1 Introduction

The main challenge for humanity is providing food for the 11 billion by the end of this century. [1]. Despite heavy inputs like fertilizers and pesticides, green revolution technology has increased global productivity by 40% [2]. Pesticides, particularly those used against pests, are crucial in modern agricultural production [3] due to their ability to keep crops pest-free and ensure high crop yields, contributing to the significant increase in agricultural production [4]. The situation is similarly similar in Bangladesh, which has a population of 166.50 million and a density of 1125 persons per square kilometer, making it one of the world's most densely inhabited nations [5]. With 58% of the population in rural areas [6], the agriculture sector contributes 11.20% of the country's GDP in 2022–23 [7]. With a total land area of 14.8 million hectares, the nation must use its 14.3 million hectares of cultivable land to meet its population's food needs [6].

The people of the agrarian community live in extreme poverty and even suffer from food insecurity from time to time [8]. For the most part, they rely on traditional agricultural techniques and meteorological factors to produce their crops [9]. As a result, every year they face various natural calamities such as floods, droughts and cyclones which take lives and destroy crops, livestock and property [10]. Bangladesh has achieved notable strides in achieving its goal of achieving food grain self-sufficiency, mostly attributed to the notable augmentation of its agricultural sector [11]. For instance, nearly half of all rice acreage is now planted with advanced cultivars [12]. To maintain efficient and rapid agricultural expansion, intensification is necessary on a continuous basis [13]. However, there is growing fear that intensive farming may not be environmentally friendly and that it may harm other lucrative businesses like fishing, particularly by contaminating the water [14].

Since the 1950s, the use of agrochemicals has expanded by 150–300%, posing a major risk to both public health and the environment [15]. Compared to 1960 (758 metric tons) and 1980 (3028 metric tons), the amounts of pesticides applied in Bangladesh has grown significantly, reaching over 19,000 metric tons in 2000 [16]. In 2018, the total amount of pesticides applied nationwide rose to 38,691 metric tons [6]. The extensive use of banned pesticides in Bangladesh raises concerns about the possible effects of this rapid increase in pesticide use on farmers' health and the environment, notably pesticide poisoning [3]. However, the extensive use of pesticides poses a significant obstacle to the development of sustainable agriculture [17], leading to the contamination of food, water, and air—all essential elements of life [18, 19]. The irresponsible application of pesticides is causing three things: biodiversity loss, a decline in beneficial insects and spiders, and a progressive rise in agricultural production costs [20] which is creating a burden on the smallholder farmers [21].

Eco-friendly agriculture can be way to minimize the abundant use of agro-chemicals for crop production [22]. Shanka [2] studied about different eco-friendly crop production practices in African region like intercropping, cover crops, use of green manure, vermicomposting, crop rotation, Integrated Nutrient Management (INM), Integrated Pest Management (IPM) etc. and their role in lessening the use of pesticides. On the other hand, Ram et al. [23] showed the intensive use of eco-friendly crop production practices in India also. However, although there are a few instances, no such eco-friendly method is used by farmers at the grassroots level in Bangladesh [16]. Agrochemical use in the agriculture sector of Bangladesh can be reduced by a number of relatively simple interventions [24]. Keeping the aforementioned issues in mind, the Bangladeshi government launched a project named “Safe Crop Production through Eco-friendly Approaches”.

Several studies have been conducted on eco-friendly agriculture in different countries. Among them, Verma et al. [25] studied about eco-friendly approach called use of plant growth-promoting rhizobacteria, Shanka [2] studied about the roles of eco-friendly low input technologies in crop production in sub-Saharan Africa, Amoo et al. [26] studied on another eco-friendly approach called biofertilizer, Zuma et al. [22] studied on incorporating cropping system to mitigate the effects of climate change, Morya & Kumar [27] studied on eco-friendly pest management system. But no studies were found on the extent of use of eco-friendly crop production practices by the smallholder farmers and making any comparison among their usage. In addition to that, no literature was found to identify the factors that may influence the use of eco-friendly crop production practices by the smallholder farmers.

Thus, this study is undertaken to determine the extent of use of eco-friendly crop production practices by the project beneficiary and non-beneficiary smallholder farmers and whether there are any differences between their use. Finally, this study will also identify the factors that may influence the use of eco-friendly crop production practices by the two groups of smallholder farmers.

