
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)13037-X
10.1016/j.heliyon.2024.e37006
e37006
Research Article
Determinants of exotic poultry breeds adoption by smallholder farmers in Gibe district, Hadiya zone, Ethiopia
Yesuph Dessalegn Shiferaw dessuyusuf@gmail.com
a⁎
Wordofa Muluken Gezahegn mgw.tud@gmail.com
b
Tefera Tesfaye Lemma t.lemma41@yahoo.com
c
a Department of Rural Development and Agricultural Extension, College of Agricultural Science, Wachemo University, P.O. Box 667, Hossana, Ethiopia
b Institutions, Innovation Systems, and Economic Development, Haramaya University, Dire Dawa, Ethiopia
c Rural Development, Haramaya University and Vice President for Research Affairs, Ethiopia
⁎ Corresponding author. dessuyusuf@gmail.com
28 8 2024
15 9 2024
28 8 2024
10 17 e3700621 12 2023
23 8 2024
26 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
This study aimed to analyze farmers' opinions, its role to household welfare, and the factors that influence the likelihood and intensity of exotic poultry adoption among rural chicken producers. To attain this, 155 households were targeted for interview. To this end, a multistage sampling procedure was administered to select households. Accordingly, quantitative data was backed by the qualitative data so as to bolster its credibility. Thus, the qualitative data was obtained through focus group discussions and key informant interviews. The result revealed that for enhanced market demand of chickens and egg production capacity among other allied factors farmers were interested with its production though exposure to disease and predators, absence of rural vaccination services, and the need for more care were also identified as challenges of production. Furthermore, exotic poultry producers’ get advantage over their non-exotic poultry producers as a result of the sale of eggs and a live chicken. The producers improved their diets notably for egg and chicken meat. This also implies that exotic poultry producers were better at food diversification than their counter part using the days recall method. The model output, on the other hand, showed that household size, farming experience, farm size, sex, off/non-farm income, livestock holding, distance to market, and access to credit service were all statistically significant at 1 %. The study suggests that focusing on key factors influencing the adoption and use of exotic poultry will help maintain and increase their adoption rates.

Keywords

Determinants
Adoption
Exotic poultry
Opinion
Double-hurdle model
Rating scale
==== Body
pmc1 Introduction

Poultry farming in Ethiopia supports livelihoods in multiple ways. It provides protein, generates extra income, offers security during tough times, and fosters social connections through gifts and hospitality [1]. The primary reasons for raising poultry are to meet immediate food needs and earn money [[1], [2], [3]]. Rural poultry farming, which requires minimal resources and investment, is especially appealing to the most disadvantaged and vulnerable segments of the rural population [4]. Therefore, boosting production can enhance income and food consumption, as surplus chickens can be traded for other livestock, such as small ruminants [5]. Additionally, diversified production helps manage risks more effectively [6] (see Table 1, Table 2, Table 3).Table 1 Size of sample households in the sample villages using PPS.

Table 1S/no	Name of village	Total no of HHs	Number of household	Number of sample household	Total sample	
Adopter	Non-adopter	Adopter	Non-adopter		
1	Homecho PA	546	195	351	12	21	33	
2	Hamolla	780	288	492	17	29	46	
3	Omochora	1294	565	729	33	43	76	
Total 3	2620	1048	1572	62	93	155	
Where, HHs=Households.

Source: Gibe district office of Agriculture

Table 2 Food groups and their weights.

Table 2Food groups Food groups Weight	
Cereals and Tubers (staples)	2	
Pulses	3	
Vegetables	1	
Fruit	1	
Meat (poultry)	4	
Milk	4	
Sugar	0.5	
Oil	0.5	
Source: WFP

Table 3 Respondents’ opinion on the production of exotic poultry.

