Научная статья на тему 'WHICH AGRICULTURAL INNOVATIONS MATTER MOST TO NIGER’S FARMERS? COUNT-BASED AND BEST-WORST SCALING APPROACHES'

WHICH AGRICULTURAL INNOVATIONS MATTER MOST TO NIGER’S FARMERS? COUNT-BASED AND BEST-WORST SCALING APPROACHES Текст научной статьи по специальности «Сельское хозяйство, лесное хозяйство, рыбное хозяйство»

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Agricultural innovations / farmers / changing climate / conditional logit / complete block design

Аннотация научной статьи по сельскому хозяйству, лесному хозяйству, рыбному хозяйству, автор научной работы — Amadou Zakou

The negative impact of quadruple insecurities (food, health, security and climate change) on smallholder farmers and their livelihoods have been considered as global challenge and threat for sustainable development and climate change management in most developing nations. Although farmers have developed and keep developing coping strategies by innovating to accommodate the negative impact of this quadruple insecurity, little is relatively known how agricultural innovations and its impact on farmers’ welfare in changing climate are poorly understood. Based on previous studies and Survey amongst farmers, twenty four agricultural innovations have identified and included in this research. The experimental design popularly called complete block design was used to collect data from 436 farmers randomly selected. For each question, farmers were asked to choose his eight best and his eight worst agricultural innovations in changing climate. This repeated process is consistent with random utility, which is deeply rooted in microeconomic theory. Count-based method and multinomial logit were used to fit the data. Results indicate that rainfed rice production, saving and credit scheme for rural women, Maradi red goat breeding, processing peanuts into oil and cake, planting trees for land recovering, using of annual and perennial crops for cattle fattening, manufacturing handicrafts with local perennial crops, honey harvesting via improved beehives, cheese making are the most important agricultural innovations that farmers would prefer to implement in changing climate. Income and Animal-based agricultural innovations are more welfare enhancing. The findings of this research may be used to promote and achieve the United Nations sustainable development goals by planning changes and thereby improving the food security and local farmer’s welfare in the study area and beyond.

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Текст научной работы на тему «WHICH AGRICULTURAL INNOVATIONS MATTER MOST TO NIGER’S FARMERS? COUNT-BASED AND BEST-WORST SCALING APPROACHES»

UDC 631

WHICH AGRICULTURAL INNOVATIONS MATTER MOST TO NIGER'S FARMERS?

COUNT-BASED AND BEST-WORST SCALING APPROACHES

Amadou Zakou

Department of Rural Economics and Sociology, Faculty of Agricultural Sciences, Djibo Hamani University, Tahoua, Niger E-mail: zakouamadou77@gmail.com

ABSTRACT

The negative impact of quadruple insecurities (food, health, security and climate change) on smallholder farmers and their livelihoods have been considered as global challenge and threat for sustainable development and climate change management in most developing nations. Although farmers have developed and keep developing coping strategies by innovating to accommodate the negative impact of this quadruple insecurity, little is relatively known how agricultural innovations and its impact on farmers' welfare in changing climate are poorly understood. Based on previous studies and Survey amongst farmers, twenty four agricultural innovations have identified and included in this research. The experimental design popularly called complete block design was used to collect data from 436 farmers randomly selected. For each question, farmers were asked to choose his eight best and his eight worst agricultural innovations in changing climate. This repeated process is consistent with random utility, which is deeply rooted in microeconomic theory. Count-based method and multinomial logit were used to fit the data. Results indicate that rainfed rice production, saving and credit scheme for rural women, Maradi red goat breeding, processing peanuts into oil and cake, planting trees for land recovering, using of annual and perennial crops for cattle fattening, manufacturing handicrafts with local perennial crops, honey harvesting via improved beehives, cheese making are the most important agricultural innovations that farmers would prefer to implement in changing climate. Income and Animal-based agricultural innovations are more welfare enhancing. The findings of this research may be used to promote and achieve the United Nations sustainable development goals by planning changes and thereby improving the food security and local farmer's welfare in the study area and beyond.

KEY WORDS

Agricultural innovations, farmers, changing climate, conditional logit, complete block design.

Achieving sustainable development goals (SDGs) has been not only eroded by human capacity development and demographic challenges, but also threatened by difficult and unpredictable climatic conditions as well as by the recent COVID-19 pandemic. There are also many complex agricultural production challenges such as infertile soils, low and erratic rainfall regime, floods, drought, lack of adequate market information, low human and socioeconomic development making the predominant smallholder farmers face uncertain situations in attempting to intensify food production. Therefore, farmers need to have adequate access to quality extension agent, resources and agricultural innovations to enable them increase productivity thereby enhancing food and income security (Braun et al, 2021). The application of agricultural innovations towards achieving sustainable development goals in African countries such as Niger is poorly understood and documented.

