Publication activity
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
Research across participating journals · All insights follow your collection filters.
Publication activity alongside incoming citations.
Articles grouped by publication year
Hover over a year or focus the chart and use arrow keys to inspect values.
2026 is year to date. 0 undated publications excluded.
OpenAlex · year of the citing work
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
Leading affiliations and themes in this collection.
Full distributions & methodology ↓Independent sources. Clear time scales.
Crossref and OpenAlex · separate totals for the same publication cohorts
Hover over a year or focus the chart and use arrow keys to inspect values.
Latest lifetime totals, grouped by the cited article’s year. These are not citations received in that year.
OpenAlex · incoming citation links grouped by citing-work year
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
Select journals to compare the same collection filters. Source totals stay separate. These measures describe research activity, not journal quality.
Articles by publication year
Latest lifetime totals · grouped by publication year
Latest lifetime totals · grouped by publication year
By year of the citing work · 2017–2026
2026 is year to date. Crossref and OpenAlex lifetime charts share a citation scale. Unknown observations appear as gaps; known zero stays zero. Annual receipts use available OpenAlex histories and may not sum to lifetime totals. 0 undated publications excluded from publication-year charts.
Crossref citation coverage: 4 / 4 publications (100.0%). Latest observation: 21 Oct 2026, 07:22 UTC. Means and percentages use records with known counts.
DOI-matched OpenAlex observations for the same selected publications. These counts are separate from Crossref and are never added together.
Observation range: 21 Oct 2026 07:22 UTC — 22 Oct 2026 18:19 UTC. Missing matches are not zero citations. Previous observations may remain if a refresh fails or a DOI no longer matches.
OpenAlex affiliations and primary-topic classification. Each publication counts once per institution or country; multi-affiliated publications appear in multiple groups, so percentages can sum above 100%. Countries describe author affiliations, not nationality. Topics use one primary topic per publication.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
4 / 4 with data · 0 missing or unmatched. Percentages use all 4 selected publications.
Citations are the latest recorded totals for articles published in each year, not citations received during that year. Crossref and OpenAlex remain separate and share the same citation scale. 2026 is incomplete; newer articles have had less time to receive citations.
0 undated publications excluded. Unknown citation counts are shown as —, never as zero. Partial coverage can understate totals; expand each table for known / total records.
| Publication year | Journal / scope | Publications | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2023 | All selected publications | 2 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | 0 | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 1 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | Crossref citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2023 | All selected publications | 7 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| Publication year | Journal / scope | OpenAlex citations | Publications | Crossref known | OpenAlex known |
|---|---|---|---|---|---|
| 2023 | All selected publications | 7 | 2 | 2/2 | 2/2 |
| 2024 | All selected publications | — | 0 | 0/0 | 0/0 |
| 2025 | All selected publications | 0 | 1 | 1/1 | 1/1 |
| 2026 | All selected publications | 0 | 1 | 1/1 | 1/1 |
Incoming citations to the selected publications, grouped by the year of the citing work. This is separate from lifetime citation totals grouped by the cited article’s publication year.
The publication filters above define which articles receive the citations. The citation-year range below only controls this chart and the incoming-citation comparison. Removing publication-year filters includes older articles’ incoming citations too.
Annual history available for 4 / 4 selected publications. Supported display window: 2017–2026; 2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Missing histories and years beyond a saved observation’s window remain unknown (—); partial coverage can understate totals.
Annual-history observations (UTC): 2026-10-21T07:22:46.740761+00:00 — 2026-10-22T18:19:25.396765+00:00. Older observations may be retained after failed or incomplete refreshes.
| Citation year | Journal / scope | OpenAlex · Citations received by year | Publications | Annual history known |
|---|---|---|---|---|
| 2017 | All selected publications | 0 | 4 | 4/4 |
| 2018 | All selected publications | 0 | 4 | 4/4 |
| 2019 | All selected publications | 0 | 4 | 4/4 |
| 2020 | All selected publications | 0 | 4 | 4/4 |
| 2021 | All selected publications | 0 | 4 | 4/4 |
| 2022 | All selected publications | 0 | 4 | 4/4 |
| 2023 | All selected publications | 1 | 4 | 4/4 |
| 2024 | All selected publications | 2 | 4 | 4/4 |
| 2025 | All selected publications | 3 | 4 | 4/4 |
| 2026 | All selected publications | 1 | 4 | 4/4 |
Counts represent citation links, not unique citing papers across a journal: one paper citing two selected articles contributes two links. Older citations outside this window are excluded, so annual sums need not equal lifetime totals. OpenAlex methodology ↗
Records with full publication dates only. 2026 is an incomplete year.
| Period | Publications |
|---|---|
| 2023-03 | 1 |
| 2023-10 | 1 |
| 2025-12 | 1 |
| 2026-07 | 1 |
Latest Crossref totals for the selected publications; not citations received in the selected years.