Table 3Preference criteria of farmers to exotic poultry over the local breed	Anticipated benefits over local breed	Rank	
N	percentage	
Market demand of live chicken?	
 Superior	57	91.9	1st	
 About the same	5	8.1	
 Inferior	0	0	
Total	62	100	
Market price of egg?	
 Superior	46	74.2	4th	
 About the same	10	16.1	
 Inferior	6	9.7	
Total	62	100	
Egg production capacity?	
 Superior	53	85.5	2nd	
 About the same	9	14.5	
 Inferior	0	0	
Total	62	100	
Early maturing chicks?	
 Superior	48	77.4	3rd	
 About the same	8	12.9	
 Inferior	6	9.7	
Total	62	100	
Preference for egg?	
 Superior	19	30.6	5th	
 About the same	38	61.3	
 Inferior	5	8.7	
Total	62	100	
Source: Authors computation N = total number of responses ranging from superior, same, and inferior

Recently, there has been a growing demand for higher-quality food and more varied diets, which are linked to sufficient calorie and protein intake [4]. In Ethiopia, chicken consumption is strongly tied to wealth status and is mainly reserved for holidays [7,8]. According to Ref. [9], the average annual consumption of chicken meat is around 2.85 kg, with 57 eggs being consumed per year. Other sources report an annual intake of 1.87 kg of chicken meat and 57 eggs, or 2.29 kg. Despite poultry's significance in household income, consumption, food security, and the national economy, there is often a gap between the supply and demand for eggs and chicken meat [[8], [9], [10]]. With the country's population rising, the demand for these products is increasing, but the current production levels are insufficient to meet this growing need [2,11].

As a result, research and development of exotic chicken breeds in Ethiopia began in the early 1950s to enhance egg and meat production [12]. Since then, multiple centers for breeding and multiplying exotic chickens have been established to support national poultry extension efforts, providing farmers with improved birds and viable eggs [13]. Although there have been recent advances in the adoption of exotic poultry, Ethiopia's poultry production still consists of 78.04 percent local breeds, 17.58 percent hybrids, and only 4.34 percent exotic breeds [14]. Studies show that the economic contribution of exotic chickens in Ethiopia is significantly lower compared to other African nations, and their adoption is still in its early phases [[15], [16], [17]].

Research has been conducted to identify the reasons behind the low adoption of exotic chicken breeds. However, most previous studies have focused on assessing adoption levels, as well as examining the factors, performance, challenges, and opportunities related to exotic chicken production [15,[18], [19], [20], [21]]. Accordingly, key aspects like farmers' opinions about the particular technologies and their roles on household consumption and income generation have been overlooked. As a result, understanding farmers' perceptions of technologies is equally crucial in adoption decisions and thus deserves research attention [22]. Ref. [23] found that farmers' perceptions of technology-specific attributes affect the decision for adoption beyond other factors. However, earlier adoption studies have rarely considered the effect of farmers’ opinions on adoption decisions.

Previous studies often used single equation methods to assess poultry technology adoption, missing factors affecting both adoption and usage intensity. The double hurdle econometric model is recommended for its detailed analysis of adoption and usage intensity decisions, surpassing traditional models like Tobit and Heckman. In Gibe district, efforts over the past decade have focused on boosting chicken productivity by promoting popular exotic breeds like Rhode Island Red and White Leghorns [24]. However, no research has yet assessed the adoption levels of these breeds. To this end, this study aims to examine farmers' opinions, assess the role of these breeds on household welfare, and identify factors influencing the likelihood and extent of their adoption by smallholder farmers.

2 Materials and methods

2.1 Description of study area

The study was conducted in Gibe district, Central Ethiopia, within the Hadiya administrative zone. The district, with elevations from 1001 to 2500 m, is 260 km from Addis Ababa and borders Gomibora, Yem Zone, and Misha. It includes 21 rural villages and one rural town, with a population of 141,312 and 24,093 households [25]. The area has three climatic zones: 53.1 % midland, 32.7 % lowland, and 14.2 % highland, with annual rainfall between 1001 and 1200 mm and temperatures averaging 17.6 °C–25 °C [26]. Crop and livestock farming, including 42,985 chickens, are crucial for the local economy. While traditional methods are common, there is growing adoption of exotic chicken breeds like Rhode Island Red and White Leghorns to enhance productivity. Understanding adoption factors can improve their use and inform decision-makers.

2.2 Theoretical framework for adoption of exotic chicken breeds

Adoption refers to the choice to begin and continue using a technology [27]. This decision is grounded in the farmer utility maximization theory [23]. Numerous recent studies have applied this approach to examine decisions regarding the adoption and effects of improved technologies across different contexts [28,29]. The study used a random utility framework to model household decisions on adopting exotic chicken breeds. Households choose adoption to maximize utility, based on whether the benefits outweigh those of not adopting. Since the utilities of adopters and non-adopters are not directly observable, a latent model estimates the net benefit by including both observed and unobserved variables.

