Optimization and Experiment on Key Parameters of Harvester for Auricularia auricula

Abstract

The Auricularia auricula harvester has low harvesting productivity, low qualification rate, and high breakage rate, and the lack of research on key operating parameters has become a bottleneck restricting the large-scale development industry. In view of the difficulty of industrialization and promotion of Auricularia auricula harvesting equipment, this paper combines the research on the physical properties of Auricularia auricula, adopts a quadratic orthogonal rotation combination design test and response surface analysis method to carry out the optimization and test of the key parameters of the harvesting equipment of Auricularia auricula, including the speed of the tray fungus stick (A), the frequency of the harvesting knife (B), and the distance of the harvesting knife (C). Design-Expert software was used to analyse the data and investigate the influence of each parameter and its interaction on the harvesting productivity, qualified rate, and breakage rate. The test results show that the factors affecting the harvesting productivity are in order: (A) > (B) > (C); the factors affecting the harvest qualification rate are in order: (C) > (B) > (A); and the factors affecting the harvesting damage rate are in order: (C) > (B) > (A). The multi-objective optimization results show that the optimal parameter combination of the key parameters of the Auricularia auricula harvesting equipment operation is that the tray speed is 308.17 r/min, the harvesting knife frequency is 10.78 Hz, the spacing between the harvesting knives is 84.67 mm, the productivity is 363 bags/h, the pass rate is 94.26%, and the breakage rate is 2.40%. The field production application under this optimized parameter combination shows that the productivity of the Auricularia auricula mechanized harvester is 346 bars/h, the qualified rate is 91.43%, and the breakage rate is 3.19%. This study can provide a reference for improving the quality of Auricularia auricula harvesting equipment.

1. Introduction

Auricularia auricula is mainly distributed in temperate and subtropical regions of the Northern hemisphere in China, Japan, Korea, Vietnam, and other places [1]. As the earliest country in the world to cultivate Auricularia auricula, China has been cultivating it artificially for more than 1400 years, and its output accounts for more than 90% of the world total [2,3]. According to the statistics of China Edible Fungi Association [4], in 2020, the output of Auricularia auricula in China will reach 7,064,300 t, accounting for 17.39% of the total output of edible fungi, with a yearly increase of 0.66%. It has been the second largest cultivated variety of edible fungi in China for many years. Auricularia auricula is a rare edible fungus unique to China. It is rich in polysaccharides, proteins, minerals, and various active substances, and has many functions such as anti-oxidation, anti-tumor, anti-aging, and lowering blood lipids [5,6,7,8]. In recent years, the export volume has been continually increasing, with the annual export volume reaching 19,200 t, and the annual foreign exchange earning exceeding 280 million dollars.

Harvesting of mature Auricularia auricula has the characteristics of short time and multiple harvesting. If not harvested in time, it will lead to Auricularia auricula rot or too big pieces, the large pieces, resulting in quality decline. At present, the production of Auricularia auricula has realized mechanization and automation, except for harvesting [9,10]. The picking efficiency of skilled Auricularia auricula farmers in the main producing areas of China is only 100~120 fungus sticks/h, which is far from meeting the demand of large-scale production of Auricularia auricula. Moreover, after continuous operation of workers, the picking efficiency and the qualified rate of harvesting will obviously decrease. Due to the operation principle of “harvesting the big Auricularia auricula and keeping the small ones” in China, at present, manual selective grading picking is still the main method for Auricularia auricula harvesting [11], supplemented by machinery. Compared with mechanized picking of fruits and vegetables, which mainly focuses on single fruit with regular shape, high hardness, and low density [12,13,14,15], Auricularia auricula picking requires one-time picking of high-density mature Auricularia auricula pieces growing on cylindrical mushroom sticks, instead of selective picking by flexible manipulator on the plane like Agaricus bisporus and Flammulina velutipes [16,17,18,19]. At the same time, because the foreign Auricularia auricula industry accounts for a relatively small proportion, no foreign researchers have studied the mechanized harvesting equipment of Auricularia auricula [20,21,22]. Currently, the research on harvesting equipment of Auricularia auricula in China focuses mainly on production equipment enterprises, and the harvesting quality is considered mostly by factors such as the shape, position, and material of harvesting knives. For example, in the mushroom rod-spinning harvesting equipment, the size of harvested Auricularia auricula is adjusted mainly by controlling the distance between harvesting knives and mushroom rods, which is relatively close and has high harvesting efficiency, but the yield of harvesting is low; on the contrary, the recovery efficiency decreases and the recovery qualification rate becomes higher. Chi Qingkai of Jilin Kai sheng Technology Manufacturing Factory has developed an automatic Auricularia auricula [23] picking machine, which is a fixed three-fungus-stick synchronous picking machine. Although the picking efficiency is 10 times higher than that of manual picking, the qualified rate is low, and the farmers’ acceptance is not high, so it has not been widely popularized and applied. Jia Guibo Heilongjiang Guilong Edible Fungi Machinery Equipment Co, Ltd., designed an assembly line horizontal Auricularia auricula harvester [24], which used rollers to harvest the fungus sticks as a whole, but the selective harvesting could not be realized during picking, and the qualified rate was low. Zhuang Zongqin et al. of Xiamen Qi Anda Automation Equipment Co., Ltd., proposed a fully automatic Auricularia auricula picking machine [25]. However, the equipment production and application have not yet been carried out.