Unknown counts are excluded from the mean, median and cited-publication rate.
Same filters, source and counting rules across journals. Descriptive statistics, not a quality ranking.
| Journal / publisher | Publications | Crossref citations | OpenAlex citations | OpenAlex coverage | Crossref mean | Crossref median | Crossref cited %* | Crossref coverage |
|---|---|---|---|---|---|---|---|---|
| International Journal of Business Ecosystem & Strategy Bussecon International Academy | 1 | 0 | 0 | 1/1 | 0.0 | 0 | 0.0 | 1/1 · 100.0% |
| International Journal of Research in Business and Social Science SSBFNET | 3 | 7 | 7 | 3/3 | 2.33 | 2 | 66.7 | 3/3 · 100.0% |
* Percentage among publications with a known citation count.
The primary aim of this scholarly discourse is to demonstrate how South African indigenous people advanced agricultural practices without the dominant aid of globalisation and modernity that, to a certain degree, discredits Indigenous Knowledge Systems (IKS) that have existed from time immemorial. Qualitative research inquiry and IKS are synergetically used as approaches to this scholarly discourse to form juxtaposition and triangulation – a balancing act. The main discussions and findings of the article underline that incontrovertibly, South African indigenous people had their traditional ways of advancing human and social life such as relying on traditional medicine, farming, harvesting and many other determinants. In respect of the problematised phenomenon, the conclusion infuses recommendations for future scholarly debates while the emphasis is on embracing traditional knowledge and avoid continuous and solitary accreditation of neo-liberalist and imperialist notions in South Africa and elsewhere.
Indigenous knowledge (IK) plays a crucial role in rural African communities by contributing to the development of mitigation and adaptation strategies, enhancing resilience to climate-related challenges. However, there is limited documentation of its application in South Africa. This study investigates the adoption of IK in the Vhembe district, focusing on general use, disease prediction and farming practices. Results indicate that the respondents possessed a rich reservoir of IK, with 76.1% affirming its use for different purposes. Most respondents (75.3%) use IK for farming, with 63.1% using it for disease prediction. Most participants (74.3%) reported adequate confidence levels in their use of IK for general purposes. Respondents who had stayed longer in Vhembe reported higher confidence levels in using IK, as did those above 66 years old in using this knowledge system for disease prediction. The use of IK indicators for early warning of malaria outbreaks was also documented. Investigating and documenting IK use in communities could inform the basis for preservation and hence, enhance IK recognition. The integration of IK in the development of early warning systems may enhance their relevance and effectiveness in combating the effects of climate change and infectious diseases.
The nexus of Artificial Intelligence (AI) and indigenous knowledge systems (IKS) rarely features as a viable intervention in African food system policy and academic debates. This has created knowledge and practical gaps with policy and practice implications. This article argues that leveraging the AI-IKS nexus has significant potential to transform African food systems currently in crisis. This conceptual article explores the importance of IKS in Sub-Saharan Africa (SSA) and examines how AI solutions can transform regional food systems. The article shows that harnessing the AI-IKS nexus entails merging traditional, generational ecological wisdom with modern technology to enhance food security, sustainability, and resilience. Key applications include using AI to analyse indigenous drought-prediction techniques alongside meteorological data, identifying climate-resilient indigenous crops, and deploying Computer Vision and Natural Language Processing to digitise and disseminate traditional knowledge in local languages. The article argues that this synergy has the potential to enhance climate resilience, boost yields through precision agriculture, reduce post-harvest losses, and promote sustainable resource management, ultimately strengthening food security.
Small-scale farmers in South Africa, particularly in Indigenous communities, continue to heavily rely on artificial farming, overlooking Indigenous agricultural knowledge. The key influence behind this is that the artificial farming practices have become more accessible than the Indigenous agricultural knowledge. This paper is aimed at understanding the economic viability of the Indigenous liquified manure for small-scale farmers while promoting the sustainable Indigenous agriculture within Indigenous communities. The paper is centred on addressing poor agricultural practice of the Indigenous liquified manure in establishing indigenous agriculture knowledge culture in rural communities in Vuwani. A sample of 18 participants consisting of 13 small-scale indigenous farmers, 3 traditional leaders, and 2 agricultural experts were drawn using purposive sampling from Vuwani rural communities. The qualitative semi-structured interviews and focus group discussions were employed for data collection and analysed using thematic analysis. The study unveiled that the Indigenous liquified manure contributes to the high produce of the indigenous crops that enables the Indigenous communities to economically sustain themselves. The findings further show that the practice of the Indigenous liquified manure is understood as an entrepreneurial opportunity to create job opportunities in the Vuwani.
