and image processing on 5 sweet
potato cultivars, the researchers showed that this method was successful and could classify
sweet potato cultivars with 100% accuracy.
By determining and examining the existing relations between the force and the deformation
of agricultural products up to the point of surrender, the range of forces harmful to fruit can
be determined so that harvesting and transportation machines are designed in such a way that
the forces from them do not exceed this range. On the other hand, one of the ways to
determine the degree of ripeness of the fruit is to touch and press it with the thumb, which is
an experimental way and depends on the skill of the person touching it. The mechanical
penetration test of the fruit can be an indicator to check the ripeness of the fruit by
quantifying this diagnosis and using this diagnosis to determine the optimal harvest time.
Several types of research have been conducted on the physical and mechanical properties of
agricultural products in Iran and other countries. In a research conducted by Ali Mohammadi
and Rasakh to determine some mechanical properties of lime fruit under quasi-static loading,
the results showed that the effect of loading speed, loading direction and size of a lime on the
breaking force of lime is significant. As the size of the lemon decreases, the breaking force
and deformation decrease, and also with increasing loading speed, the braking force
increases. In another research conducted by Mohd Nejad and Khosdada, the effect of size,
speed and direction of loading on the mechanical properties of lime was investigated and the
results showed that the interaction of loading speed and size on fracture energy and toughness
and the main effects of size, loading speed and The loading direction is significant on the
modulus of elasticity, but none of the effects on the rupture force is significant.
Methodology
First, 5 different varieties of potatoes (Agria, Spirit, Sante, Marfona and Jelly) were prepared
from Ardabil Agricultural Research Center immediately after harvest. After preparing the
varieties, 21 samples of each potato variety were prepared using a cutting cylinder and then
data collection was done with santam machine.
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To measure the rupture energy of potato samples, santam device (available in the Biosystem
Engineering Department of Mohaghegh Ardabili University) was used. For this purpose, each
potato variety was subjected to a compressive force at three loading speed levels (10, 40 and
70 mm/min) with 7 repetitions. Then, using the amount of rupture force and deformation
(surface area under the force-deformation curve), the amount of rupture energy was
calculated.
The data obtained from the experiment were analyzed statistically with Minitab 18 software.
Conclusion
The amount of rupture energy in 5 different varieties of potato was obtained using santam
device and equation 1. The values obtained for 5 potato cultivars were analyzed using
Minitab18 software and the results are given in Table (1).
The results of the analysis of variance for the firmness of 5 different potato cultivars were
significant at the 1% level and the coefficient of variation was 9.6. In Figure 2, you can see
the average results.
According to Figure 2, it is clear that the lowest amount of rupture energy is related to the
Agria variety and the highest is related to the Jali variety. Also, it can be found that with a
loading speed of 10 mm/min, the highest amount of rupture energy is obtained in all figures.
In this research, the firmness level for 5 different potato cultivars was calculated using the
santam machine available at Mohaghegh Ardabili University and the area under the forcedeformation curve. The amount of calculated rupture energy has the ability to be used as a
method for the proper selection of different potato cultivars. The use of this method in potato
cultivars will be very useful for factories such as chips factories and processing units, and it is
also expected that similar methods related to mechanical properties such as crispness and
hardness and with the help of different statistical methods to optimize production and The
processing of agricultural products can be used in the food industry, which leads to more
customer-friendliness and can also reduce agricultural waste.