2 Methodology

2.1 Study location

The study was conducted in two villages (Darirampur and Birrampur Uzanpara) of Rampur union under Trishal Upazila (sub-district) of Mymensingh district (Fig. 1). These two villages are important because of their landscape and diversity which are suitable for agricultural production. For that reason, majority of the people (74%) of these two villages are engaged in agricultural activities compared to other villages of Rampur union. On the other hand, the investigational study region was purposefully chosen because Rampur Union was one of the areas where the project “Safe Crop Production through Eco-friendly Approaches” was intensively implemented and Rampur union was declared as an “IMP Model Union” by the Government of Bangladesh.

Fig. 1
figure 1

Map of Mymensingh district and Trishal upazila (sub-district) showing the study area

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2.2 Population and sampling

The smallholder farmers in 2 villages of Rampur union were considered as the target population of the study. From the 2 villages, 60 smallholder farmers were considered as representative from the project beneficiaries of the project “Safe Crop Production through Eco-Friendly Approaches” and another 60 were considered as a representative from the non-beneficiary smallholder farmers. Simple random sampling technique was used for selecting the smallholder farmers from the 2 villages. Thus, the total sample of the study was 120 smallholder farmers (60 from each of the project beneficiary and non-beneficiary smallholder farmers’ groups). The sampling technique is presented in Table 1.

Table 1 Distribution of population and sample of the smallholder farmers in the study area
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2.3 Household survey

An organized interview schedule was created utilizing existing literature on pertinent subjects to gather information from individual farmers. Understanding farmers' socioeconomic, personal, and contextual origins is essential to understanding why they employ eco-friendly crop production techniques. For this reason, the purpose of the interview schedule's first portion was to gather information regarding smallholder farmers’ age, educational level, household size, farm size, annual family income, farming experience, agricultural training experience, organizational participation, credit received, extension media contact, knowledge of and attitude toward eco-friendly crop production practices (Table 2).

Table 2 Measurement of independent variables of this study
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2.4 Data collection and measurement of variables

An organized questionnaire-based household survey, three key informant interviews (KIIs), and five focus group discussions (FGDs) were the study's principal sources of data and information. To complement the original data, secondary data was gathered from publications, scholarly journals, and unpublished works, like thesis and reports. The study's empirical data were gathered during March and April of 2022. The researcher did everything to build the necessary rapport with the participants so that they would feel comfortable answering the questions on the schedule. The next section provides a summary of each data collection technique.

2.4.1 Measurement of use of eco-friendly crop production practices

The extent of use of eco-friendly crop production practices by the project beneficiary and non-beneficiary smallholder farmers was the dependent variable of the study. To measure this, a 4-point rating scale was used. A total of 21 eco-friendly crop production practices were included in the questionnaire. These practices were identified by searching literatures from Rebouh et al. [28], Zhang et al. [29], Bahadur et al. [30], Devarinti [31]. The respondents were asked to rate their use on a 4-point rating scale, with the options "frequently," "occasionally," "rarely," and "never" and the scores that were awarded were 3, 2, 1, and 0, respectively [32]. Weights of responses were added and compared to the chosen 21 practices to get the final score and therefore, the score for the extent of use of eco-friendly crop production practices of a respondent could vary from 0 to 63. Independent sample t-test was performed at 5% level of significance to compare the use of eco-friendly crop production practices by the two groups of smallholder farmers.

Frequency counts of the responses were recorded to compute the Use Index (UI) for each of the eco-friendly crop production practices [33]. For determining the extent of use of individual practices, rank order was made based on Use Index (UI). Use Index was computed by using the following formula:

$$Use \, Index \, = \, \left( {N_{1} \times \, 3} \right) \, + \, \left( {N_{2} \times \, 2} \right) \, + \, \left( {N_{3} \times \, 1} \right) \, + \, \left( {N_{4} \times \, 0} \right)$$
(1)

Here, N1 = Number of farmers using frequently; N2 = Number of farmers using occasionally; N3 = Number of farmers using rarely; N4 = Number of farmers never used

In summary, the UI value of a practice may be calculated by summing the frequency counts of all the cells in the scale. A value of 0 denotes "no usage," while a value of 180 denotes "maximum use" for that specific practice.

