scholarly journals Farmers’ Perceptions of Commercial Insect-Based Feed for Sustainable Livestock Production in Kenya

2021 ◽  
Vol 13 (10) ◽  
pp. 5359
Author(s):  
Afrika Onguko Okello ◽  
Jonathan Makau Nzuma ◽  
David Jakinda Otieno ◽  
Michael Kidoido ◽  
Chrysantus Mbi Tanga
Keyword(s):  
Food Systems ◽  
Large Scale ◽  
Principal Component ◽  
Farm Income ◽  
Purchase Decisions ◽  
Wealth Status ◽  
Feed Formulation ◽  
Alternative Protein ◽  
Livestock Products ◽  
The Impact

The utilization of insect-based feeds (IBF) as an alternative protein source is increasingly gaining momentum worldwide owing to recent concerns over the impact of food systems on the environment. However, its large-scale adoption will depend on farmers’ acceptance of its key qualities. This study evaluates farmer’s perceptions of commercial IBF products and assesses the factors that would influence its adoption. It employs principal component analysis (PCA) to develop perception indices that are subsequently used in multiple regression analysis of survey data collected from a sample of 310 farmers. Over 90% of the farmers were ready and willing to use IBF. The PCA identified feed performance, social acceptability of the use of insects in feed formulation, feed versatility and marketability of livestock products reared on IBF as the key attributes that would inform farmers’ purchase decisions. Awareness of IBF attributes, group membership, off-farm income, wealth status and education significantly influenced farmers’ perceptions of IBF. Interventions such as experimental demonstrations that increase farmers’ technical knowledge on the productivity of livestock fed on IBF are crucial to reducing farmers’ uncertainties towards acceptability of IBF. Public partnerships with resource-endowed farmers and farmer groups are recommended to improve knowledge sharing on IBF.

scholarly journals Large scale similarity search across digital reconstructions of neural morphology

2021 ◽  
Author(s):  
Bengt Ljungquist ◽  
Masood A Akram ◽  
Giorgio A Ascoli
Keyword(s):  
Similarity Search ◽  
Large Scale ◽  
Principal Component ◽  
Software Tool ◽  
Cell Types ◽  
Brain Regions ◽  
Morphological Comparison ◽  
Data Set ◽  
Qualitative Performance ◽  
The Impact

Most functions of the nervous system depend on neuronal and glial morphology. Continuous advances in microscopic imaging and tracing software have provided an increasingly abundant availability of 3D reconstructions of arborizing dendrites, axons, and processes, allowing their detailed study. However, efficient, large-scale methods to rank neural morphologies by similarity to an archetype are still lacking. Using the NeuroMorpho.Org database, we present a similarity search software enabling fast morphological comparison of hundreds of thousands of neural reconstructions from any species, brain regions, cell types, and preparation protocols. We compared the performance of different morphological measurements: 1) summary morphometrics calculated by L-Measure, 2) persistence vectors, a vectorized descriptor of branching structure, 3) the combination of the two. In all cases, we also investigated the impact of applying dimensionality reduction using principal component analysis (PCA). We assessed qualitative performance by gauging the ability to rank neurons in order of visual similarity. Moreover, we quantified information content by examining explained variance and benchmarked the ability to identify occasional duplicate reconstructions of the same specimen. The results indicate that combining summary morphometrics and persistence vectors with applied PCA provides an information rich characterization that enables efficient and precise comparison of neural morphology. The execution time scaled linearly with data set size, allowing seamless live searching through the entire NeuroMorpho.Org content in fractions of a second. We have deployed the similarity search function as an open-source online software tool both through a user-friendly graphical interface and as an API for programmatic access.

A Methodological Approach to Assess the Co-Behavior of Climate Processes over Southern Africa

2019 ◽  
Vol 32 (9) ◽  
pp. 2483-2495 ◽  
Author(s):  
Kwesi A. Quagraine ◽  
Bruce Hewitson ◽  
Christopher Jack ◽  
Izidine Pinto ◽  
Christopher Lennard
Keyword(s):  
Southern Africa ◽  
Large Scale ◽  
Southern Oscillation ◽  
Methodological Approach ◽  
Principal Component ◽  
Self Organizing Maps ◽  
Circulation Patterns ◽  
Climate Forcings ◽  
The Impact ◽  
Precipitation And Temperature