The mechanized harvesting equipment of Auricularia auricula has not yet formed standardized technological parameters and equipment performance indicators due to less application demonstration, which leads to the low operation quality of the mechanized harvesting equipment, resulting in less application of Auricularia auricula growers or specialized cooperatives [26], which has seriously restricted the large-scale popularization and application of harvesting equipment. Therefore, in order to solve the restriction on the popularization and application of mechanized harvesting equipment of Auricularia auricula, this paper started with the research on physical characteristics of Auricularia auricula and carried out the experiment and optimization research on key parameters of Auricularia auricula harvesting equipment so as to obtain the best key operation parameters and provide reference for improving the operation quality of harvesting equipment.

2. Working Principle of Auricularia auricula Harvester

2.1. Structure of Harvester

According to the growth characteristics and picking requirements of Auricularia auricula, the mature pieces growing on the circumference of the cylindrical fungus stick should be picked, while the immature pieces should remain on the fungus stick to continue growing. Therefore, Auricularia auricula picking is different from single picking of fruits and vegetables and comb-clip picking of cotton and other crops [27,28,29]. Instead, the rotating fungus stick and reciprocating harvesting knife are combined to harvest fungus stick ear pieces. In this paper, the common mobile single-rod harvester, with fungus rod encircling and rotating in the main producing areas of Auricularia auricula, was used as the main test; the model is 4EH-120 Auricularia auricula harvester and the battery or 220 V power supply was used as the walking power. The Auricularia auricula harvester is basically composed of frame, rod pressing device, tray device, centralizer, harvesting device, aggregate box, walking wheel, and power system, and its structure is shown in Figure 1. When operating, the workers push the harvesting machine to the place where the fungus stick is to be harvested and adjust the distance between the harvesting knife and the fungus stick according to the size and density of the upper piece of the fungus stick. During harvesting, we must ensure that more than 80% of the pieces in the rod are in contact with the outer edge of the harvester to meet the rod recovery requirements. At the same time, the distance should not be too close to prevent small from being picked up, so that the requirement of “picking large Auricularia auricula and retaining small Auricularia auricula” cannot be realized. After electrifying, workers put the artificial bacteria rod to be harvested on the tray in the harvesting device with the top facing down, and at this time, the nest at the top of the bacteria rod is located on the positioning protrusion in the tray to prevent the bacteria rod from tilting when rotating. After the fungus collecting rod is put in place, the fungus rod is pressed by the rotating positioning beads in the rod pressing device, and at the same time, the encircling rebound centralizing mechanism is tightened to centralize the fungus rod before harvesting. When the righting mechanism is reset, the tray drives the bacteria rod to rotate. At this time, the harvesting knife fixed on the frame reciprocates. With the rotation of the bacteria rod, the Auricularia auricula pieces meeting the requirements are harvested by the harvesting knife and dropped into the box below. After the bacteria rod is harvested, the handle is lifted, the harvested bacteria rod is taken out, and then the bacteria rod is put into place for harvesting. During harvesting, the rod pressing device can rotate, so that the rod to be collected can smoothly enter the tray device.

2.2. Operation Process

Before harvesting Auricularia auricula, the appropriate working parameters of the harvester should be determined according to the varieties of different production areas, the specifications of fungus sticks, the growth of Auricularia auricula, and other conditions. The operation process is shown in Figure 2. After the power is turned on, manually put the bacteria rod (a) to be collected onto the positioning column (b) in the collection device to prevent the bacteria rod from tilting after rotation. At the same time, pay attention to the centering device when placing the bacteria stick to prevent the plastic bag or hand in the bacteria stick from being scratched. Press the bacteria rod through the gland (c) and touch the rotary motor and the collector motor to work, and then harvest (d). When the gland is lifted, the bacteria rod and the harvesting knife halts and the harvesting is completed (e).