Multiple linear regression analysis was used to identify influential factors that might have significant effects on the use of eco-friendly crop production practices by smallholder farmers [34]. Once more, a step-wise multiple regression analysis was carried out to comprehend the role that each of the significant factors had in explaining variation in the use of eco-friendly crop production practices [35]. This tool was used to identify the significant independent variables that have an effect on the dependent variable. It helps to reveal the value of adjusted R2, that is, the amount of change of the dependent variable by the independent variables. The equation of multiple regression is as follows:

$$y \, = \beta_{0} + \, \beta_{1} X_{1} + \, \beta_{2} X_{2} + \, \beta_{3} X_{3} + \, \beta_{4} X_{4} + \, \beta_{5} X_{5} + \, \beta_{6} X_{6} + \, \beta_{7} X_{7} + \, \beta_{8} X_{8} + \, \beta_{9} X_{9} + \, \beta_{10} X_{10} + \, \beta_{11} X_{11} + \, \beta_{12} X_{12} + \, e$$
(2)

Here, y = y^ + e = Use of eco-friendly crop production practices (Scale score); β0 = Intercept; X1 = Age (Yrs.); X2= Educational level (No.); X3= Household size (No.); X4= Farm size (Ha); X5= Annual family income (BDT); X6= Farming experience (Yrs.); X7= Agricultural training experience (Days); X8= Organizational participation (Scale score); X9= Credit received (Scale score); X10= Extension media contact (Scale score); X11= Knowledge of eco-friendly crop production practices (Score); X12= Attitude toward eco-friendly crop production practices (Scale score)

The study's objectives were followed throughout the compilation, tabulation, and analysis of the gathered data to find out mean, standard deviation, range, frequency and other statistical measurements. The data analysis was done using the Statistical Package for Social Science (SPSS v.21).

3 Results

3.1 Socio-economic characteristics of the two groups of smallholder farmers

The study made an effort to examine the socioeconomic characteristics of the two smallholder farming groups that were chosen as the sample of the study. Twelve selected characteristics of the smallholder farmers such as: age, educational level, household size, farm size, annual family income, farming experience, agricultural training experience, organizational participation, credit received, extension media contact, knowledge of and attitude toward eco-friendly crop production practices constituted independent variables of the study. Table 3 displays the descriptive parameters of the socioeconomic traits of the smallholder farmers.

Table 3 Socio-economic characteristics of the smallholder farmers
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Table 3 represents that the majority of the project beneficiary farmers (71.7%) and more than half of the non-beneficiary farmers (56.7%) were middle-aged. The t value of -1.02 indicated that there was no significant difference between the ages of the two groups. A considerable proportion of the project beneficiary farmers (43.3%) have secondary level education while less than half (46.7%) of the non-beneficiary farmers were illiterate. The t value of 1.93 indicated that there was no significant difference between the educational levels of the two groups of farmers. Ogunmefun and Achike [36] assert that farmers' educational attainment affects their ability to manage their operations and implement appropriate technology. Table 3 shows that about two-thirds (65%) of the project beneficiary farmers and less than half (43.4%) of the non-beneficiary farmers had large household size. The t value of 1.40 indicated that there was no significant difference in the household size.

Highest proportion of the project beneficiary farmers (95%) and absolute majority (96.7%) of the non-beneficiary smallholder farmers had small farm size but the t value of 0.47 indicated that there was no significant difference. Data presented in Table 3 shows that the highest proportion of the project beneficiary farmers (86.7%) had low-income and similar result was found for the non-beneficiary farmers where more than three-fourths (78.3%) had low-income. The t value of -0.51 indicated that there was no significant difference. The majority of the project beneficiary farmers (43.4%) had high farming experiences, whereas, the majority of the non-beneficiary farmers (40%) had medium farming experience. Highly experienced farmers are able to forecast market conditions and farm output [37]. The t value of -0.66 indicated that there was no significant difference.

Table 3 shows that majority of the project beneficiary farmers (70%) had short-duration training experience but the majority of the non-beneficiary farmers (71.6%) had no training experience. The t value of 7.17 clearly indicated that there was a significant difference. Training improves farmers' capacity to run their operations profitably and efficiently while also maximizing farm yield [38]. Majority of the project beneficiary farmers (75%) and majority of the non-beneficiary farmers (85%) had low organizational participation but the t value of 4.17 clearly indicated that there was a significant difference. Table 3 also represents that majority of the project beneficiary farmers (81.7%) and non-beneficiary farmers (66.7%) had received no credit. It is because farmers receive credit with high-interest rates which becomes a huge burden for them to pay the interest rate if production is not satisfactory [39]. The t value of -1.33 clearly indicated that there was no significant difference.