African countries in general and West African countries in particular are expecting considerable contributions from science and technology in the agricultural sector in order to address the significant challenges related to population, economic growth, food security, climate change, poverty reduction (Zoundi & Hitimana, 2005). These challenges have been exacerbated by the covid-19 pandemic negative impact on food sector and agriculture. The pandemic has also stimulated innovative spirits by developing and deploying digital technology thereby addressing these challenges and proposing solutions. Recent studies

from Africa suggest that digital technology can enhance smallholder productivity and income by improving their access to farm output, inputs and financial markets. A large body of studies has also revealed that innovation in general and agricultural innovation in particular when properly managed can contribute to achieve sustainable goals. Studies have also indicated that technological and institutional innovations can potentially improve the agricultural productivity, food security and income levels of smallholder men and women farmers. However, innovation processes are hindered by barriers related to governance, the economy, knowledge, socio-cultural factors, and resource factors. Furthermore, transform followers to leaders and leaders to agent of change is key to effectively and efficiently manage limited resources for the benefit of the majority (Haug et al., 2021). Digitalization of African agriculture has recently gained momentum with diversity of digital tools, platforms and services emerging and being deployed to support delivery of extension agents to farmers, thereby contributing to reduce rural poverty and improve food security in Africa (Juma, 2011; Gatzweiler & Von Braun, 2016). Finally, understanding and applying these innovations in agriculture thereby achieving United Nations' sustainable development goals is a key challenge.

In Niger, balancing population growth and the food supply constitutes a real challenge especially in countries where agricultural innovations' adoption rate is still very low (Braun et al. 2021). There were 32 agricultural innovations that have been characterized, selected and documented, in which 12 innovations in Dioundiou and Yelou, 20 innovations in Torodi and Makalondi (Saidou & Adam, 2013). The objective of this Project is to help farmers to build their resilience capacity in order to enhance food security. This project called Innovation Africa pointed out that food security should be based on the promotion of agricultural innovations and local strategies as well as local planning thereby improving food security situation at rural household level. Participative approach was used to compile the best agricultural innovations and local strategies for food security. Endogenous, exogenous and hybrid agricultural innovations have been disseminated, but in realizing agricultural innovation objectives as a result of the advancement in information and communication technologies (ICT), adequate agricultural information should be provided to farmers. Digital agricultural is also a key to plan and effectively and efficiently manage changes that may occur in the future. In addition,

E-agriculture has been recently developed to improve agricultural and breeding practices for both crops and livestock, facilitate easy access to market and thereby gaining a better benefit for their products (Hamadou, 2018).

In Tahoua State, agricultural innovation such water and soil conservation activities has been undertaken to bring back marginal land in active agricultural production. Thus, Tahoua State has benefited several interventions ranging from Keita integrated project, to low valley projects and small scale irrigation which have been used as strategies to restore degraded ecosystems and thereby ensuring food security. Recent studies have also documented that exogenous, endogenous and hybrid agricultural innovations have been developed and disseminated amongst resource-poor farmers, but agricultural production is still low and the impact of introducing these agricultural innovations on farmers productivity, income, poverty reduction and welfare is poorly understood and documented.

The objective of this paper is to assess farmers' preferences for agricultural innovations. Specific objectives include: (i) to determine the influence of farmers' socioeconomic characteristics on agricultural innovations; (ii) determine the influence of farms' characteristics on agricultural innovations. We hypothesize that crop-based agricultural innovations are more welfare enhancing in animal-based agricultural innovations. We also hypothesize that income generating activities based agricultural innovations are more welfare enhancing than food science and nutrition based agricultural innovations. Finally, we assume than endogenous agricultural innovations are more welfare enhancing than exogenous and hybrid agricultural innovations.

THEORETICAL FRAMEWORK

The farmer immediate environment is dynamically influenced by various changes due to climate change, flood, tornado and famine. Random utility theory that is well rooted in microeconomic has been widely used in studying consumers' behavior. Methods of data collection such as on likert scale as well as Best Worst Scaling (BWS) have well documented in the literature, but methods such as complete block design as data collection is still in its infancy. Extension agents are trained as leaders to facilitate innovations diffusion amongst rural farmers who become agent of change. Farmers adopt a given innovation where he has perceived the intended benefits. Similarly, when a bundle of innovations are presented to farmers, they would make repeated choices amongst the most important, the least important and indifferent bundles.

MATERIALS AND METHODS OF RESEARCH

Experimental design called complete block design was used to design questionnaire served in data collection from randomly selected respondents. The application of this design is based on a simple data generating process which consists of identifying a set having multiple of three baskets. Based on previous studies related to agricultural innovations and Survey with resourceful persons, 24 agricultural innovations have been identified and included in this study. Thus, for each question, each respondent was asked to select his eight best and eight worst agricultural innovations. In total, 436 respondents were randomly selected and interviewed. Data were collected in both rural and urban areas of Tahoua State as a ways to diversify the sample. To determine the relative importance of each agricultural innovation, a BWS experiment design was employed. Table 1 was used to collect data from randomly selected farmers and herdsmen.