2.3. Operation Quality Parameters

According to the effect of manual harvesting of Auricularia auricula and consumers’ requirements for Auricularia auricula quality, the performance indexes of mechanized harvesting equipment are divided into recovery rate, harvesting qualified rate (harvest the big and leave the small), and breakage rate. According to the above working principle, the main parameters that affect the quality of mechanized harvesting of Auricularia auricula are: the rotating speed of tray, the vibration frequency of harvesting knife, and the distance between harvesting knife and fungus stick. Among them, the rotating speed of the fungus stick and the frequency of the harvesting knife are the equipment operation parameters, and the distance between the fungus stick and the harvesting knife is the key technological parameter. The optimal parameter combination is the key to achieving the best recovery rate, harvesting qualification rate, and breakage rate of Auricularia auricula. Therefore, in this paper, a quadratic orthogonal rotation combination design experiment and response surface analysis method are used to carry out key parameter experiment and optimization research, so as to improve the operation quality of Auricularia auricula harvesting equipment.

3. Materials and Methods

3.1. Test Materials

The experiment selected the largest standardized production base of Auricularia auricula in China, “Hei Shan No.10”, the main variety planted in spring in the Dongning area, Heilongjiang Province. The mature Auricularia auricula was 15–35 mm in diameter and 0.7–1.0 mm thick, its color was dark brown, its back was gray and unreinforced, and it was gelatinous and flaky. Water spraying was stopped 1 day before harvesting Auricularia auricula, and it was harvested on a sunny day. Therefore, the test sample was the fungus stick one day after the water was stopped. As shown in Figure 3, the fungus stick is placed on a bed with a width of 160 mm and a middle aisle of 50 mm, and a perforated black plastic film is laid on the bed to prevent the soil from splashing on the Auricularia auricula. The diameter of the fungus is 110 mm and the height is 220 mm. The moisture content of the Auricularia auricula piece is 84.21%, the tensile elastic modulus is 0.947 MPa, the Poisson’s ratio is 0.445, and the shear elastic modulus is 0.327 MPa. In the test of connecting force between Auricularia auricula piece and fungus stick, the connecting force between piece and substrate is 3.167 N, the strength is 0.436 MPa, and the fracture failure occurs at the puncture hole of the fungus bag, that is, the Auricularia auricula root.

3.2. Test Conditions and Process

At present, the operation quality of Auricularia auricula harvester has not been defined in China’s agricultural industry standards. Therefore, the determination of field test methods and the determination of field conditions refer to the provisions of GB/T5262-2008 agricultural machinery test conditions determination method and GB/T67-2008 agricultural machinery production test method [30,31,32]. The harvest test was conducted in the open field Auricularia auricula production base in Suiyang Town, Dongning City, the first county of Auricularia auricula in China, from 12 June to 20 June, 2021. The test time was in the mature period of Auricularia auricula in spring, which was the best time for the harvest of Auricularia auricula. The water spraying was stopped 1–2 days before harvest, and the harvest was carried out in the morning of a sunny day. During the test, the mobile single rod Auricularia auricula harvester was used to randomly select the mature Auricularia auricula rods at the picking place, and the test was conducted according to the horizontal combination of factors designed in the test. For each group of tests, the level of each test factor was adjusted in advance. After the test is stable, the Auricularia auricula was picked. After the test is completed, the power was turned off, and the harvesting device left the test area. The picked Auricularia auricula was collected and the number of fungus sticks, qualified Auricularia auricula, and damaged picked Auricularia auricula were manually counted.

3.3. Test Instruments

In order to realize the continuous adjustment of the operating parameters of Auricularia auricula harvesting equipment, the speed regulator was used to adjust the rotating speed of tray motor and harvesting knife motor, and the distance between fungus rod and harvesting knife was positioned by Vernier caliper. The main instruments and equipment included US-52 pallet motor governor (Ou Bang, Taiwan Province, China, range 0–500 r/min,) and P1007a harvester motor governor (ZFX, Shenzhen China, range 0–100%, accuracy 1%). Other auxiliary tools included tachometer (model: Fluke 931, accuracy 0.02%); electronic scale (manufactured by Shanghai Lichen Instrument Technology Co., Ltd., Shanghai, China, model YP300001D, measuring range 0~30 kg, accuracy 0.1 g); calipers, stopwatches, and other equipment.

3.4. Test Methods

3.4.1. Determination of Factor Parameters

According to the working performance index and working parameters of Auricularia auricula harvester, three key factors affecting the harvesting effect were selected in this experiment: rotating speed of tray fungus rod (hereinafter referred to as rotating speed) x₁, vibration frequency of harvesting knife (hereinafter referred to as frequency) x₂, and distance between fungus rod and harvesting knife (hereinafter referred to as distance) x₃.