2.3 Sampling techniques and data collection

A multi-stage sampling method was used to select respondents for the study. First, Gibe district was chosen due to its notable poultry production. Villages with exotic poultry breeds were identified, and three namely Homecho, Hamolla and Omochora were randomly selected. Households in these villages were categorized as either adopters or non-adopters of exotic poultry breeds. From these, 155 households were randomly chosen for interviews, using a probability proportionate to size approach. The sample size for the investigation was chosen using [30] the simplified formula is:n=N1+N(e)2

Where n is the sample size, N is households in the study area (2,620) and e is the precision level at 8 %.

The study collected data from primary sources, including household surveys, semi-structured interviews, focus group discussions (FGDs), and key informant interviews (KIIs) in Omochora and Homecho villages. FGDs were held separately for men and women and jointly, using checklists. Six trained enumerators recorded and transcribed the data. Secondary data on population, agricultural costs, land use, and agroecology supplemented the primary data.

2.4 Methods of data analysis

A rating scale of three and four points was used to analyze opinions for chicken breeds and barriers to adopting exotic chickens. Both quantitative (percentages, ranks) and qualitative (narration) data were assessed. The role of exotic poultry on income and consumption was analyzed with descriptive statistics (frequency, mean, standard deviation), and food variety was measured using a Food Consumption Score (FCS) organized into eight categories [31].

FCS = a staples x staples+ a legum x legumes+ a vegetables x vegetables+ a fruit x fruit+ a animal (poultry) x animal (poultry)+ a sugar x sugar+ a dairy x dairy+ a oil x oil.

Where, FCS = Food consumption score, ai = Weight of each food group, and xi = Frequency of food consumption. A higher Food Consumption Score (FCS) indicates more frequent use of specific foods, greater dietary diversity, and family food habits over seven days. Econometric models assessed factors influencing adoption decisions, and truncated regression measured the intensity of exotic poultry adoption among adopters.

2.5 Double-hurdle econometric model specification

This study employed a Double Hurdle technique to evaluate how intensely farmers adopt exotic poultry. This approach involves two stages in the adoption process: the first assesses the decision to adopt, and the second measures the level of adoption [32]. [33]Research indicates that these two stages are interconnected. Previous studies [[34], [35], [36]] have used this framework to explore this relationship. The Double Hurdle model extends the Tobit model by distinguishing between two separate stochastic processes: one for the decision to adopt and one for the intensity of adoption. The double-hurdle model has an adoption (D) equation:

Di = 1 if Di*>0 the farmer adopts exotic poultry breed and 0 if Di*<0, otherwise.

Di = α′Zi + ui.

Being D* a latent variable that takes the value 1 if the farmer adopts exotic poultry breed and 0 otherwise, Zi are explanatory variables that determine the probability of farmers adoption of exotic poultry breeds, α coefficients of parameters estimated and Ui is the error term with zero mean and constant variance.

The level of adoption (Y) has an equation of the following:

Yi = Yi* if Yi*>0 and Di*>0.

Yi = 0 otherwise.

Yi* = β′Xi + Vi.where, Y = number of exotic poultry breed kept by a household in a specific period, Xi explanatory variables, β is a vector of parameters and Vi are error term distributed as follows:{Ui≈N(0,1)Vi≈N(0,δ2)

The log-likelihood function for the double-hurdle model is:logl∑0ln[1−∅(αZi′)(βXi′σ)]+∑ln[∅(αZi′)1σ∅(Yi−βXi′σ]

Under the assumption of independency between the error terms Ui and Vi the model (as originally proposed by Ref. [32] is equivalent to a combination of a truncated regression model and a univariate probit model.