Table 1 - Listed below presents a sample of the questionnaire served in data collection

Eight (8) most important agricultural innovations Agricultural innovations included in the study Eight (8) least important agricultural innovations

✓ Rainfed rice cultivation

✓ Land recovering via tree planting

✓ Maradi red goat breeding

✓ Women's saving and credit scheme

✓ Honey harvesting via improved beehives

Use of millet glumes in cassava production

Cheese making ✓

Use of cassava for cattle fattening ✓

Processing peanuts into oil and cake ✓

Transforming Shea butter in soap

Use of annual and perennial crops for cattle fattening

Use of semi-modern irrigation system in gardening

✓ Transforming sorghum in couscous

✓ Manufacturing handicrafts with local perennial crops

Fertilization of land with household debris and waste ✓

Use of peanut cake for food conservation

Production and Marketing of gum Arabic ✓

Plantation of leguminous crops such Acacia spp

✓ Production and marketing of Moringa oleifera

Transforming cassava into bread flour

Use of early improved varieties of millet

Private development of rivers for rainfed rice cultivation ✓

Degraded land recovering and fertilization via organic manure ✓

Growing onions in sandy soil ✓

Source: List of most important agricultural innovations adopted from Saidou and Adam (2013) and used as tools for data collection.

We assumed that the BWS approach based on repeated choices between the most important and the least important agricultural innovations is consistent with random utility

theory, which is well rooted in the microeconomic theory. Thus, the utility function for various types of agricultural innovations can be mathematically expressed as follows:

Uij=pj-pk+£ij (1)

Where: Uij is the utility for person i facing agricultural innovations j, fy is the utility for person i selecting best agricultural innovations j, (3k is the disutility of per i selecting worst agricultural j and £tj is the stochastic term which is assumed to be normally distributed with mean zero and variance a}. The difference between fy and pk is assumed to be normally distributed with mean ^ and variance-covariance Q. The equation (1) is also assumed to mimic the underlying data generating process.

Alternatively, the relative importance can be mathematically written as follows:

Pi = M = » (2)

1 M 8N V '

Where: p is the weighted average for a given agricultural innovation, fy is the number of times that a given agricultural innovation was selected the best, W1 is the number of time that a given agricultural innovations was chosen as the worst, N is the sample size and eight (8) is the frequent of selecting a basket of agricultural innovations as best and worst. The standard deviation for various agricultural innovations was computed using information matrix denoted Q. For instance, the given standard deviation can be mathematically expressed as follows:

sn-jx-v (3)

Where: SDi denotes standard deviation for agricultural innovation i, Pi is the relative proportion or probability of a given agricultural innovations, (1-Pi) is the probability that innovation i is not selected and N is the sample size.

RESULTS AND DISCUSSION

This section summarizes information from data analysis. Tables 1 through 6 respectively report socioeconomic characteristics of surveyed farmers, farmers preferences for agricultural innovations, determinants of agricultural innovations and farmers' welfare estimates for agricultural innovations. Table 2 presents the socioeconomics characteristics of surveyed respondents.

Table 2 - Socioeconomic characteristics of surveyed respondents

Variables Definitions Mean SD

Age Age in numbers 30 10.000

Gender 1 for male, 0 otherwise 0.62 0.486

Marital status 1 for married, 0 for non married 0.67 0.470

Education 1 for educated, 0 otherwise 0.80 0.400

Annual income 1 if income between 51000 and 80000, 0 otherwise 0.26 0.250

1 if income greater than 80000, 0 otherwise 0.44 0.434

Annual expenses 1 if expenses between 26000 and 40000, 0 otherwise 0.13 0.083

1 if expenses greater than 40000, 0 otherwise 0.34 0.276

Food security 1 if yes food secured household, 0 for no 0.31 0.461

Family Size 1 for family size greater 7, for family size less than 7 0.47 0.500

Farm size (ha) 1 for farm size greater than 10 ha, 0 for less than 10 ha 0.31 0.461

Herd size (head) 1 for herd Size greater than 20, 0 for herd size less than 20 0.47 0.500

N 436

As reported in Table 2, most of respondents were male (62%), married (67%), educated (80%), and with an average age of 30 years. While majority of respondents (70%) had an annual income between 51000 to 80000 and above 80000, 53% of respondents were

planned to spend their income less than 26000 on agricultural innovations. Most of respondents (69%) would prefer to adopt agricultural innovations for reasons rather than food security. Finally, most of respondents had 53%, 69% and 53% respectively for family size less than 7 members, farm size less than 10 ha and herd size less than 20 heads.