(1)

Speed

The fungus rod is driven to rotate by the tray. In the preliminary test, when the rotating speed of the tray was greater than or equal to 280 r/min, the Auricularia auricula piece firmly attached to the fungus rod could be completely harvested; if the rotating speed was too low, the root of the Auricularia auricula piece easily adhered to the fungus rod and will not easily fall off, resulting in the Auricularia auricula piece being damaged. If the rotating speed was too high, the Auricularia auricula piece dropped all the small Auricularia auricula together, resulting in a decrease in the yield of harvesting. In this experiment, the rotating speed of the bacterial rod was selected to be 280–320 r/min, and the rotating speed of the bacterial rod was set to 280, 300, and 320 r/min, respectively.

(2)

Frequency

The vibration frequency of the harvesting knife directly affects the integrity of the harvesting. If the vibration frequency increases, the Auricularia auricula will come in contact with the harvesting knife frequently, which will easily lead to the breakage of the Auricularia auricula. Therefore, when determining the vibration frequency of the harvesting knife, it is necessary to comprehensively consider both the harvesting efficiency and the Auricularia auricula piece breakage rate so as to ensure that the Auricularia auricula piece is harvested efficiently and its breakage rate is low. Through a single factor test of harvesting knife frequency, when the vibration frequency of the harvesting knife exceeds 8 Hz, the root of the Auricularia auricula piece can be completely separated from the substrate, and the frequency is too low. The harvested Auricularia auricula piece readily attaches to the fungus bag and cannot fall off, and the harvesting knife repeatedly collides up and down, resulting in broken Auricularia auricula. If the frequency is too high, this results in repeated collision between the Auricularia auricula piece and the harvesting knife, and the Auricularia auricula breakage rate increases. The vibration frequency of the harvesting knife in this test is selected within 8–12 Hz for the test, and the harvesting knife frequency is set to 8, 10, and 12 Hz, respectively.

(3)

Distance

The distance between the fungus rod and the harvesting knife directly affects the harvesting effect of the Auricularia auricula piece. The smaller the distance, the better the harvesting effect, but the small Auricularia auricula pieces that do not meet the harvesting requirements are also picked. If the distance is too large, the Auricularia auricula cannot come in contact with the recovery knife, resulting in lower recovery ratio. The position of the Auricularia auricula piece of the harvesting stick and the harvesting knife is shown in Figure 4.

To prevent the Auricularia auricula piece from being blocked by the harvesting knife, the distance between the harvesting knife and the fungus stick (L − D/2) should be larger than the minimum harvesting diameter of Auricularia auricula and smaller than the maximum diameter of Auricularia auricula. The theoretical range of L is 70 mm ≤ L ≤ 90 mm, and the Auricularia auricula pieces will be squeezed when being harvested. The best distance between the fungus stick and the harvesting knife needs to be determined by experiment, and the harvesting knife distances are set to 70 mm, 80 mm, and 90 mm, respectively.

3.4.2. Measurement of Response Index

According to the working performance requirements of Auricularia auricula harvester, this experiment selected the fungus rod harvesting productivity Y₁, ear piece harvesting qualified rate Y₂, and ear piece breakage rate Y₃ as its effect evaluation indexes.

(1)

Bacterial rod harvesting productivity Y₁

For the number of fungus rods harvested by Auricularia auricula harvester for 1 h, each group of tests was repeated 3 times, and the average of the results of the 3 tests was taken. The calculation formula is

$$Y_1=\frac{{}_Q}{t}$$

(1)

where Q is the number of collected bacteria rods, rods.

(2)

Harvesting qualification rate Y₂

The amount of 500 g of the Auricularia auricula in the collected aggregate box was randomly selected and weighed, and the total number of Auricularia auricula and the number of damaged Auricularia auricula were counted. According to the Auricularia auricula grade requirement in the national standard of Auricularia auricula (GB/T 6192—2019) [25], the product was sieved with a 15 mm sieve, and then the number of Auricularia auricula passing through the sieve was counted. Each group of tests was repeated 3 times, and the average of the results of 3 tests was taken. The calculation formula is

$$Y_2=\frac{n_1-n_2-n_3}{n_1}\times 100\%$$

(2)

In the formula, n₁ is the total number of Auricularia auricula, each; n₂ is the number of damaged Auricularia auricula, each; n₃ is the number of Auricularia auricula that failed to pass through the 15 mm screen, each.

