scholarly journals Automatic Section Control Technologies and GPS Auto-guidance Systems Adoption in Cotton Production

2018 ◽  
Vol 10 (7) ◽  
pp. 282 ◽  
Author(s):  
Brittani Edge ◽  
Margarita Velandia ◽  
Christopher Boyer ◽  
James Larson ◽  
Dayton Lambert ◽  
...  
Keyword(s):  
Precision Agriculture ◽  
Farm Size ◽  
Cotton Production ◽  
Probit Regression ◽  
Field Geometry ◽  
Production Practices ◽  
Cotton Farmers ◽  
Using Data ◽  
Control Technologies ◽  
Automatic Section Control

Using data from a survey of cotton producers in 14 US states, and a bivariate probit regression, this study examined the effects of the following measured parameters on the adoption of Automatic Section Control (ASC) technologies and GPS Auto-Guidance (AG) systems: age, education, farm size, field geometry, information sources, as well as the use of specific production practices and other Precision Agriculture (PA) technologies. Results suggest that younger, more educated producers, consulting farm dealers for information about PA technologies, using other PA technologies, and managing larger farming operations located in counties with more irregularly shaped fields are more likely to adopt ASC technologies and AG systems. Predicted adoption probabilities estimated using regression results suggest the use of other PA technologies and farm dealers as a source of precision farming information have the largest impact on the probability of adopting ASC by cotton farmers. Additionally, these results suggest farmers with operations in eastern Arkansas, western Tennessee, and a couple of counties in middle Tennessee are more likely to adopt ASC technologies. Producers in these regions had the highest percentages of users of other PA technologies and farm dealers to obtain PA information.

scholarly journals Factors influencing the adoption of improved vegetable production practices among women farmers in Aguata-Agricultural Zone, Anambra State, Nigeria

Agrosearch ◽  
2021 ◽  
Vol 20 (2) ◽  
pp. 67-81
Author(s):  
L.E. Odoemlam ◽  
F.C. Nzeakor
Keyword(s):  
New Technologies ◽  
Women Farmers ◽  
Farm Size ◽  
Farm Income ◽  
Vegetable Production ◽  
Probit Regression ◽  
Factors Influencing ◽  
Production Practices ◽  
Adoption Level ◽  
On Farm

The study examined the level and determinants of adoption of improved vegetable production practices in the study area. A three-stage sampling procedure was used in the selection of 160 respondents. A structured questionnaire was used for data collection. Data collected were analysed using descriptive statistics and Probit regression model. Results on adoption level of the selected improved vegetable production practices indicated that improved seeds had a grand mean of 𝑥̅ = 3.17, field preparation (𝑥̅ = 3.19), planting distance (𝑥̅ = 2.99), water management (𝑥̅ = 3.43), fertilizer/organic manure application (𝑥̅ = 3.55), pesticides (𝑥̅ = 2.57), harvesting ( 𝑥̅= 5.00) and storage procedure (𝑥̅ = 4.89) based on 5-point Likert scale adoption level. On factors influencing adoption of improved vegetable production practices, the result revealed that farm size (1.00188***), credit access (4.704902**), on-farm demonstration (2.900749**) and farm labour (1.295902***) had a positive and significant influence on improved vegetable production practices by the respondents. The result further indicated that the age (0.3135258***) and the off-farm income (0.0870768) of the farmers had a negative influence on the adoption of improved vegetable production practices. Based on these findings, the study revealed that the women farmers could have full adoption of the improved production practices if the factors are adequately addressed. The study therefore recommends that before the introduction of a new technology, the ADPs should ensure that maximum audience analysis is carried out to address some of the factors influencing adoption. Besides, introduction of new technologies to farmers should go hand-in-hand with on-farm demonstration since it is by that they would develop confidence and allay their fears associated with improved practices.

scholarly journals Determinants of technical efficiency in cotton production in the southern cotton growing zone of Nigeria: A stochastic production frontier approach

2019 ◽  
Vol 2 (02) ◽  
pp. 58-63
Author(s):  
MUYIWA SUNDAY OLATIDOYE ◽  
TAIWO ALIMI ◽  
ADEBAYO AKINBOYE AKINOLA
Keyword(s):  
Technical Efficiency ◽  
Stochastic Frontier ◽  
Chemical Properties ◽  
Sampling Technique ◽  
Descriptive Statistics ◽  
Farm Size ◽  
Primary Data ◽  
Cotton Production ◽  
Stochastic Production Frontier ◽  
Cotton Farmers