Highest proportions of the project beneficiary farmers (80%) and non-beneficiary farmers (65%) had medium extension media contact. Having access to extension agents makes it possible to obtain reliable information for a variety of farming tasks [40]. The t value of 11.75 clearly indicated that there was a significant difference. Data presented in Table 3 also show that more than half (51.7%) of the project beneficiary farmers had high level of knowledge, whereas more than half of the non-beneficiary farmers (86.7%) had a moderate level of knowledge. The t value of 20.23 clearly indicated that there was a significant difference. Knowledge of eco-friendly crop production practices is an important aspect of motivating farmers to use and incorporate those practices into their farming activities [41]. Finally, majority proportion (78.3%) of the project beneficiary farmers had a favorable attitude, whereas all of the non-beneficiary farmers (100%) had a moderately favorable attitude toward eco-friendly crop production practices. The t value of 19.78 clearly indicated that there was a significant difference. Attitude toward eco-friendly crop production practices is an important factor in the adoption and use of those practices. It is expected that negative attitudes toward the agrochemicals will increase the use of eco-friendly crop production practices by the non-beneficiary farmers [42].

3.2 Extent of use of eco-friendly crop production practices by the two groups of smallholder farmers

The primary goal of the study was to assess the extent of use of eco-friendly crop production practices by the project beneficiary and non-beneficiary smallholder farmers which is presented in Fig. 2. The scores obtained for the use of eco-friendly crop production practices by the beneficiaries ranged from 29 to 44 and the obtained score for the non-beneficiaries ranged from 11 to 26, against a possible range of 0–63. Based on the possible range, the respondents were classified into three categories: ‘low use (up to 21)’, ‘medium use (22–42)’ and ‘high use (> 42)’. Similar technique was followed by Alam et al. [43] in their study concerning with the use of agrochemicals in pineapple farming. This classification technique is also followed by Islam and Islam [44], Roy et al. [45], Rahman [46], and Farouque and Sarker [47] in their respective studies. Data presented in Fig. 2 show that the highest proportion of the project beneficiary farmers (95%) had medium use and on the contrary, the highest proportion of the non-beneficiary farmers (85%) had low use of the eco-friendly crop production practices. The t value was found 31.21 which clearly indicate that there was a significant difference in the use. That means the use of eco-friendly crop production practices by the project beneficiary smallholder farmers is much higher than the non-beneficiary smallholder farmers.

Fig. 2
figure 2

Distribution of the smallholder farmers based on their use of eco-friendly crop production practices

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It was found from Fig. 2 that the use of eco-friendly crop production practices by the project beneficiary smallholder farmers is much higher than that of non-beneficiary smallholder farmers. This may be due to that as the beneficiary smallholder farmers were involved in the project related to eco-friendly crop production techniques, they got different interventions from the project like different biological pest controlling equipment (yellow sticky trap, sex pheromone trap, net house etc.), biofertilizers, training on different non-chemical agricultural practices, demonstrations on organic farming and organic pest management, field days, workshops which resulted in better knowledge and attitude of the beneficiary farmers toward eco-friendly crop production practices. For that reason, the highest proportion (95%) of the project beneficiary farmers had medium use of the eco-friendly crop production practices compared to the non-beneficiary farmers. Mondal et al. [48] in their study found that about 46% of farmers used the practices of organic vegetable production in Thailand as they had proper knowledge. A study conducted by Nurzaman [49] found similar findings between two groups of farmers where the FFS farmers had a significantly higher practice of IPM than the non-FFS farmers. Mukta et al. [50] and Negatu et al. [42] also reported similar findings in their studies.

3.3 Rank order based on the use of eco-friendly crop production practices

For a better understanding of the use of eco-friendly crop production practices by the two groups (project beneficiary and non-beneficiary) of smallholder farmers, the Use Index (UI) was computed and presented in Table 4.

Table 4 Rank order of the eco-friendly crop production practices based on their use
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In case of the project beneficiary smallholder farmers, the first one is ‘Use of yellow sticky trap (UI-180)’. This may be due to the availability and cheap price of the yellow sticky trap in the local market. Other possibilities might be due to the efficiency of the yellow sticky trap for controlling insects, its simplicity and ease of use in the crop field which are supported by the study of Heinz et al. [51]. "Cultivation of cover crops" had the lowest score (UI-5), placing it at the bottom of the list (21st). This may be due to the reason that the project beneficiary farmers didn’t aware of this practice and different GOs and NGOs didn’t introduce this practice to the project beneficiary farmers. That’s why this practice was least used by them in the study area. Neill & Lee [52] found similar causes for less use of cover crops by the farmers.