Table 3 presents farmers preferences for agricultural innovations based on count-based estimates. As indicated in Table 3, coefficients with positive signs are considered as the most important, while coefficients with negative are considered as least important. Results show that rainfed rice cultivation, women's saving and credit scheme, honey harvesting via improved beehives, use of millet glumes in cassava production, Maradi red goat breeding, planting trees for land recovering, processing peanuts into oil and cake, use of semi-modern irrigation system in gardening, use of annual and perennial crops for cattle fattening, manufacturing handicrafts with local perennial crops and cheese making are positive and significant at 5% level, revealing that these agricultural innovations are the most important for farmers. This is consistent with a study on effect of zai and water conservation technique on water balance conducted in Niger shows that this system improves soil water status allowing plants to escape from dry spells, but leading to loss of nutrients such as nitrogen (Fatondji et al., 2011). Conversely, results indicate that coefficients of transforming cassava into bread flour followed by the use of early improved varieties of millet, private development of rivers for rainfed rice cultivation, degraded land recovering and fertilization via organic manure, planting of leguminous crops such Acacia spp and growing onions in sandy soil are negative and significant agricultural innovations, indicating that they are the least important agricultural innovations for farmers. Results reported respectively in Table 3 and Table 7 shows that count-based and multinomial logit estimation are similar, though multinomial logit estimates are higher in magnitude than count based estimates. Although estimates from both count- based and multinomial estimates being reported, only estimates from the former were presented and interpreted.

Table 3 - Farmers' Preferences for Agricultural innovations based on Best Worst Scaling

Agricultural Innovations identified and included in this study Best Worst Weight ± SD

Rainfed rice cultivation 165 73 0.038 ± 0.007a

Women's saving and credit scheme 132 78 0.025 ± 0.006a

Honey harvesting via improved beehives 136 96 0.017 ± 0.006a

Use of millet glumes in cassava production 136 96 0.015± 0.006a

Maradi red goat breeding 133 98 0.015 ± 0.006a

Planting trees for land recovering 123 91 0.014 ± 0.005a

Processing peanuts into oil and cake 110 79 0.013 ± 0.005a

Use of semi-modern irrigation system in gardening 125 100 0.012 ± 0.005a

Use of annual and perennial crops for cattle fattening 121 97 0.011 ± 0.005a

Manufacturing handicrafts with local perennial crops 120 99 0.010± 0.004a

Cheese making 109 92 0.007± 0.002a

Transforming shea butter in soap 106 95 0.003± 0.002

Use of peanut cake for food conservation 107 109 -0.002±0.002

Production and marketing of gum arabic 107 111 -0.003±0.003

Use of cassava for cattle fattening 85 95 -0.005±0.004

Fertilization of land with household debris and waste 99 112 -0.008±0.005

Transforming sorghum in couscous 79 104 -0.011 ±0.005

Production and marketing of Moringa oleifera 63 89 -0.013±0.006

Transforming cassava into bread flour 48 88 -0.018±0.007a

Use of early improved varieties of millet 66 108 -0.019±0.007a

Private development of rivers for rainfed rice cultivation 57 103 -0.020±0.007a

Degraded land recovering and fertilization via organic manure 69 123 -0.021 ±0.007a

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Planting of leguminous crops such Acacia species (spp) 70 125 -0.022 ±0.009a

Growing onions in sandy soil 56 140 -0.035±0.001a

N 436 -

Note: Weight ± SD stands for weighted average and standard deviation respectively. Numbers with letters are significantly different at 5% level. These agricultural innovations were first documented by Saidou and Adam (2013).

With regard to education, results show that educated farmers prefer rainfed rice cultivation and land recovering via tree planting as their best agricultural innovations,

whereas uneducated farmers prefer degraded land recovering and fertilization via organic manure. Table 4 reports determinants of agricultural innovations. Results presented in Table 4 report the determinants of agricultural innovations as function of gender, marital status, educational level and age.

With regard to gender, Table 4 shows those male header households prefer rainfed rice cultivation followed by land recovering via tree planting. Maradi red goat breeding, women's saving and credit scheme, honey harvesting via improved beehives and use of millet glumes in cassava production as their best agricultural innovations to be implemented; while female headed household would prefer to implement agricultural innovations such as transforming cassava into bread flour followed by the use of early improved varieties of millet, private development of rivers for rainfed rice cultivation, degraded land recovering and fertilization via organic manure, planting of leguminous crops such Acacia species and growing onions in sandy soil.