The nexus of Artificial Intelligence (AI) and indigenous knowledge systems (IKS) rarely features as a viable intervention in African food system policy and academic debates. This has created knowledge and practical gaps with policy and practice implications. This article argues that leveraging the AI-IKS nexus has significant potential to transform African food systems currently in crisis. This conceptual article explores the importance of IKS in Sub-Saharan Africa (SSA) and examines how AI solutions can transform regional food systems. The article shows that harnessing the AI-IKS nexus entails merging traditional, generational ecological wisdom with modern technology to enhance food security, sustainability, and resilience. Key applications include using AI to analyse indigenous drought-prediction techniques alongside meteorological data, identifying climate-resilient indigenous crops, and deploying Computer Vision and Natural Language Processing to digitise and disseminate traditional knowledge in local languages. The article argues that this synergy has the potential to enhance climate resilience, boost yields through precision agriculture, reduce post-harvest losses, and promote sustainable resource management, ultimately strengthening food security.
Small-scale farmers in South Africa, particularly in Indigenous communities, continue to heavily rely on artificial farming, overlooking Indigenous agricultural knowledge. The key influence behind this is that the artificial farming practices have become more accessible than the Indigenous agricultural knowledge. This paper is aimed at understanding the economic viability of the Indigenous liquified manure for small-scale farmers while promoting the sustainable Indigenous agriculture within Indigenous communities. The paper is centred on addressing poor agricultural practice of the Indigenous liquified manure in establishing indigenous agriculture knowledge culture in rural communities in Vuwani. A sample of 18 participants consisting of 13 small-scale indigenous farmers, 3 traditional leaders, and 2 agricultural experts were drawn using purposive sampling from Vuwani rural communities. The qualitative semi-structured interviews and focus group discussions were employed for data collection and analysed using thematic analysis. The study unveiled that the Indigenous liquified manure contributes to the high produce of the indigenous crops that enables the Indigenous communities to economically sustain themselves. The findings further show that the practice of the Indigenous liquified manure is understood as an entrepreneurial opportunity to create job opportunities in the Vuwani.
Indigenous knowledge (IK) plays a crucial role in rural African communities by contributing to the development of mitigation and adaptation strategies, enhancing resilience to climate-related challenges. However, there is limited documentation of its application in South Africa. This study investigates the adoption of IK in the Vhembe district, focusing on general use, disease prediction and farming practices. Results indicate that the respondents possessed a rich reservoir of IK, with 76.1% affirming its use for different purposes. Most respondents (75.3%) use IK for farming, with 63.1% using it for disease prediction. Most participants (74.3%) reported adequate confidence levels in their use of IK for general purposes. Respondents who had stayed longer in Vhembe reported higher confidence levels in using IK, as did those above 66 years old in using this knowledge system for disease prediction. The use of IK indicators for early warning of malaria outbreaks was also documented. Investigating and documenting IK use in communities could inform the basis for preservation and hence, enhance IK recognition. The integration of IK in the development of early warning systems may enhance their relevance and effectiveness in combating the effects of climate change and infectious diseases.
The primary aim of this scholarly discourse is to demonstrate how South African indigenous people advanced agricultural practices without the dominant aid of globalisation and modernity that, to a certain degree, discredits Indigenous Knowledge Systems (IKS) that have existed from time immemorial. Qualitative research inquiry and IKS are synergetically used as approaches to this scholarly discourse to form juxtaposition and triangulation – a balancing act. The main discussions and findings of the article underline that incontrovertibly, South African indigenous people had their traditional ways of advancing human and social life such as relying on traditional medicine, farming, harvesting and many other determinants. In respect of the problematised phenomenon, the conclusion infuses recommendations for future scholarly debates while the emphasis is on embracing traditional knowledge and avoid continuous and solitary accreditation of neo-liberalist and imperialist notions in South Africa and elsewhere.
Source coverage refers to this result set; a publication may occur in several sources. Sync times refer to contributing journals.
Missing abstracts: 0 · Missing authors: 0 · Missing publication dates: 0 · Dates without day precision: 0
| Source | Most recent successful journal sync | Latest attempt |
|---|---|---|
| crossref | 21 Oct 2026 07:22 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |
| ojs-rest | 21 Oct 2026 07:22 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 06:46 UTC |
| oai-pmh | 20 Oct 2026 19:55 UTC · ijrbs | complete · ijrbs · 20 Oct 2026 19:50 UTC |
| openalex-enrichment | 21 Oct 2026 07:23 UTC · ijrbs | complete · ijrbs · 21 Oct 2026 07:22 UTC |