Abstract The study develops an approach to assess co-behavior of climate processes. The regional response of precipitation and temperature patterns over southern Africa to the combined roles (co-behavior) of El Niño–Southern Oscillation (ENSO), Antarctic Oscillation (AAO), and intertropical convergence zone (ITCZ) is evaluated. Self-organizing maps (SOMs) classify circulation patterns over the subcontinent, and principal component analysis (PCA) is used to identify related patterns across the data. The tropical rain belt index (TRBI), a measure of the ITCZ, is generally in phase with the AAO but mostly out of phase with ENSO. The phases of AAO may enhance or suppress ENSO impact on the location and distribution of regional precipitation and temperature over the region. This understanding of the co-behavior of large-scale processes is important to assess the impact these processes collectively have on precipitation and temperature, especially under future climate forcings.

scholarly journals Impact of Participation in Contract Farming on Smallholder Farmers’ Income and Food Security in Rural Benin: PSM and LATE Parameter Combined

2020 ◽  
Vol 12 (3) ◽  
pp. 901 ◽  
Author(s):  
Odountan Ambaliou Olounlade ◽  
Gu-Cheng Li ◽  
Sènakpon E. Haroll Kokoye ◽  
François Vihôdé Dossouhoui ◽  
Kuassi Auxence Aristide Akpa ◽  
...  
Keyword(s):  
Food Security ◽  
Food Consumption ◽  
Large Scale ◽  
Smallholder Farmers ◽  
Average Treatment Effect ◽  
Farm Income ◽  
Security Level ◽  
Negative Consequences ◽  
Contract Farming ◽  
The Impact

Investigated in this work is the impact of contract farming participation on smallholder farmers’ income and food security in rice crop production in Northern Benin using 400 randomly selected rice farmer households. Unlike previous studies, we corrected for both observed and unobserved biases by combining propensity score matching (PSM) and the local average treatment effect parameter (LATE). The results showed significant negative consequences of partaking in rice contract farming. We found evidence of significant negative effects on rice production income at a 1% level. The more the rice farmers join in contract farming, the lower the farm income became. Decreased food consumption was also a result of contract farming participation for potential participants by a score of 60.64, placing their households at the food security status level of poor food consumption because the quantity and nutritional quality of the food consumed were inadequate. Contract farming is, therefore, not a reasonable policy instrument that can help farmers increase their income and improve their food security level in the Alibori Department, Benin if farmers do not diversify their crops. The necessary resources and economic environment are not yet in place to allow contract farming to take full advantage of its potential benefits. To prevent the wasting of scarce public resources, expanding contract farming would not be appropriate in marginal areas with markets and other infrastructure. Additional measures are needed for contract farming to be profitable for contracting actors and to ensure sustainability and the large-scale participation of farmers.

Fault Localization Analysis for Multiple Fault Diagnosis in Multi-Station Assembly Systems

2007 ◽  
Author(s):  
Posheng Tsai ◽  
Kamal Mannar ◽  
Darek Ceglarek
Keyword(s):  
Manufacturing Systems ◽  
Large Scale ◽  
Fault Localization ◽  
Principal Component ◽  
Component Analysis ◽  
Fault Isolation ◽  
Data Driven ◽  
Multiple Fault ◽  
Critical Measure ◽  
The Impact

Modern large scale multi-station manufacturing systems require effective variation reduction to improve the final assembly dimensional quality. One critical measure is to diagnose the fault in the process using knowledge-based root cause identification, which can be very challenging due to the complexity of the system. The paper investigates the need of data-driven fault localization to enhance the diagnosability within the context of multiple-fault scenario(s) in multi-station assembly processes where multivariate measurements are used. The paper proposes three types of fault-signal transmission in assembly system and illustrates the nature of structured noise. Moreover, the impact of structured noise on the diagnosability is illustrated on two major fault isolation methods, namely, Principal Component Analysis and Independent Component Analysis. We then propose to use data-driven fault localization to reduce the structured noise effect and enhance the diagnosability. A simulation case study based on automotive panel assembly model is provided to illustrate the impact of structured noise and the need for data-driven localization.

scholarly journals How do farmland rental markets affect farmers’ income? Evidence from a matched renting-in and renting-out household survey in Northeast China

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0256590
Author(s):  
Ning Geng ◽  
Zhifeng Gao ◽  
Chuchu Sun ◽  
Mengyao Wang
Keyword(s):  
Land Reform ◽  
Large Scale ◽  
Household Survey ◽  
Scale Economy ◽  
Farm Income ◽  
Agricultural Cooperatives ◽  
System Reform ◽  
Rental Market ◽  
Rental Markets ◽  
The Impact