3 Results and discussion

3.1 Farmers’ opinions on exotic poultry breeds

Among exotic poultry producers, 91.9 % believe exotic breeds have higher market prices for live chickens, and 74.2 % think exotic eggs are more valuable than local ones. Additionally, 85.5 % feel exotic breeds produce more eggs, and 77.4 % think exotic chicks mature faster. Focus group discussions indicate that higher market prices drive the shift towards exotic poultry, enhancing financial viability for farmers. Exotic poultry are favored for their size and accessibility, although 30.6 % of adopters prefer them for consumption. Barriers to adoption include disease susceptibility (41.9 %), high chick costs (37.1 %), and chick scarcity (29 %). Concerns also include high feed costs, lack of vaccination, and dissatisfaction with local health services, though marketing challenges, theft, and lack of extension support are not seen as major issues (see Table 4).

3.2 The role of exotic poultry adoption to household welfare

Table 5 shows that, on average, adopters earned an annual poultry income of ETB 975.11, which is significantly higher than the ETB 212.5 earned by non-adopters. The analysis highlights a notable difference in total annual household income from poultry between these two groups. This suggests that the increased income could be attributed to the benefits adopters gain from raising exotic poultry, allowing them to sell more eggs and live chickens compared to those raising local breeds (see Table 6).Table 4 Respondents’ opinion on exotic poultry production challenges.

Table 4Potential challenges to its production	Four point rating scale for measuring barriers		Rank barriers	
Not barrier	Somewhat barrier	Moderate barrier	Extreme barrier	Total N	Total %	
N	%	N	%	N	%	N	%	
Inaccessibility of the chicks	12	19.4	14	22.6	18	29	18	29	62	100	4th	
Expensiveness of the chicks	5	8.1	6	9.7	28	45.2	23	37.1	62	100	3rd	
Susceptibility to predators	43	69.4	7	11.3	8	12.9	4	6.5	62	100	9th	
Susceptibility to disease	16	25.8	1	1.6	19	30.6	26	41.9	62	100	1st	
Needs more care	21	33.9	4	6.5	22	35.5	15	24.2	62	100	5th	
High feed requirement	37	59.7	4	6.5	11	17.7	10	16.1	62	100	6th	
Lack of credit access	40	64.5	6	9.7	8	12.9	8	12.9	62	100	7th	
Lack of vaccination	8	12.9	9	14.5	21	33.9	24	38.7	62	100	2nd	
Lack of extension support	49	79	9	14.5	4	6.5	–	–	62	100	–	
Marketing problem	57	91.9	4	6.5	1	1.6	–	–	62	100	–	
Problem with output taste	51	82.3	8	12.9	3	4.8	–	–	62	100	–	
Theft	56	90.3	3	4.8	2	3.2	1	1.6	62	100	9th	
Lack of awareness	49	79	7	11.3	5	8.1	1	1.6	62	100	9th	
Could not hatch	44	71	4	6.5	9	14.5	5	8.1	62	100	8th	
Source: Authors computation N = number of responses ranging not barrier, somewhat barrier etc. % = percentage of responses

Table 5 The average annual income from sale of poultry for the sample respondent.

Table 5Distribution statistics	Adopter	Non-adopter	t-value	p-value	
Mean	975.11	212.5	−10.76	.000***	
Standard deviation	598.10	270.93			
Minimum	–	–			
Maximum	2145	1266			
Source: Authors computation *** represents level of significance at 1 %

Table 6 The mean number of days that different food groups consumed.

Table 6Mean number of days food group consumed with FCS by the respondents	Adopter	Non-adopter	t-value	p-value	
Cereal and tubers	7.93	6.08	−4.13	0.000***	
Pulses	5.56	6.06	0.68	Ns	
Meat (poultry)	5.87	2.75	−3.22	0.000***	
Vegetables	4.61	3.16	−5.99	0.000***	
Fruit	1.51	1.54	0.169	Ns	
Oil	1.42	1.72	2.55	0.012**	
Sugar	0.34	0.44	0.980	Ns	
Milk	3.23	5.03	2.80	0.006***	
Total	30.47	26.78	−1.76	0.080*	
Source: Authors computation Ns = not significant *, ** and *** indicates significance level at 1 %, 5 % and 10 %

The Food Consumption Score, which measures how often different food groups are consumed over a week, revealed that households raising exotic poultry had a higher average score (30.47) compared to those who did not (26.78). This higher score likely results from increased income, allowing adopters to buy a wider range of foods. Adopters consumed more meat, cereals, and vegetables, but less milk and dairy, possibly due to owning fewer cattle. Non-adopters consumed more pulses, milk, oil, fruit, and sugar. Exotic poultry provided more eggs and meat, contributing to greater dietary diversity, whereas local breeds offered fewer eggs and were less effective in feeding large families. On the other hand, over the one-week recall period, respondents most frequently consumed cereals and tubers, followed by vegetables, oil, fruit, pulses, milk, meat (beef, goat, poultry, eggs), and honey. Consumption rates were highest for cereals and tubers (100 %), and lowest for honey (43.3 %).