(3)

Breakage rate Y₃

The amount of 500 g of the Auricularia auricula in the collected aggregate box was randomly selected and weighed, and the total number of Auricularia auricula and the number of damaged Auricularia auricula were counted. Each group of tests was repeated 3 times, and the average of the results of 3 tests was taken. The calculation formula is

$$Y_3=\frac{n_2}{n_1}\times 100\%$$

(3)

In the formula, n₁ is the total number of lugs, each; and n₂ refers to the number of damaged lugs, each.

3.4.3. Experimental Design

In order to obtain the best operation parameters of Auricularia auricula harvesting equipment, according to the single-factor test results, the quadratic rotation orthogonal combination design method was adopted to study the effects of the rotation speed of fungus rod, the frequency of harvesting knife, and the distance between fungus rod and harvesting knife on harvesting productivity, harvesting qualified rate, and harvesting damage rate, and the multi-objective parameter optimization was completed. The factor level codes are shown in

Table 1. Coding table of experiment factors and levels.

Level	Speed/(r·min−1)	Frequency/Hz	Distance/mm
−1	280	8	70
0	300	10	80
1	320	12	90

.

According to the level coding table of test factors, the quadratic rotation orthogonal combination design scheme was formulated to conduct the performance test of Auricularia auricula harvester; a total of 17 groups of tests were arranged, each group of tests was repeated 3 times, and the average of the three test results was taken. The test scheme design and result analysis were completed by Design-Expert 8.6.0 software, as shown in

Table 2. Result and design of tests.

No.	Factors and Levels			Response Index
	Speed A	Frequency B	Distance C	Productivity Y1/(bag·h−1)	Pass Rate Y2/%	Damage Rate Y3/%
1	320	8	80	352	90.81	2.94
2	300	10	80	372	94.35	3.46
3	300	12	70	368	84.83	7.69
4	300	12	90	348	91.52	1.12
5	320	12	80	376	89.25	3.73
6	300	8	90	340	91.43	0.81
7	300	10	80	366	93.85	3.31
8	300	10	80	369	94.61	3.11
9	280	12	80	346	87.03	4.12
10	320	10	70	361	82.67	6.57
11	280	10	70	349	88.48	4.86
12	300	10	80	361	93.81	4.02
13	280	8	80	352	90.04	2.73
14	300	10	80	364	95.13	3.13
15	300	8	70	358	91.35	3.86
16	280	10	90	330	86.49	0.92
17	320	10	90	342	92.64	0.96

. The mathematical regression models of recovery productivity Y₁, recovery qualification rate Y₂, recovery damage rate Y₃, tray rotation speed A, recovery knife frequency B, and the distance between bacteria rod and recovery knife skin C were obtained by analyzing the test results, and their interaction laws were analyzed and studied.

4. Results and Discussion

The test results are shown in Table 2. We analyzed the test results and fit the regression model equations of production rate Y₁, qualification rate Y₂, and damage rate Y₃, respectively, to study the influence of each factor on the evaluation index and the interaction rule. To investigate the data obtained in the test, Design-Expert software was used to conduct multiple regression fitting analysis and create a mathematical regression model of the performance indicators of Auricularia auricula harvester productivity Y₁, qualification rate Y₂, damage rate Y₃ on the tray speed A, the frequency B of the harvesting knife, and the distance C between the rod and the skin of the harvesting knife. The regression model formula is as follows:

$$\begin{array}{ll}{Y}_1=& 368.16+6.75A+4.75B+2.45C+7.50AB-\\ & 0.50BC-8.95A^2-0.95B^2-11.95C^2\end{array}$$

(4)

$$\begin{array}{ll}{Y}_2=& 92.64-1.08A-2.20B+4.98C+0.36AB+\\ & 2.99AC+1.65BC-3.64A^2-1.43B^2-3.14C^2\end{array}$$

(5)

$$\begin{array}{ll}{Y}_3=& 4.59+0.41A+1.23B-2.35C-0.15AB-0.42\mathrm{AC}-\\ & 0.88BC-0.034A^2+8.25\times {10}^{-3}{B}^2-0.044C^2\end{array}$$

(6)

4.1. Bacterial Rod Harvesting Productivity

(1)

Regression analysis of recovery productivity

According to the analysis of variance in

Table 3. Variance analysis of harvest productivity.