Promoting farmland transfer through the farmland rental market is an essential instrument to achieve the scale economy of agricultural production in China. However, past literature on the land reform in China pays more attention to the renting-in household or the renting-out household, respectively, less to both types of households together. Using a large-scale survey of farm households in China, we examine the determinants of participation in the farmland rental market and quantify the impact of the rental market on farmers’ income. Findings show household off-farm income, family members’ part-time employment, agricultural subsidies, and participation in agricultural cooperatives significantly affect farmers’ participation in the farmland rental market. Participation in the farmland rental market significantly increases the income of renting-in households, while it decreases the income of renting-out households, which might result from the temporary lag effect of the land system reform.

scholarly journals The Impact of dental wear on the analysis of morphological affinities based on dental non-metric traits

2021 ◽  
Vol 34 (2) ◽  
Author(s):  
Daniel Fidalgo ◽  
Veronica Wesolowski ◽  
Mark Hubbe
Keyword(s):  
Large Scale ◽  
Principal Component ◽  
Ordinal Scale ◽  
State University ◽  
Arizona State University ◽  
Dental Wear ◽  
Severe Wear ◽  
Morphological Studies ◽  
Individual Trait ◽  
The Impact

Dental wear is described as a limitation to dental morphological studies, as it obscures important crown trait features, resulting in significant differences on trait frequencies, an essential component for estimating biodistances. However, the actual impact of dental wear on biological distances still requires further characterization. We explore the impact of dental wear on morphological affinities for Brazilian pre-colonial series in the context of worldwide reference series. Twenty crown traits were scored using the Arizona State University Dental Anthropological System, and dental wear was quantified as an ordinal scale between 1 (no wear) and 8 (crown eroded). Seven crown trait frequencies are significantly associated with dental wear (p<0.05), demonstrating its impact on their analysis. To explore this impact on biodistances, data was divided by wear categories (all teeth, low-wear, moderate/severe wear) and morphological affinities among series was compared through Euclidean distances, Mean Measure of Divergence, and Principal Component Analysis. Results show the impact of wear is only meaningful when a sample contains many wear-biased traits with only moderate/severe wear. We conclude despite the impact of wear on individual trait frequencies, its impact on morphological affinities can be mitigated by including other variables or when comparisons focus only on large-scale biological differences.

scholarly journals Predicting social and health vulnerability to floods in Bangladesh

2021 ◽  
Vol 21 (6) ◽  
pp. 1807-1823
Author(s):  
Donghoon Lee ◽  
Hassan Ahmadul ◽  
Jonathan Patz ◽  
Paul Block
Keyword(s):  
Disaster Management ◽  
Large Scale ◽  
Management Practices ◽  
Principal Component ◽  
Social Health ◽  
Equal Weight ◽  
Coping Capacity ◽  
Health Vulnerability ◽  
And Coping ◽  
The Impact

Abstract. Floods are the most common and damaging natural disaster in Bangladesh, and the effects of floods on public health have increased significantly in recent decades, particularly among lower socioeconomic populations. Assessments of social vulnerability on flood-induced health outcomes typically focus on local to regional scales; a notable gap remains in comprehensive, large-scale assessments that may foster disaster management practices. In this study, socioeconomic, health, and coping capacity vulnerability and composite social-health vulnerability are assessed using both equal-weight and principal-component approaches using 26 indicators across Bangladesh. Results indicate that vulnerable zones exist in the northwest riverine areas, northeast floodplains, and southwest region, potentially affecting 42 million people (26 % of the total population). Subsequently, the vulnerability measures are linked to flood forecast and satellite inundation information to evaluate their potential for predicting actual flood impact indices (distress, damage, disruption, and health) based on the immense August 2017 flood event. Overall, the forecast-based equally weighted vulnerability measures perform best. Specifically, socioeconomic and coping capacity vulnerability measures strongly align with the distress, disruption, and health impact records observed. Additionally, the forecast-based composite social-health vulnerability index also correlates well with the impact indices, illustrating its utility in identifying predominantly vulnerable regions. These findings suggest the benefits and practicality of this approach to assess both thematic and comprehensive spatial vulnerabilities, with the potential to support targeted and coordinated public disaster management and health practices.

scholarly journals Sustainable Agricultural Practices, Farm Income and Food Security among Rural Households in Africa

2021 ◽  
Author(s):  
Abdul-Hanan Abdallah ◽  
Awal Abdul-Rahman ◽  
Gazali Issahaku
Keyword(s):  
Food Security ◽  
Food Systems ◽  
Treatment Effects ◽  
Rural Households ◽  
Agricultural Practices ◽  
Sub Saharan Africa ◽  
Farm Income ◽  
Welfare Benefits ◽  
Sustainable Agricultural Practices ◽  
The Impact