3.3 Determinants of exotic poultry adoption and intensity of use

The study used a double-hurdle econometric model to analyze factors affecting exotic poultry adoption. To address potential multicollinearity among variables, the variance inflation factor (VIF) and coefficient of contingency were applied. Results showed no significant multicollinearity issues, as the coefficients were very low.

3.3.1 Determinants of household exotic poultry adoption decision

A larger household size significantly increases the likelihood of adopting exotic poultry by 6.4 % for each additional member, as larger households can manage poultry more efficiently and save on labor costs (Table 7). This results in better poultry management and reduced production expenses. This finding aligns with studies in Refs. [37,38], which also show that larger households positively and significantly influence the adoption of exotic poultry and dairy technology. However, it contrasts with the findings of Ref. [39], which reported a negative relationship between family size and the adoption of improved poultry.Table 7 Marginal effects of probit regression for decision of improved poultry adoption.

Table 7Variables	Coef.	Std. Err	P > /Z/	Marginal Effect	
 _cons	.0240419	1.228487	0.984		
SEXHH	−.1420707	.5741261	0.805	−.0120684	
AGEHH	−.0048424	.0236433	0.838	−.0053841	
EDULHH	−.2944477	.3467843	0.396	−.0760895	
FAMSZE	.3459991	.1146506	0.003***	.0646253	
LIVHOLD	−.3400996	.1010693	0.001***	−.0298333	
FARMSIZE	−1.094162	.3495348	0.002***	−.1367179	
OFFFARM	.0000667	.0000956	0.485	.0000127	
OUTPUTTASTE	1.098008	.4236057	0.010**	.1679179	
DRESISTANCE	−.0515801	.3638348	0.887	−.0578759	
CREDIT	−1.089799	.4055898	0.007***	−.1613552	
EXTENSION	−.0075753	.1082704	0.944	.0013689	
PAINCOOP	1.11379	.4757398	0.019**	.1091037	
MARKDISTCE	−.2671294	.095369	0.005***	−.0379448	
YRSADOPTION	.209183	.0397534	0.000***	.0453777	
Household exotic poultry breed adoption decision, Log likelihood = −34.98 Pseudo R2 = .66, LR chi-square (14) = 138.67, Prob > chi2 = .000, N = 155.

Source: Model result ** and *** indicates significant level

Livestock ownership negatively impacts the decision to adopt exotic poultry, with each additional unit of livestock reducing the likelihood of adoption by 3 %. Households with more livestock are less likely to adopt exotic poultry, likely due to a focus on larger investments with perceived higher returns. This result differs from studies in Refs. [40,41], which found that livestock ownership increased the adoption of other technologies like sweet potato varieties and crossbred dairy cows. However, it aligns with Ref. [42], which also reported that large livestock holdings negatively and significantly affect exotic poultry adoption.

Farm size negatively affects exotic poultry adoption, with each additional .125 ha of land reducing the likelihood of adoption by 14 %. This is likely because farmers with more land focus on crop production, expecting higher returns than from raising small animals. This finding is consistent with Ref. [2], which reported a similar relationship, but contrasts with Ref. [39], which found that larger farm sizes positively influenced poultry adoption. A positive assessment of exotic poultry taste significantly increases adoption likelihood by 17 % for each 1 % improvement in taste perception. Farmers are more likely to adopt exotic breeds if they view their taste favorably, despite some preference for local poultry for home consumption. The study aligns with Ref. [43], which also found that acceptance of new technology's output taste positively influences adoption.