With respect to marital status, results reveal that married farmers would prefer to implement agricultural innovations such as rainfed rice cultivation, women's saving and credit scheme, honey harvesting via improved beehives, use of millet glumes in cassava production, Maradi red goat breeding, planting trees for land recovering, processing peanuts into oil and cake, use of semi-modern irrigation system in gardening, use of annual and perennial crops for cattle fattening, manufacturing handicrafts with local perennial crops and cheese making. In contrast, non married farmers would prefer to vote for production and marketing of gum arabic, use of cassava for cattle fattening, fertilization of land with household debris and waste, transforming sorghum in couscous, production and marketing of Moringa oleifera, transforming cassava into bread flour, use of early improved varieties of millet, private development of rivers for rainfed rice cultivation, degraded land recovering and fertilization via organic manure, planting of leguminous crops such Acacia spp and growing onions in sandy soil as their best agricultural innovations.

Table 4 - Influence of farmers' socioeconomic characteristics on agricultural innovations' preferences

n/n Male farmers Married Education Young

Agricultural innovations Weight ±SD Weight ±SD Weight ±SD Weight ±SD

Rainfed rice cultivation 0.036±0.011a 0.040±0.011a 0.039±0.017a 0.040±0.010a

Land recovering via tree planting 0.022±0.009a 0.023 ±0.009a 0.029±0.015a 0.030±0.009a

Maradi red goat breeding 0.021 ±0.009a 0.022 ±0.009a 0.028± 0.015 0.021 ±0.007a

Women's saving and credit scheme 0.020±0.008a 0.019 ±0.008a 0.022± 0.013 0.020±0.007a

Honey harvesting via improved beehives 0.017± 0.008a 0.017±0.008a 0.022± 0.013 0.018±0.007a

Use of millet glumes in cassava production 0.015±0.007a 0.015±0.007a 0.020± 0.013 0.015±0.006a

Cheese making 0.013±0.007 0.012 ±0.006a 0.017± 0.012 0.015±0.006a

Use of cassava for cattle fattening 0.012±0.006 0.012± 0.006 0.014±0.011 0.015±0.006a

Processing peanuts into oil and cake 0.005± 0.004 0.010 ±0.006 0.005±0.006 0.014±0.006a

Transforming shea butter in soap 0.003±0.003 0.006 ±0.004 0.005±0.006 0.014±0.006a

Use of annual and perennial crops for cattle fattening 0.002±0.003 0.003±0.003 0.004±0.006 0.004±0.003

Use of semi-modern irrigation system in gardening 0.002±0.003 0.000±0.001 0.004±0.006 0.004±0.003

Transforming sorghum in couscous 0.002±0.003 0.000 ±0.001 0.001 ±0.003 -0.002±0.002

Manufacturing handicrafts with local perennial crops -0.004±0.004 -0.003 ±0.003 0.001 ±0.003 -0.003±0.003

Fertilization of land with household debris and waste -0.005±0.004 -0.005 ±0.004 -0.003±0.005 -0.008±0.005

Use of peanut cake for food conservation -0.006±0.005 -0.005 ±0.004 -0.008± 0.008 -0.010±0.005

Production and marketing of gum arabic -0.012±0.007 -0.015 ±0.007a -0.009±0.009 -0.014±0.006a

Plantation of leguminous crops such acacia spp -0.015±0.007 -0.015 ±0.007a -0.012±0.010 -0.018±0.007a

Production and marketing of Moringa oleifera -0.015±0.008 -0.018±0.008a -0.022±0.014 -0.018±0.007a

Transforming cassava into bread flour -0.017 ±0.008a -0.020±0.008a -0.022 ± 0.014 -0.021 ±0.008a

Use of early improved varieties of millet -0.018 ±0.008a -0.020± 0.008a -0.026±0.015 -0.021 ±0.008a

Private development of rivers for rainfed rice cultivation -0.019± 0.008a -0.020 ±0.008a -0.031 ±0.016 -0.023±0.008a

Degraded land recovering and fertilization via organic manure -0.020 ± 0.009a -0.023± 0.009a -0.036±0.017a -0.027±0.009a

Growing onions in sandy soil -0.032± 0.011a -0.030±0.010a -0.043±0.019a -0.037±0.010a

N 271 291 124 371

Note: Weight ± SD stands for weighted mean and standard deviation, note that numbers with letters are significantly different at 5% level.

Finally, with regard to age, results show that coefficients of rainfed rice cultivation followed by land recovering via tree planting, Maradi red goat breeding, women's saving and credit scheme, honey harvesting via improved beehives, use of millet glumes in cassava production, cheese making, use of cassava for cattle fattening, processing peanuts into oil and cake and Transforming shea butter in soap were positive and significant, revealing that

young farmers prefer to implement these agricultural innovations. Conversely, coefficients of production and Marketing of gum arabic followed by plantation of leguminous crops such Acacia spp, gardening and marketing of Moringa oleifera, transforming cassava into bread flour, use of early improved varieties of millet, private development of rivers for rainfed rice cultivation, degraded land recovering and fertilization via organic manure and growing onions in sandy soil were negative and significant, showing that old farmers prefer to implement these agricultural innovations.

