scholarly journals Effect of changes in population density and crop productivity on farm households in Malawi

2019 ◽  
Vol 50 (5) ◽  
pp. 615-628 ◽  
Author(s):  
Adam M. Komarek ◽  
Siwa Msangi
Keyword(s):  
Population Density ◽  
Crop Productivity ◽  
Farm Households ◽  
On Farm

scholarly journals Tackling G × E × M interactions to close on-farm yield-gaps: creating novel pathways for crop improvement by predicting contributions of genetics and management to crop productivity

2021 ◽  
Author(s):  
Mark Cooper ◽  
Kai P. Voss-Fels ◽  
Carlos D. Messina ◽  
Tom Tang ◽  
Graeme L. Hammer
Keyword(s):  
Climate Change ◽  
Crop Improvement ◽  
Target Population ◽  
Crop Productivity ◽  
Climate Change Scenarios ◽  
Global Food Security ◽  
Genotype By Environment ◽  
Improvement Strategies ◽  
Yield Gaps ◽  
On Farm

Abstract Key message Climate change and Genotype-by-Environment-by-Management interactions together challenge our strategies for crop improvement. Research to advance prediction methods for breeding and agronomy is opening new opportunities to tackle these challenges and overcome on-farm crop productivity yield-gaps through design of responsive crop improvement strategies. Abstract Genotype-by-Environment-by-Management (G × E × M) interactions underpin many aspects of crop productivity. An important question for crop improvement is “How can breeders and agronomists effectively explore the diverse opportunities within the high dimensionality of the complex G × E × M factorial to achieve sustainable improvements in crop productivity?” Whenever G × E × M interactions make important contributions to attainment of crop productivity, we should consider how to design crop improvement strategies that can explore the potential space of G × E × M possibilities, reveal the interesting Genotype–Management (G–M) technology opportunities for the Target Population of Environments (TPE), and enable the practical exploitation of the associated improved levels of crop productivity under on-farm conditions. Climate change adds additional layers of complexity and uncertainty to this challenge, by introducing directional changes in the environmental dimension of the G × E × M factorial. These directional changes have the potential to create further conditional changes in the contributions of the genetic and management dimensions to future crop productivity. Therefore, in the presence of G × E × M interactions and climate change, the challenge for both breeders and agronomists is to co-design new G–M technologies for a non-stationary TPE. Understanding these conditional changes in crop productivity through the relevant sciences for each dimension, Genotype, Environment, and Management, creates opportunities to predict novel G–M technology combinations suitable to achieve sustainable crop productivity and global food security targets for the likely climate change scenarios. Here we consider critical foundations required for any prediction framework that aims to move us from the current unprepared state of describing G × E × M outcomes to a future responsive state equipped to predict the crop productivity consequences of G–M technology combinations for the range of environmental conditions expected for a complex, non-stationary TPE under the influences of climate change.

Credit constraints and labour allocation decisions in rural Burkina Faso

2017 ◽  
Vol 77 (2) ◽  
pp. 257-274 ◽  
Author(s):  
Mohamed Porgo ◽  
John K.M. Kuwornu ◽  
Pam Zahonogo ◽  
John Baptist D. Jatoe ◽  
Irene S. Egyir
Keyword(s):  
Burkina Faso ◽  
Agricultural Production ◽  
Credit Constraints ◽  
Probit Model ◽  
Multinomial Logit Model ◽  
Farm Households ◽  
Content Type ◽  
Labour Market Participation ◽  
On Farm ◽  
Allocation Decisions

Purpose Credit is central in labour allocation decisions in smallholder agriculture in developing countries. The purpose of this paper is to analyse the effect of credit constraints on farm households’ labour allocation decisions in rural Burkina Faso. Design/methodology/approach The study used a direct elicitation approach of credit constraints and applied a farm household model to categorize households into four labour market participation regimes. A joint estimation of both the multinomial logit model and probit model was applied on survey data from Burkina Faso to assess the effect of credit constraint on the probability of choosing one of the four alternatives. Findings The results of the probit model showed that households’ endowment of livestock, access to news, and membership to an farmer-based organization were factors lowering the probability of being credit constrained in rural Burkina Faso. The multinomial logit model results showed that credit constraints negatively influenced the likelihood of a farm household to use hired labour in agricultural production and perhaps more importantly it induces farm households to hire out labour off farm. The results also showed that the other components of household characteristics and farm attributes are important factors determining the relative probability of selecting a particular labour market participation regime. Social implications Facilitating access to credit in rural Burkina Faso can encourage farm households to use hired labour in agricultural production and thereby positively impacting farm productivity and relieving unemployment pressures. Originality/value In order to identify the effect of credit constraints on farm households’ labour decisions, this study examined farm households’ decisions of hiring on-farm labour, supplying labour off-farm or simultaneously hiring on-farm labour and supplying family labour off-farm under credit constraints using the direct elicitation approach of credit constraints. To the best of the authors’ knowledge, this study is the first to examine this problem in Burkina Faso.