Abstract Sustainable agriculture has been recognized in the literature as one of the important pathways to ensuring food systems and livelihoods among rural households in Africa. Using data from the ‘Intensification of Food Crops Agriculture in Sub-Saharan Africa (Afrint)’ project, we examine the impact of adoption of multiple sustainable agricultural practices (SAPs) - zero-tillage, intercropping, residue incorporation and animal manure - on farm incomes and food security (captures as self-sufficiency in food production-SSF) among African rural households. Multinomial endogenous treatment effect (METE) method is applied to control potential selection bias. In addition, the multivalued treatment effects (MTE) model and dose-response-functions (DRFs) are also used to examine the treatment effects heterogeneity associated with SAPs adoption. The study reveals that joint adoption of SAPs is increased farm income and food security relative to the adoption of a single practice. Households obtain significantly higher farm income (FI) and food security (FS) via adoption of at least three practices relative to households adopting less than three practices. These findings reaffirm the benefits of adopting SAPs as a package rather than single practice, to enable farm households to derive significant welfare benefits.

scholarly journals Assessment of promising areas of digital livestock farming in the framework of "Agriculture 4.0"

2021 ◽  
Vol 7 (Special) ◽  
pp. 11-11
Author(s):  
Dmitry Istomin ◽  
◽  
Andrey Ivanov
Keyword(s):  
Food Systems ◽  
Large Scale ◽  
Agricultural Sector ◽  
Technology Development ◽  
Smallholder Farmers ◽  
Regulatory Requirements ◽  
Livestock Farming ◽  
Future Technology ◽  
Livestock Sector ◽  
The Impact

Digital innovation is increasingly being promoted as a practice that allows producers to tackle the challenges of reducing the impact of livestock on greenhouse gas emissions, meeting the growing needs of the population, and the welfare of animals and the environment. Today, digital technologies are being implemented in the livestock sector in different ways: automation technologies are popular among farmers, and not technologies for collecting or processing data for decision-making. There is a risk that, with a focus on the future, technology development will focus on livestock in corporate, large-scale industrial production and therefore will not address the barriers to integrated digital solutions development and access for smallholder farmers. If so, Agriculture 4.0 will play a more limited role in making food systems sustainable. Agriculture 4.0 developers must focus not only on developing the latest sensor or device, but on a more holistic perspective, including consideration of regulatory requirements, business model, recommendations and capacity development, to ensure implementation and ensure the sharing of the benefits of Agriculture 4.0 for all participants in the agricultural sector. Keywords: LIVESTOCK, DIGITAL AGRICULTURE, AGRICULTURE 4.0

scholarly journals Predicting social and health vulnerability to floods in Bangladesh

2020 ◽  
Author(s):  
Donghoon Lee ◽  
Hassan Ahmadul ◽  
Jonathan Patz ◽  
Paul Block
Keyword(s):  
Disaster Management ◽  
Large Scale ◽  
Management Practices ◽  
Principal Component ◽  
Social Health ◽  
Equal Weight ◽  
Coping Capacity ◽  
Health Vulnerability ◽  
And Coping ◽  
The Impact

Abstract. Floods are the most common and damaging natural disaster in Bangladesh, and the effects of floods on public health have increased significantly in recent decades, particularly among lower socio-economic populations. Assessments of social vulnerability on flood-induced health outcomes typically focus on local to regional scales; a notable gap remains in comprehensive, large-scale assessments that may foster disaster management practices. In this study, socio-economic, health, and coping capacity vulnerability and composite social-health vulnerability are assessed using both equal-weight and principal component approaches using 26 indicators across Bangladesh. Results indicate that vulnerable zones exist in the northwest riverine areas, northeast floodplains, and southwest region, potentially affecting 42 million people (26 % of total population). Subsequently, the vulnerability measures are linked to flood forecast and satellite inundation information to evaluate their potential for predicting actual flood impact indices (distress, damage, disruption, and health) based on the immense August 2017 flood event. Overall, the forecast-based equally weighted vulnerability measures perform best. Specifically, socio-economic and coping capacity vulnerability measures strongly align with the distress, disruption, and health impacts records observed. Additionally, the forecast-based composite social-health vulnerability index also correlates well with the impact indices, illustrating its utility in identifying predominantly vulnerable regions. These findings suggest the benefits and practicality of this approach to assess both thematic and comprehensive spatial vulnerabilities, with the potential to support targeted and coordinated public disaster management and health practices.

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