Abstract. Olatidoye MS, Alimi T, Akinola AA. 2018. Quality assessment of the physico-chemical properties of vermiwash produced from different sources during successive storage periods. Asian J Agric 2: 58-63. The study investigated on socio-economic factors and estimated the technical efficiency indices and factors influencing technical efficiency of the sampled cotton farmers in the Southern Cotton growing zone of Nigeria. A multistage sampling technique was employed to select a total sample of 300 cotton farmers. The study made use of only primary data which was collected through the aid of a well-structured questionnaire. The data were analyzed using descriptive statistics and stochastic frontier production parametric model. The results of the descriptive statistics showed that majority (83%) of the cotton farmers in the study area were males while the mean age of the respondents was 49 years. The average household size was 8 persons per household and majority (69%) of the respondents had formal education. Majority of the respondents (59%) had no access to credit facilities while majority (80.4%) of the cotton farmers had reasonable years of experience ranging between 11 and above in cotton production. Furthermore, the study found that the technical efficiency of the farmers range from 0.35 and 0.99 with a mean of 0.79. This indicates ample opportunity for farmers to increase their productivity through improvement in their technical efficiency. Seed, fertilizer, pesticides and farm size were found to be statistically significant and positively related to farmers’ output while education, credit, extension contact and farming experience of the respondents negatively influenced farmers’ technical inefficiency. The farmers therefore need to increase their output through more intensive use of seed, land, pesticides and fertilizers.

scholarly journals Economics of autonomous equipment for arable farms

2021 ◽  
Author(s):  
James Lowenberg-DeBoer ◽  
Kit Franklin ◽  
Karl Behrendt ◽  
Richard Godwin
Keyword(s):  
Precision Agriculture ◽  
Environmental Performance ◽  
Crop Production ◽  
Practical Experience ◽  
Production Costs ◽  
Farm Size ◽  
Medium Size ◽  
Economic Implications ◽  
The United Kingdom ◽  
Crop Agriculture

AbstractBy collecting more data at a higher resolution and by creating the capacity to implement detailed crop management, autonomous crop equipment has the potential to revolutionise precision agriculture (PA), but unless farmers find autonomous equipment profitable it is unlikely to be widely adopted. The objective of this study was to identify the potential economic implications of autonomous crop equipment for arable agriculture using a grain-oilseed farm in the United Kingdom as an example. The study is possible because the Hands Free Hectare (HFH) demonstration project at Harper Adams University has produced grain with autonomous equipment since 2017. That practical experience showed the technical feasibility of autonomous grain production and provides parameters for farm-level linear programming (LP) to estimate farm management opportunities when autonomous equipment is available. The study shows that arable crop production with autonomous equipment is technically and economically feasible, allowing medium size farms to approach minimum per unit production cost levels. The ability to achieve minimum production costs at relatively modest farm size means that the pressure to “get big or get out” will diminish. Costs of production that are internationally competitive will mean reduced need for government subsidies and greater independence for farmers. The ability of autonomous equipment to achieve minimum production costs even on small, irregularly shaped fields will improve environmental performance of crop agriculture by reducing pressure to remove hedges, fell infield trees and enlarge fields.

Do Foreign Remittances Matter in Attaining Zero Hunger?

2020 ◽  
pp. 197-215
Author(s):  
Oluwakemi Adeola Obayelu ◽  
Rebecca Funmi Akinmulewo
Keyword(s):  
Food Insecurity ◽  
Rural Households ◽  
Household Head ◽  
Farm Size ◽  
Living Standard ◽  
The North ◽  
Using Data ◽  
Zero Hunger ◽  
Female Headed Households ◽  
Food Insecurity Access

Foreign remittance has remained a major source of income and a means to reduce hunger for many poor people in developing countries. The contribution of foreign remittances to food insecurity status of rural households in Nigeria was assessed using data from 2015/2016 Living Standard Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA). Food insecurity status was achieved using the household food insecurity access scale. Data were analysed using descriptive, ordered, and nested logit models. Female-headed households residing in south-east zone with 51 to 70 years old heads and more than six members had greater access to remittances but were severely food insecure. Drivers of food insecurity were age, gender, marital status, education of the household head, membership of cooperatives, access to extension, farm size and per capita income, and living in the north central geo-political zone. Foreign remittances had a positive effect on the food insecurity status of rural households.

Wage-differentials and Their Determinants Across Industries in the Organized Manufacturing Sector of India

2020 ◽  
pp. 097215092091256
Author(s):  
Chandrima Ganguly ◽  
Joydeb Sasmal
Keyword(s):  
Wage Differentials ◽  
Manufacturing Sector ◽  
Wage Bargaining ◽  
Wage Determination ◽  
Farm Size ◽  
Total Employment ◽  
Annual Survey ◽  
Productivity Differentials ◽  
Specific Factors ◽  
Using Data

This article calculates the magnitude of wage differentials across industries in the organized manufacturing sector of India and identifies the major determinants of wage differentiation among the industries. Using data from Annual Survey of Industries in India for the period from 2000–2001 to 2015–2016, this study shows that mean wage is less in labour-intensive industries compared to the capital-intensive industries. The results of panel regression of annual average wage on various industry-specific factors show that productivity of labour is the most important factor in wage determination, and productivity largely depends on capital–labour ratio. The other significant factors in this regard are farm size, amount of profit and proportion of casual and female workers in total employment. Important policy implication of this study is that regulatory wage fixation and wage bargaining outcomes are not as significant as productivity differentials in explaining wage gaps across industries.

scholarly journals Internet Access and Internet Purchasing Patterns of Farm Households