Similarly, for a better picture of the extent of use of eco-friendly crop production practices by the non-beneficiary smallholder farmers, the Use Index (UI) was computed and presented in Table 4.

The first one is the ‘Practicing intercropping (UI-161)’. This may be due to that the non-beneficiary smallholder farmer has very limited agricultural land and that’s why they try to obtain as much profit as possible from those limited land area through intercropping. In many cases, intercropping is done to compensate for the failure of the main crop and also the ergonomic usage of the limited agricultural land. Gebru [53] reported similar findings in his study. Lastly, the practice named ‘Cultivation of cover crops’ got the lowest score (UI-2) and hence got the lowest (21st) position in the order. This can be because different GOs and NGOs failed to inform the farming community about this practice and non-beneficiary farmers were unaware of it. Neill & Lee [52] found similar causes for less use of cover crops by the farmers.

3.4 Factors influencing the use of eco-friendly crop production practices

To ascertain the components and their significance in predicting the focal variable, multiple linear regression analysis was done i.e., use of eco-friendly crop production practices by the two groups of smallholder farmers. Table 5 represents the summary of the multiple linear regression analysis for the project beneficiary smallholder farmers.

Table 5 Summary of linear regression analysis of the project beneficiary smallholder farmers explaining the dependent variable
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Six of the twelve variables were found to be significant, with an F value of 23.151 and an R2 of 0.855. This suggests that around 85.5% of the use of eco-friendly crop production practices might be explained by the combined influence of these six explanatory variables. Table 5 indicates the coefficient of educational level (t = 2.601; p < 0.05), annual family income (t = 2.402; p < 0.05), agricultural training experience (t = 3.640; p < 0.05), extension media contact (t = 2.973; p < 0.05), knowledge of eco-friendly crop product ion practices (t = 3.542; p < 0.05) and attitude toward eco-friendly crop production practices (t = 2.626; p < 0.05) had significant influence in predicting their use.

The regression coefficient indicates that if educational level changes by 1 number (one year of schooling) then the use changes by 0.116. That means project beneficiary farmers who belong to high educational levels will have more use of eco-friendly crop production practices. Sarker and Itohara [33] reported similar findings in the case of the extent of practices of organic farming technologies. Smallholder project beneficiary farmers’ annual family income had a significant positive coefficient value which was 0.024. The regression coefficient indicates that if annual family income changes by 1 number (1 thousand BDT) then the use changes by 0.024. That means project beneficiary farmers having high annual family income have more use of eco-friendly crop production practices. This result is consistent with that of Vidogbéna et al. [54], who discovered that the use of environmentally friendly nets for vegetable production was significantly influenced by the farmers' income. The regression coefficient indicates that if agricultural training experience changes 1 number (one day) then the use changes by 0.778. That means project beneficiary farmers having high agricultural training experience will have more use of eco-friendly crop production practices. Sarker and Itohara [33] also reported similar finding.

The regression coefficient indicates that if extension media contact changes 1 number (one scale score) then the use changes by 0.310. That means project beneficiary farmers having high extension media contact will have more use of eco-friendly crop production practices. Similar results regarding vegetable growers' adoption of environmentally friendly management strategies were reported by Pyasi et al. [55]. The regression coefficient also indicates that if knowledge changes 1 number (one score) then the use changes by 0.246. That means project beneficiary farmers having high knowledge will have more use of eco-friendly crop production practices. Uddin [56] reported similar findings in his study of sustainable agriculture. The regression coefficient indicates that if the attitude changes 1 number (one scale score) then use changes by 0.106. That means project beneficiary farmers having a favorable attitude will have more use of eco-friendly crop production practices. This finding is in line with Sarker et al. [57] where they found farmers’ attitude has a significant effect on organic homestead gardening. Considerable proportion (43.3%) of the project beneficiary farmers had secondary level of education which affected their use of eco-friendly crop production practices. Besides as they were part of the project, they got sufficient training, came in contact with different extension media which caused their better knowledge and attitude toward eco-friendly crop production practices which ultimately resulted in their increase in annual family income.

The outcomes of a step-wise multiple regression analysis are displayed in Table 6 to help comprehend the role of each significant variable in explaining variance in the level of usage of eco-friendly crop production practices by the project beneficiary smallholder farmers.