The rationale of part-time farming: empirical evidence from Norway

2017 ◽  
Vol 44 (1) ◽  
pp. 53-59 ◽  
Author(s):  
Klaus Mittenzwei ◽  
Stefan Mann
Keyword(s):  
Empirical Evidence ◽  
Household Income ◽  
Design Methodology ◽  
Farm Households ◽  
Apparent Contradiction ◽  
Content Type ◽  
Level Data ◽  
Part Time ◽  
On Farm ◽  
Practical Implications

Purpose Outside farming, pluriactivity is generally considered as undesirable, whereas agricultural economists tend to recommend part-time farming. This contradiction is to be solved. The paper aims to discuss this issue. Design/methodology/approach Linking tax-payer and statistical farm-level data from Norway, the authors tested how profitable part-time farming is for Norwegian farm households. Findings The analysis showed that concentrating on either working on-farm or off-farm generates a higher household income than combining the two. Practical implications Part-time farming may be a lifestyle decision, but apparently is not economically optimal for most farms. Originality/value The contribution solves an apparent contradiction between the discourses inside and outside agriculture.

scholarly journals Does Participation in Agricultural Cooperatives Affect Farm Sustainability? Empirical Evidence from Taiwan

2019 ◽  
Vol 11 (18) ◽  
pp. 4987 ◽  
Author(s):  
Bo Wang ◽  
Po-Yuan Cheng ◽  
Brian Lee ◽  
Lih-Chyun Sun ◽  
Hung-Hao Chang
Keyword(s):  
Farm Households ◽  
Agricultural Cooperatives ◽  
Food Labels ◽  
Potential Mechanism ◽  
Farm Production ◽  
Causal Mediation Analysis ◽  
Nationally Representative ◽  
Farm Sustainability ◽  
On Farm ◽  
The Impact

Recent research has highlighted the importance of agricultural cooperatives on farm production. Although the consensus from the literature suggests that participating in these organizations significantly affects farm production, there is inconclusive evidence on whether this effect is positive or negative. Moreover, previous studies solely focus on the magnitude of this effect and fail to explain the mechanism behind it. This study contributes to this knowledge gap by estimating the impact of agricultural cooperatives on farm profits. To do this, we apply the causal mediation analysis to explain the potential mechanism behind this relationship. Using a nationally representative survey of farm households from Taiwan in 2013, we find that participating in cooperatives increases farm profits. Furthermore, this effect is more pronounced for producers with higher profits. Concerning the mechanism, we find that the use of food labels accounts for approximately 15 to 28% of the total effect of cooperative participation on farm profits.

Economic impacts on farm households due to water reallocation in China's Chaobai watershed

2009 ◽  
Vol 96 (5) ◽  
pp. 883-891 ◽  
Author(s):  
Yuan Zhou ◽  
Yili Zhang ◽  
Karim C. Abbaspour ◽  
Hans-Joachim Mosler ◽  
Hong Yang
Keyword(s):  
Economic Impacts ◽  
Farm Households ◽  
On Farm

Participatory research in dryland cropping systems — monitoring and simulation of soil water and nitrogen in farmers' paddocks in Central Queensland

2004 ◽  
Vol 44 (3) ◽  
pp. 321 ◽  
Author(s):  
M. A. Foale ◽  
M. E. Probert ◽  
P. S. Carberry ◽  
D. Lack ◽  
S. Yeates ◽  
...  
Keyword(s):  
Soil Water ◽  
Service Providers ◽  
Production Systems ◽  
Cropping Systems ◽  
Management Strategies ◽  
Cropping System ◽  
Crop Productivity ◽  
Mineral Nitrogen ◽  
Soil Behaviour ◽  
On Farm

Collaboration of researchers and service-providers with farmers in addressing crop and soil management, using on-farm experiments and cropping system simulation, was negotiated in 2 districts in Central Queensland, Australia. The 2 most influential variables affecting crop productivity in this region (soil water and mineral nitrogen contents) and the growth of sown crops, were monitored and simulated for 3 years beginning in December 1992. Periodic soil sampling of large experimental strips on 3 farms, from paddocks that differed in cropping history and soil properties, provided robust datasets of change, over time, of soil water and mineral nitrogen status. Farmers participated in twice-yearly discussions with researchers, informed by the accumulating data, which influenced thinking about soil behaviour and possible new management strategies. As the study period coincided with a prolonged drought, so that cropping opportunities were few, the objectives of the work were modified to concentrate almost exclusively on the soil variables.The contribution of the Agricultural Production Systems Simulator, which was used to simulate the measured changes in soil water and mineral nitrogen, was found by all participants to be useful. The APSIM output generally demonstrated close correspondence with field observations, which raised confidence in its applicability to local cropping systems. Exploration of hypothetical situations of interest to farmer participants, in the form of what-if scenarios, provided insights into the behaviour of the production system for a range of soil and seasonal conditions. The informed speculation of the simulator became a substitute for the farmers' own, more tentative, efforts.The regular participative review sessions proved to be highly effective in stimulating the learning of both farmers and researchers. The farmers were able to feel comfortable as owners of the collaborative experiments and custodians of the learning environment. Clear evidence for the ongoing learning of these farmers appeared in post-collaboration practices and experiences.

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