Table 5 reports influence of farm characteristics such as family size, farm size, herd size and food security information on farmers' agricultural innovations preferences. Results indicate that coefficients for rainfed rice cultivation, land recovering via tree planting, Maradi red goat breeding, women's saving and credit scheme and honey harvesting via improved beehives were positive and significant at 5%, implying that these agricultural innovations are the most important for large family size. However, coefficients of use of early improved varieties of millet followed by private development of rivers for rainfed rice cultivation, degraded land recovering and fertilization via organic manure and growing onions in sandy soil are the most important agricultural innovations for Small family size.

When food security information is provided, results show that rainfed rice cultivation, land recovering via tree planting, Maradi red goat breeding, Women's saving and credit scheme, honey harvesting via improved beehives and use of millet glumes in cassava production were the most important agricultural innovations to cope with food security. However, when food security information is not provided, results indicate that use of early improved varieties of millet followed by private development of rivers for rainfed rice cultivation, degraded land recovering and fertilization via organic manure growing onions in sandy soil as their most valuable agricultural innovations.

Table 5 also presents the influence of herd size on agricultural innovations adoption. Results show that farmers with large herd size prefer to adopt rainfed rice cultivation followed by land recovering via tree planting, Maradi red goat breeding, women's saving and credit scheme, honey harvesting via improved beehives as their best agricultural innovations. Results also reveal that farmers with small herd size prefer to implement private development of rivers for rainfed rice cultivation, degraded land recovering and fertilization via organic manure growing onions in sandy soil as their best agricultural innovations.

Table 5 - Influence of farm's characteristics on agricultural innovations' preferences

n/n Large family size Large farm size Food security Large livestock size

Agricultural innovations Weight ±SD Weight ±SD Weight ±SD Weight ±SD

Rainfed rice cultivation 0.034±0.013a 0.029±0.016 0.038±0.011a 0.048±0.015a

Land recovering via tree planting 0.028±0.012a 0.020±0.013 0.0200±0.008a 0.035±0.013a

Maradi red goat breeding 0.018±0.009a 0.019±0.013 0.020±0.008a 0.028±0.011a

Women's saving and credit scheme 0.018±0.009a 0.018±0.012 0.020±0.008a 0.023±0.011a

Honey harvesting via improved beehives 0.018±0.009a 0.015±0.012 0.019±0.008a 0.020±0.010a

Use of millet glumes in cassava production 0.016±0.009 0.013±0.011 0.015±0.007a 0.014±0.008

Cheese making 0.016±0.009 0.012±0.010 0.012±0.007 0.013±0.008

Use of cassava for cattle fattening 0.014±0.008 0.010±0.009 0.009±0.006 0.009±0.007

Processing peanuts into oil and cake 0.013±0.008 0.007±0.008 0.008±0.005 0.006±0.005

Transforming shea butter in soap 0.011 ±0.007 0.007±0.008 0.006±0.005 0.002±0.003

Use of annual and perennial crops for cattle fattening 0.010±0.007 0.004±0.006 0.003±0.003 0.001 ±0.002

Use of semi-modern irrigation system in gardening 0.000±0.000 0.003±0.005 0.002±0.003 0.001 ±0.002

Transforming sorghum in couscous -0.002±0.003 0.001 ±0.003 0.000±0.001 0.000±0.000

Manufacturing handicrafts with local perennial crops -0.002±0.003 -0.003±0.005 -0.001 ±0.002 -0.003±0.004

Fertilization of land with household debris and waste -0.010±0.007 -0.006±0.007 -0.006±0.005 -0.004±0.005

Use of peanut cake for food conservation -0.010±0.007 -0.007±0.008 -0.008±0.005 -0.005±0.005

Production and Marketing of gum arabic -0.011 ±0.007 -0.008±0.008 -0.009±0.006 -0.009±0.007

Plantation of leguminous crops such acacia spp -0.012±0.008 -0.010±0.009 -0.012±0.007 -0.014±0.008

Production and marketing of Moringa oleifera -0.013±0.008 -0.014±0.011 -0.014±0.007 -0.016±0.009

Transforming cassava into bread flour -0.016±0.009 -0.017±0.012 -0.014±0.007 -0.017±0.009

Use of early improved varieties of millet -0.021 ±0.010a -0.019±0.013 -0.015±0.008a -0.019±0.010

Private development of rivers for rainfed rice cultivation -0.022±0.011a -0.022±0.014 -0.020±0.009a -0.032±0.013a

Degraded land recovering and fertilization via organic manure -0.023±0.011a -0.023±0.015 -0.025±0.010a -0.036±0.013a