A 1 % increase in credit access surprisingly decreases the likelihood of adopting exotic poultry by 16 %, possibly because households with credit prefer investing in larger, potentially higher-return ventures rather than poultry. This finding contrasts with Ref. [39], which reported a positive relationship between access to credit and poultry adoption. Participation in cooperatives increases the likelihood of adopting exotic poultry by 11 %, likely due to better access to agricultural advice and information. This finding aligns with studies in Refs. [39,44], which also found that cooperative membership increases the likelihood of technology adoption.

3.3.2 Determinants of the intensity of exotic poultry adoption

The truncated regression model, which assesses the intensity of exotic poultry adoption based on the number owned, was statistically significant at the 1 % level. The model effectively explains the relationship between the variables, with factors like household gender, cooperative participation, off-farm income, experience with exotic poultry, and market distance influencing adoption intensity (Table 8).Table 8 Results of truncated regression for the intensity of exotic poultry breed adoption.

Table 8Variables	Coef.	Std. Err	P > /Z/	
 _cons	−1.792229	6.988532	0.798	
SEXHH	−4.730603	2.52972	0.061*	
AGEHH	.152765	.1293698	0.238	
EDULHH	−2.500418	1.685245	0.138	
FAMSZE	.2670054	.4709789	0.571	
LIVHOLD	.0901489	.3848683	0.815	
FARMSIZE	−.8181667	1.872679	0.662	
OFFFARM	−.000755	.0003931	0.055*	
OUTPUTTASTE	−2.495525	2.171688	0.251	
DRESISTANCE	−1.919302	1.595845	0.229	
CREDIT	−.0271926	1.977674	0.989	
EXTENSION	.3879361	.3724581	0.298	
PAINCOOP	7.0924	2.99909	0.018**	
MARKDISTCE	−.8476907	.4711787	0.072*	
YRSADOPTION	1.404782	.2797666	0.000***	
Intensity of exotic poultry breeds adoption by household, limit: lower = 0, upper = +inf, Wald chi2(14) = 70.74, log likelihood = −167.26, Prob > chi2 = .0000, N = 62.

Source: Model result *, ** and *** indicates significant level

Female farmers were found to keep 4.7 more exotic poultry than male farmers, possibly because female-headed households, often with fewer resources, are more inclined to adopt low-cost, manageable technologies like poultry farming, which is typically seen as a minor activity for women and children. This finding is consistent with Ref. [39,42], which showed that being female positively influences poultry adoption, though it contradicts the results of Ref. [37,45], which indicated that being female negatively affects the intensity of adoption.

Increased off-farm/non-farm income significantly reduces the number of exotic poultry kept, as higher income leads to a decrease of .0008 poultry per income unit. This suggests that farmers allocate resources and labor to more lucrative activities, choosing higher-paying off-farm jobs over poultry management. This finding aligns with the conclusions of Ref. [39,46], which found that off-farm income reduces the intensity of improved poultry adoption.

On average, each additional year of adopting exotic poultry breeds results in an increase of about 1.4 poultry per household, with early adopters benefiting more and showing greater adoption intensity over time. This finding is consistent with Ref. [38,39], which reported that experience with technology positively influences the adoption of dairy technology.

4 Conclusion

The study examined socio-economic and demographic factors affecting the adoption of exotic chickens by smallholder farmers in the Hadiya Zone. Key influencing factors include household size, gender of the head, off-farm income, farm size, livestock holdings, experience, market proximity, taste assessment, cooperative participation, and credit access. To boost adoption, the study recommends supporting farmer cooperatives, offering lower interest rates on credit, promoting cooperative membership, improving credit access, and enhancing training for farmers on exotic chicken breeds.

Funding statement

No funding has been received from any organization for this study.

Data availability statement

All data are included in the article/referenced in the article.

CRediT authorship contribution statement

Dessalegn Shiferaw Yesuph: Software, Resources, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Muluken Gezahegn Wordofa: Validation, Supervision, Software, Methodology, Data curation, Conceptualization. Tesfaye Lemma Tefera: Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.

Declaration of competing interest

We express our strong desire to have original work published in your journal, Heliyon. Thank you very much in advance for publishing our original work in your journal.

Acknowledgments

The authors would like to express sincere gratitude to all officials, sample respondents, and experts who participated in providing relevant information and data collection along with editors and reviewers.
==== Refs
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