Index	Source	Square	df	Mean Squares	F	p
Y1	Model	2482.06	9.00	275.78	24.85	0.0002 **
	A	243.00	1	243.00	21.89	0.0023 **
	B	120.33	1	120.33	10.84	0.0133 *
	C	16.56	1	16.56	1.49	0.2615
	OFF	225.00	1	225.00	20.27	0.0028 **
	AC	0	1	0	0	1.00
	BC	1.00	1	1.00	0.09	0.7728
	A2	337.27	1	337.27	30.39	0.00091 **
	B2	3.80	1	3.80	0.34	0.5768
	C2	601.27	1	601.27	54.17	0.0002 **
	Residual	77.70	7.00	11.10
	Lack of fit	4.50	3.00	1.50	0.082	0.9664
	Pure error	73.20	4.00	18.30
	R2	0.9696
	Adjustment of R2	0.9306
	Coefficient of variation /%	0.94

Note: p < 0.01 (Extremely significant, **); p < 0.05 (Significant, *), the same below.

, the determining coefficient R² of the model is 0.9306 and the p-value of the model is 0.0002; the value of the misfitting item is 0.9664, so it can be judged that the fitting accuracy of the model is high with respect to the actual results. The reliability of response surface analysis results is high. The coefficient of variation of the model is 0.94%, which indicates that the precision of the model is good. This model can predict and analyze the change of the harvesting productivity of Auricularia auricula harvester, and according to the absolute value of the model coefficient, it can be judged that the primary and secondary order of the factors influencing the harvesting productivity of fungus sticks is: A, B, C.

(2)

Analysis of recovery efficiency and response surface of each parameter

The response surface and contour lines of various influencing factors on the harvesting productivity of fungus sticks are shown in Figure 5. The comprehensive response surface can judge the strength of the interaction between the two factors and the law of their impact on the harvesting productivity. It can be seen that the interaction between tray rotation speed and harvesting knife frequency has a significant impact on the harvesting productivity. The interaction between tray speed and harvesting knife distance, and the interaction between harvesting knife distance and harvesting knife frequency have no significant impact on the recovery productivity, which is consistent with the results of variance analysis in Table 3. It can be seen from Figure 5 that there is interaction between the rotating speed of the tray and the frequency of the harvesting knife. When the distance between the fungus rod and the harvesting knife is at the 0 level and the vibration frequency of the harvesting knife is at a low level, the harvesting productivity increases first and then decreases with the increase of the rotating speed of the tray. This is because the faster the rotating speeds of the tray, the more contact times between the upper ear piece of the fungus stick and the harvesting knife, which makes it easier to harvest the ear piece. However, with the increase of the rotating speed of the tray, the contact time between the upper ear piece of the fungus stick and the harvesting knife is reduced, resulting in the root of the ear piece remaining on the fungus stick, resulting in the decline of the fungus stick recovery rate. When the vibration frequency of the harvesting knife is at a high level, the harvesting productivity increases with the increase of the rotating speed of the pallet.

4.2. Harvest Qualification Rate

(1)

Regression analysis of recovery qualification rate

The results of variance analysis are shown in

Table 4. Variance analysis of pass rate.

Index	Source	Square	df	Mean Squares	F	p
Y2	Model	207.35	9.00	23.04	59.49	<0.0001 **
	A	6.21	1	6.21	16.03	0.0052 **
	B	25.84	1	25.84	66.73	<0.0001 **
	C	68.52	1	68.52	176.93	<0.0001 **
	OFF	0.53	1	0.53	1.36	0.2822
	AC	35.76	1	35.76	92.34	<0.0001 **
	BC	10.92	1	10.92	28.21	0.0011
	A2	55.79	1	55.79	144.05	<0.0001 **
	B2	8.58	1	8.58	22.16	0.0022
	C2	41.51	1	41.51	107.20	<0.0001 **
	Residual	2.71	7.00	0.39
	Lack of fit	1.49	3.00	0.50	1.64	0.3157
	Pure error	1.22	4.00	0.30
	R2	0.9871
	Adjustment of R2	0.9705
	Coefficient of variation/%	0.69

A—speed of tray, B—frequency of collector, C distance between rod and collector.

. It can be seen that the determination coefficient R² of the model is 0.9705, and the p-value of the model is less than 0.0001, which is very significant, and the value of the misfitting item is 0.3157, which is not significant. Therefore, it can be judged that the fitting accuracy of the model and the actual results is high, and the reliability of the response surface analysis results is high. The coefficient of variation of the model is 0.69%; this shows that the accuracy of the model is good. This model can predict and analyze the change of the harvesting qualified rate of Auricularia auricula harvester. According to the absolute value of the model coefficient, it can be judged that the primary and secondary order of the factors influencing the harvesting qualified rate of fungus sticks is: C, B, A.

(2)

Response surface analysis of qualified rate and parameters.