2009 ◽  
Vol 38 (2) ◽  
pp. 240-257 ◽  
Author(s):  
Ashok K. Mishra ◽  
Robert P. Williams ◽  
Joshua D. Detre
Keyword(s):  
Durable Goods ◽  
Internet Access ◽  
Farm Households ◽  
Management Tool ◽  
Farm Size ◽  
The Internet ◽  
Farm Work ◽  
Regional Location ◽  
Using Data ◽  
Purchasing Patterns

The Internet is becoming an increasingly important management tool in production agriculture. Using data from the 2004 Agricultural Resource Management Survey (ARMS) and a double-hurdle estimation approach, we explore the adoption of computers with Internet access by and Internet purchasing patterns of farm households. Adoption of the Internet is positively related to age and education of the operator, off-farm work, presence of spouse, participation in government programs, farm size, and regional location of the farm. Internet purchasing patterns of farm households are positively related to the education of the operator and spouse, presence of teenagers, and regional location of the farm. Finally, farm businesses and their households are more likely to purchase a greater percentage of non-durable goods through the Internet as distances to markets increase.

scholarly journals Intensity of Precision Agriculture Technology Adoption by Cotton Producers

2011 ◽  
Vol 40 (1) ◽  
pp. 133-144 ◽  
Author(s):  
Kenneth W. Paxton ◽  
Ashok K. Mishra ◽  
Sachin Chintawar ◽  
Roland K. Roberts ◽  
James A. Larson ◽  
...  
Keyword(s):  
Precision Agriculture ◽  
Count Data ◽  
Estimation Procedure ◽  
Yield Variability ◽  
Logit Models ◽  
Factors Affecting ◽  
Level Data ◽  
Cotton Farmers ◽  
Data Estimation

Many studies on the adoption of precision technologies have generally used logit models to explain the adoption behavior of individuals. This study investigates factors affecting the intensity of precision agriculture technologies adopted by cotton farmers. Particular attention is given to the role of spatial yield variability on the number of precision farming technologies adopted, using a count data estimation procedure and farm-level data. Results indicate that farmers with more within-field yield variability adopted a higher number of precision agriculture technologies. Younger and better educated producers and the number of precision agriculture technologies used were significantly correlated. Finally, farmers using computers for management decisions also adopted a higher number of precision agriculture technologies.

Weed community structure in spring-seeded crops in Manitoba

1991 ◽  
Vol 71 (4) ◽  
pp. 1069-1080 ◽  
Author(s):  
A. G. Thomas ◽  
M. R. T. Dale
Keyword(s):  
Cluster Analysis ◽  
Community Structure ◽  
Weed Ecology ◽  
Analysis Techniques ◽  
Temperature And Precipitation ◽  
Weed Communities ◽  
Geographic Regions ◽  
Production Practices ◽  
Using Data ◽  
And Cluster Analysis

The phytosociological structure of weed communities in spring wheat, barley, oats, flax, and canola was investigated using data collected during a 3-yr survey of 1384 fields in Manitoba. Fields were surveyed during July and August, after the application of all herbicides. Association and cluster analysis techniques, using the presence or absence of species in a field, were employed to distinguish co-occurring groups of species. Only a small number of significant positive and negative associations were found between species and only minor clusters with a few species were formed at low similarity levels. These results indicated that the weed community was composed of species responding to conditions more or less independently of each other. A comparison of weed associations among the five crops and four geographic regions in the province indicated that the weed community structure was determined largely by climatic variables. The pattern of weed association in the four geographic regions was correlated with differences in temperature and precipitation during the spring and summer. The lack of floristic differentiation was attributed to the fact that production practices were similar for the five spring-seeded crops. Key words: Weed communities, weed ecology, cluster analysis, association analysis

scholarly journals Impact Assessment of the Cotton YIELD Programme in Zambia

2021 ◽  
Vol 11,12 (1-2) ◽  
Author(s):  
James Ngulube
Keyword(s):  
Farm Size ◽  
Double Difference ◽  
Extension Agents ◽  
Cotton Yield ◽  
Cross Section Data ◽  
Difference Model ◽  
Access To Credit ◽  
Section Data ◽  
Cotton Farmers ◽  
Crop Income

ABSTRACT This paper sought to evaluate the economic impact of the Cotton YIELD Programme on crop income of smallholder cotton farmers in Zambia. Specifically, the study sought to (a) identify factors that influence smallholder cotton farmer’ participation in the programme and (b) determine whether the Cotton YIELD Programme has increased the income of smallholder cotton farmers in Zambia. The study utilized pooled cross-section data of 300 cotton farmers, collected from two households survey (2005 and 2015) in Mumbwa district of Zambia. The Double Difference model combined with Propensity Score Matching methods were employed in the analysis. Results show that participation in the programme is positively driven by education, farm size, membership, access to credit, ownership of animal traction and media. However, distance to extension agents and market outlets negatively influence participation. Furthermore, the study found that the Cotton YIELD Programme has significantly increased crop income of smallholder cotton farmers by 38.1 percent.

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