Table 6 Step-wise multiple regression analysis of the project beneficiary smallholder farmers
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Table 6 shows the percentage of different variables that explains the dependent variable. The analysis revealed that extension media contact (X10) expresses the dependent variable by 59.7%, attitude toward eco-friendly crop production practices (X12) expresses 9.0%, knowledge of eco-friendly crop production practices (X11) expresses 5.0%, agricultural training experience (X7) expresses 4.6%, educational level (X2) expresses 1.9% and annual family income (X5) expresses 1.4%. Mandal [58] explored similar findings where he found that the extension media contact was the major factor that contributed to explain the dependent variable i.e., the use of brinjal production technologies by the farmers.

Table 7 represents the summary of the multiple linear regression analysis for the non-beneficiary smallholder farmers.

Table 7 Summary of linear regression analysis of the non-beneficiary smallholder farmers explaining the dependent variable
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According to the results, four of the twelve variables had a significant F value of 18.488 and an R2 of 0.825. This suggests that about 82.5 percent of the use of eco-friendly crop production practices might be explained by the combined effects of explanatory variables. Table 7 indicates the coefficient of annual family income (t = 3.301; p < 0.05), agricultural training experience (t = 2.813; p < 0.05), organizational participation (t = 4.387; p < 0.05) and credit received (t = 3.845; p < 0.05) had significant influence in predicting their use.

The regression coefficient indicates that if annual family income changes 1 number (1 thousand BDT) then the use changes by 0.024. That means non-beneficiary farmers having high annual family income will have more use of eco-friendly crop production practices. This finding is in line with Vidogbéna et al. [54] where they found that the income of the farmers had significant effect on the adoption of eco-friendly nets for vegetable production. The regression coefficient indicates that if agricultural training experience changes 1 number (one day) then the use changes by 0.472. That means non-beneficiary farmers having high agricultural training experience will have more use of eco-friendly crop production practices. Sarker & Itohara [33] also reported similar finding.

The regression coefficient indicates that if organizational participation changes 1 number (one scale score) then the use changes by 1.046. That means non-beneficiary farmers having high organizational participation will have more use of eco-friendly crop production practices. Uddin [56] reported similar findings in his study of sustainable agriculture. The regression coefficient indicates that if credit received changes 1 number (one thousand BDT) then the use changes by 0.011. That means non-beneficiary farmers who received high credit will have more use of eco-friendly crop production practices. Similar results regarding vegetable growers' adoption of eco-friendly management strategies were reported by Pyasi et al. [55]. As the non-beneficiary smallholder farmers were involved with different organizations, they got training on different issues of agriculture from time to time. Again, as they received credit support from different organizations, they were capable of giving better input to their crop production and hence got better annual family income.

A step-wise multiple regression analysis was performed and the results are shown in Table 8 to help comprehend the role of each significant variable in explaining variance in the level of usage of eco-friendly crop production practices by the non-beneficiary smallholder farmers.

Table 8 Step-wise multiple regression analysis of the non-beneficiary smallholder farmers
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The Table 8 shows the percentage of different variables that explains the dependent variable. The analysis revealed that annual family income (X5) expresses the dependent variable by 64.1%, organizational participation (X8) expresses 7.0%, credit received (X9) expresses 4.0% and agricultural training experience (X7) expresses 2.9%. Akpan et al. [59] discovered comparable outcomes, concluding that the farmers' yearly family income was the primary factor that helped to explain the dependent variable, or the intensity of fertilizer use among small-holder crop farmers in the Abak Agricultural Zone of Akwa Ibom State, Nigeria.

4 Conclusions and recommendations

This study shown that the eco-friendly crop production practices, which were also easy to incorporate into their routine farming operations, had a significant positive impact on the smallholder farmers who were the project's beneficiaries. However, because they were left out of the project, the farmers who were the non-beneficiaries, do not have the necessary information or incentive to produce crops in an eco-friendly manner. It is recommended that adequate steps be taken to include more smallholder farmers in future projects in order to ensure safe crop production. In this case, a number of GOs and NGOs may take the necessary steps to establish and implement the same.

The results of the linear regression analysis showed that the six variables (educational level, annual family income, agricultural training experience, extension media contact, knowledge of eco-friendly crop production practices, and attitude toward eco-friendly crop production practices) explained 85.5% of the total variation in the use of eco-friendly crop production by the project beneficiary smallholder farmers. On the other hand, it was found that the four variables—annual family income, agricultural training experience, organizational participation, and credit received—accounted for 78.1% of the variation in the usage of eco-friendly crop production by the smallholder farmers who were not recipients. It is strongly recommended that the relevant authorities should continue to monitor farmers after the project is finished so they can apply the knowledge they have gained to their respective fields.