According to the test data in Table 4, the response surface of each factor to the yield of harvesting is shown in Figure 6. It can be judged that the interaction between tray speed and harvesting knife distance has a significant impact on the yield, followed by the interaction between harvesting knife frequency and harvesting knife distance; the interaction between tray speed and harvesting knife frequency has no significant impact on the yield, which is consistent with the results of variance analysis in Table 4.

It can be seen from Figure 6a that there is interaction between the pallet speed and the distance of the collector. When the frequency of the collector is at 0 water level, the percent of pass Y₂ first increases and then decreases with the increase of the tray speed and increases with the increase of the distance between the collector and the rod. This is because, with the increase of the tray speed, when the Auricularia auricula piece touches the collector, its root more easily falls off, but with the increase of the speed, it is easy to collect the surrounding small Auricularia auricula pieces together, leading to a decrease in the percent of pass; the distance of the harvesting cutter is far, the ear pieces collected are large, and the qualification rate is higher.

It can be seen from Figure 6b that there is an interaction between the frequency of the cutter and the distance of the cutter. When the rotating speed of the tray is at 0 level, the qualified rate Y₂ first increases and then decreases with the increase of the distance between the harvesting knife and the bacterial rod and decreases with the increase of the frequency of the harvesting knife. This is because the higher the frequency of the picking knife, the easier it is to cause the small Auricularia auricula pieces around the mature Auricularia auricula piece to be picked, resulting in the reduction of the qualified rate; the distance between the cutter and the rod determines the size of Auricularia auricula pieces. When the distance is relatively close, small Auricularia auricula are collected. However, when the distance is far, the total amount of Auricularia auricula pieces is greatly reduced and the qualified rate begins to decline slowly.

4.3. Recovery Failure Rate

(1)

Regression analysis of recovery failure rate

The results of variance analysis are shown in

Table 5. Variance analysis of damage rate.

Index	Source	Square	df	Mean Squares	F	p
Y3	Model	55.14	9.00	6.13	28.60	0.0001 **
	A	0.87	1	0.87	4.08	0.083
	B	8.07	1	8.07	37.67	0.0005 **
	C	15.26	1	15.26	74.25	<0.0001 **
	OFF	0.090	1	0.090	0.42	0.5375
	AC	0.70	1	0.70	3.26	0.1142
	BC	3.10	1	3.10	14.46	0.0064 **
	A2	4.94 × 10−3	1	4.94 × 10−3	0.023	0.8836
	B2	2.87 × 10−3	1	2.87 × 10−3	1.34 × 10−3	0.9718
	C2	8.24 × 10−3	1	8.24 × 10−3	0.038	0.8500
	Residual	2.71	7.00	0.21
	Lack of fit	1.49	3.00	0.32	2.28	0.2211
	Pure error	1.22	4.00	0.14
	R2	0.9735
	Adjustment of R2	0.9395
	Coefficient of variation/%	13.72

. It can be seen that the coefficient of determination R² of the model is 0.9395, and the p-value of the model is 0.0001; the value of mismatch is 0.2211, which is not significant. Therefore, it can be judged that the model has a high fitting accuracy with the actual results, and the reliability of response surface analysis results is high. The coefficient of variation of the model was 13.72%. The results show that the accuracy of the model is good. The model can predict and analyze the change of the failure rate of the harvester, and according to the absolute value of the coefficient of the model, the primary and secondary order of the influence of each factor on the recovery failure rate of the rod is: C, B, A.

(2)

Failure rate and response surface analysis of parameters

It can be seen from Figure 7 that there is an interaction between the frequency of the cutter and the distance of the cutter. With the increase of the recovery distance, the distance of the broken tray increases and the recovery frequency increases with the increase of the recovery distance. When the recovery distance is at a high level, the change of damage rate is not significant, which is because, when the recovery distance is large, the damage rate changes little, and the Auricularia auricula piece can be removed by the cutter in one operation and dropped into the aggregate box. There is no repeated harvesting in the process of dropping the Auricularia auricula piece. When the recovery distance is at a low level and the cutter frequency is at a high level, the recovery damage rate will reach a maximum value, which indicates that shorter cutter distance and higher cutter frequency are not conducive to the integrity of Auricularia auricula piece recovery.

4.4. Parameter Optimization

In order to ensure that the Auricularia auricula harvester has the best working performance, this paper optimizes the working parameters and structural parameters of Auricularia auricula harvester according to the high productivity, high qualified rate, and low damage. The optimization numerical module in V8.0.6.0 software is used for optimization, and the objective function and boundary conditions are as follows

$$\left\{\begin{array}{l}\max Y_1\\ \max Y_2\\ \min Y_3\\ X_1\in \left[-1,1\right]\\ X_2\in \left[-1,1\right]\\ X_3\in \left[-1,1\right]\end{array}\right.$$

(7)

At this time, the optimal recovery factor was the combination of design and software tools, and the optimal recovery factor was 308.6% R/26.6%, and the optimal recovery factor was the combination of design and software tools.