Growing onions in sandy soil -0.040±0.014a -0.034±0.018 -0.035±0.012a -0.048±0.016a

N 204 113 276 204

Table 6 represents various type values of agricultural innovations as function of farmers socioeconomic and farm characteristics. Results reveal that farmers place higher

value on income generating activities based agricultural innovations (0.645) followed by animal-based agricultural innovations(0.456), implying that farmers place higher values on income generating activities and animal-based agricultural innovations. Results indicate that farmers' value for animal-based agricultural innovations (0.456) is higher than those for crop-based agricultural innovations(-0.305), implying that hypothesis stating that crop-based agricultural innovations are higher than animal-based agricultural innovations was rejected and concluding that animal-based innovations are more welfare enhancing than crop-based innovations. Results also suggest that farmers' value for income based agricultural innovations (0.645) is higher than food science and nutrition based agricultural innovations (-0.032).

Table 6 - Values of agricultural innovations as function of farmers characteristics

Farmers' characteristics Crop- based Animal-based Food Science and nutrition Natural Resource management Income generating activities

Male -0.046 0.024 0.015 -0.004 0.004

Female -0.023 0.032 -0.036 -0.031 0.066

Married -0.049 0.015 0.007 0.004 0.002

Non married -0.030 0.030 -0.005 -0.062 0.046

Instruct -0.029 0.024 -0.029 0.018 0.042

Non instruct -0.011 0.037 0.015 -0.022 0.037

High income -0.011 -0.001 0.015 0.015 0.019

Medium income -0.015 0.012 0.023 -0.030 0.042

High expenses -0.021 0.101 -0.028 0.017 0.080

Medium expenses 0.031 0.022 -0.009 0.002 -0.057

Small family size -0.039 0.027 -0.016 0.013 0.048

Large family size -0.032 0.016 0.015 -0.045 0.085

Small farm size -0.018 0.015 -0.009 -0.005 0.048

Large farm size 0.008 0.062 0.006 -0.035 0.070

Small livestock size -0.009 0.047 -0.014 -0.005 0.038

Large livestock Size -0.009 -0.006 0.018 -0.025 0.078

Total -0.305 0.456 -0.032 -0.192 0.649

Table 7 - Farmers Preferences based Multinomial Estimates for Agricultural Innovations

Agricultural Innovations Mnl estimates

Rainfed rice cultivation 0.815* (0.099)

Land recovering via tree planting 0.526* (0.101)

Maradi red goat breeding 0.348* (0.094)

Women's saving and credit scheme 0.348* (0.094)

Honey harvesting via improved beehives 0.305* (0.094)

Use of millet glumes in cassava production 0.301* (0.098)

Cheese making 0.331* (0.104)

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Use of cassava for cattle fattening 0.223* (0.095)

Processing peanuts into oil and cake 0.221* (0.096)

Transforming shea butter in soap 0.192* (0.096)

Use of annual and perennial crops for cattle fattening 0.170* (0.100)

Use of semi-modern irrigation system in gardening 0.110* (0.100)

Transforming sorghum in couscous -0.019 (0.096)

Manufacturing handicrafts with local perennial crops -0.037 (0.096)

Fertilization of land with household debris and waste -0.111 (0.106)

Use of peanut cake for food conservation -0.123 (0.098)

Production and marketing of gum arabic -0.275 (0.106)

Plantation of leguminous crops such acacia spp -0.346* (0.116)

Production and marketing of Moringa oleifera -0.606* (0.127)

Transforming cassava into bread flour -0.492* (0.110)

Use of early improved varieties of millet -0.592* (0.117)

Private development of rivers for rainfed rice cultivation -0.578* (0.106)

Degraded land recovering and fertilization via organic manure -0.580* (0.106)

Growing onions in sandy soil -0.916* (0.112)

N 432

Note: Numbers in parentheses are standard errors, * stands for 5% level significance, Mnl stands for multinomial logit.

Results also suggest that exogenous agricultural innovations (0.034) are higher than endogenous (-0.001) and hybrid (-0.009) agricultural innovations, implying that exogenous innovations would enhancing farmers welfare. This shows that our research hypothesis

stating that income based agricultural innovations are higher than food science and nutrition based innovations was not rejected, revealing that income based innovations are more welfare enhancing. These results are not similar with a recent study stating that crop-based food values are higher than animal based food values (Amadou, 2021).