4.5. Test Verification

The operating parameters of Auricularia auricula harvester were adjusted to values close to the optimal combination of parameters: tray speed 300 r/min, cutter frequency 10 Hz, and cutter spacing 85 mm. In order to eliminate random error, three repeated tests were carried out to get the average values of productivity, qualified rate, and damage rate, which were 352 bags/h, 92.25%, and 3.12%, respectively, which were essentially consistent with the optimized parameters.

The parameter combination under which the experiment was carried out is as follows: tray speed 300 R/min, cutter frequency 10 Hz, interval of 85 mm. The continuous operation time of each harvest was no less than 2 h, and 5 groups were determined. The average productivity is 346 bars/h, the qualified rate is 91.43%, and the damage rate is 3.19%, as shown in

Table 6. Test results.

Survey Group	Productivity/(bag·h−1)	Pass Rate/%	Damage Rate/%
1	350	92.05	3.21
2	346	91.34	3.10
3	345	90.62	3.32
4	342	90.75	3.25
5	347	91.68	3.18
6	346	92.14	3.09
Average value	346	91.43	3.19
Standard deviation	2.38	0.59	0.08

.

5. Conclusions

The development of the Auricularia auricula industry is restricted by the poor quality of mechanized harvesting equipment. Improving the harvest quality of Auricularia auricula is of great significance to reduce the harvest loss, increase the income of farmers, and improve the harvest quality of Auricularia auricula. In this experiment, we measured the physical characteristics of mature Auricularia auricula, and described the working principle and process of harvesting equipment in order to determine the key parameters affecting the quality of Auricularia auricula harvesting. The results show that compared with manual harvesting, mechanized harvesting efficiency and quality are greatly improved. Through the analysis of variance and experiments, the important parameters that affect the quality of harvesting operation are obtained, and the accuracy and reliability of the prediction model are proved. The results showed that the harvesting quality and breakage rate were greatly improved compared with the previous results of other edible fungi varieties [16,17,18,19]. The relevant harvesting methods can be used to optimize the design of other edible fungi varieties.

In this experiment, we analyzed the working process of the Auricularia auricula harvesting equipment and optimized and verified the key parameters. The relationship between tray rotation speed, cutter frequency, and cutter distance and recovery, qualification rate, and breakage rate was studied by BBD test. BBD, ANOVA, mathematical modeling, and multi-objective optimization methods were used in the experiment, and the factors influencing the harvest efficiency were obtained as follows: tray speed > cutter frequency > distance between bacterial stick and cutter. The factors affecting the qualification rate are as follows: the distance between the bacterial stick and the cutter frequency > the cutter frequency > the pallet speed. The factors affecting the recovery damage rate are as follows: the distance between the rod and the collector > the frequency of the collector > the rotation speed of the tray. Combined with response surface analysis, it was found that the interaction between pallet speed and cutter frequency had a significant effect on harvest productivity (p < 0.01), while the interaction between other parameters had no significant effect; the interaction between pallet rotation speed and tool distance is more significant than that between tool frequency and tool distance. The interaction between tool frequency and tool spacing has a significant impact on the breakage rate (p < 0.01), but the interaction of other parameters has no significant impact on the breakage rate. Taking the maximum productivity and qualification rate and the minimum damage rate as the optimization goal, the test data was processed and optimized by Design-Expert software, and the optimal parameter combination of the recovery equipment was obtained as follows: the pallet speed was 308.17 r/min, the frequency of the recovery knives was 10.78 Hz, and the spacing of the recovery knives was 84.67 mm; the test result is the productivity was 363 bags/h, the qualification rate was 94.26%, and the damage rate was 2.40%. Small scale test verification was carried out with the optimized parameter combination tray speed of 300 r/min, cutter frequency of 10 Hz, and cutter spacing of 85 mm. The average productivity, qualification rate, and damage rate were 352 rods/h, 92.25%, and 3.12%, respectively, which were essentially consistent with the optimized parameter results. The production application under the optimized parameter combination shows that the productivity of the black fungus mechanized harvester is 346 rods/h, the qualification rate is 91.43%, and the damage rate is 3.19%. It further shows that the optimized parameters can meet the actual production requirements of the Auricularia auricula mechanized harvesting operation.