Table 8 - The most important agricultural Innovations identified and included in the study

Agricultural Innovations Descriptions

Rainfed rice cultivation It is an exogenous innovation introduced by a development project called JALDA in 2005

Planting trees for land recovering It is a hydrid innovation initiated by JALDA project in 2004

Use of cassava for cattle fattening It is an endogenous innovation developed by a 70-year-old farmer

Use of peanut cake for food conservation It is an endogenous innovation developed by a 55-year-old farmer

Women's saving and credit scheme It is an endogenous innovation started in 1992 by a group of 40 women

Maradi red goat breeding It is an endogenous innovation started by a cooperative called CERNAFA in 2010

Use of millet glumes and Piliostigma reticulata for cattle fattening It is an endogenous innovation aims at combining millet glumes and P. reticulata in 2007

Plantation of leguminous crops such Acacia spp It is an exogenous innovation started by Peace Corps in 1983

Manufacturing handicrafts with local perennial crops It is an endogenous innovation started in 1992

Use of millet glumes in cassava production It is an endogenous innovation developed by a 67-year-old farmer in 2006

Cheese making It is an endogenous innovation started by female cooperatives in 2000

Production and Marketing of Gum Arabic It is a hybrid innovation initiated by GESFORM in 2009

Transforming Shea butter in soap It is an exogenous innovation developed by CECI project in 2006

Honey harvesting via improved beehives It is an endogenous innovation started in 2008

Degraded land recovering and fertilization via organic manure It is a hybrid innovation developed by PROLINNOVA project in 1992

Transforming sorghum in couscous It is an endogenous innovation developed by a 44-year-old female in 2007

Fertilization of land with household waste It is an endogenous innovation developed by a 48-year-old farmer in 2010

Growing onions in sandy soil It is an endogenous innovation jointly developed by female farmers and a teacher in 2001

Private development of rivers for rainfed rice cultivation It is an endogenous innovation developed by local farmer in 2009

Transforming cassava into bread flour It is an endogenous innovation introduced by a 55-year-old farmer in 1973

Processing peanuts into oil and cake It is an endogenous innovation initiated by a 46-year-old farmer

Production and marketing of Moringa oleifera It is an endogenous innovation developed by a butcher that is not socially appreciated in 2008

Use of early improved varieties of millet It is an exogenous innovation introduced by development project in 2007

Use of semi-modern irrigation system in gardening It is an exogenous innovation introduced by Niger association of private Irrigation in 2007

Note: Agricultural innovations compiled and included in previous studies conducted by Saidou and Adam (2013).

Crop based agricultural innovations: Rainfed rice cultivation, use of millet glumes in cassava production, production and marketing of Moringa oleifera, use of millet glumes in cassava production, use of early improved varieties of millet, growing onions in sandy soil, use of semi-modern irrigation system in gardening and private development of rivers for rainfed rice cultivation.

Animal based agricultural innovations: Maradi red goat breeding, use of cassava for cattle fattening and use of annual and perennial crops for cattle fattening.

Food Science and nutrition based agricultural innovations: Cheese making, transforming sorghum in couscous, transforming cassava into bread flour, and use of peanut cake for food conservation.

Income generating activities based agricultural innovations: Honey harvesting via improved beehives, production and marketing of gum arabic, transforming shea butter in soap and women's saving and credit scheme.

CONCLUSION

Farmers and herdsmen are constantly operating within a vicious although endogenous, exogenous and hybrid innovations have been developed and diffused to address challenges such as climate change, covid-19, food security and poverty reduction. The objective of this paper is to assess farmers' value for agricultural innovations. While complete block design having 24 agricultural innovations was used to collect data from 436 farmers, the count-based method was used to analyze data. For each question, respondents were asked to choose his eight most important and his eight least important agricultural innovations. The difference between the most important and least important agricultural innovations is

assumed to be consistent with random utility theory, which is well rooted in microeconomic theory.

Results show that majority of respondents were married male with a formal education. Results suggest that farmers place higher value on agricultural innovations such as rainfed rice cultivation, women's saving and credit scheme, honey harvesting via improved beehives, use of millet glumes in cassava production, Maradi red goat breeding, planting trees for land recovering, processing peanuts into oil and cake, use of semi-modern irrigation system in gardening, use of annual and perennial crops for cattle fattening, manufacturing handicrafts with local perennial crops and cheese making, implying that agricultural extension worker should target and disseminate these technologies thereby boosting production and reducing food security.

Results also suggest that socioeconomics characteristics of farmers such male farmers versus female, married farmers versus non married farmers, educated versus non farmers and young and old farmers are key to disseminate agricultural innovations thereby managing efficiently and effectively these innovations. Results also reveal that farmers characteristics such as large versus small farm size, large versus small family size, food security information and large versus small livestock size greatly influence agricultural innovations amongst farmers.

Results also reveal that animal-based and income-based agricultural innovations should be targeted and reinforced to improve farmers' welfare. These findings may be useful as baseline information that can be used by extension agents to successfully implement agricultural innovations towards achieving sustainable development goals in the study area and beyond. Future direction for research is to study the stability of these agricultural innovations overtime in order to forecast demand indexes and develop a machine learning technique for urban and rural farmers.

REFERENCES

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