Evaluation of Five Improved Maize Varieties for Intercropping with Sweet Potato in Makurdi, Southern Guinea Savanna Ecology of Nigeria

Idoko, J. A.; Akaazua, B.W; Oga, J. I.

doi:10.9734/arja/2018/40425

Cited by 10 publications

(10 citation statements)

References 7 publications

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“…Despite intercropping being a common practice in many cropping systems around the world, very few studies have examined the impacts of intercropping sweet potato from any perspective (Asiimwe et al, 2016;Idoko et al, 2018). Several studies have focused on yield potential under sweet potato maize relay cropping systems (Ewell and Mutuura,1991;Fischler and Wortmann, 1999;Mohammed, 2019), whereases others indicate that sweet potato can also be alley cropped between lines of agroforestry trees or shrubs, preferably fast-growing leguminous species with open crowns that allow the sunshine through (Rusoke et al, 2000;Schonbeck and Tillage, 2011).…”

Section: Introductionmentioning

confidence: 99%

GROWTH AND YIELD OF SWEET POTATO (Ipomoea batatas L.) MONOCROPS VERSUS INTERCROPS IN THE SEMI-ARID KATUMANI, KENYA

Mbayaki

Karuku

2021

Trop Subtrop Agroecosyst

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Background: Sweet potato producers in Kenya practice either sole cropping of or relay cropping and rarely do intercropping which aims at maximizing on time and space. Objective. To assess the relative performance of sweet potato under various cropping systems. Methodology: This study was conducted in Katumani, Kenya for two seasons; 2018/2019 and 2019/2020. The treatments comprised of sole cropping of Kabode, sole cropping of Bungoma, Kabode + common bean, Bungoma + common bean, and sole cropping of common beans (Mwezi mbili) were laid out in a randomized complete block design (RCBD) in 3 replications. Monocropped sweet potato and beans served as the control treatment. Weather data, leaf area, leaf area index, vine length, and percent canopy cover were collected throughout the cropping period. The data were analysed by a two-way ANOVA at 0.05% significance level followed by a Pearson’s correlation analysis on the extent to which length of vines, percent canopy cover, leaf area index, and weather parameters; ETo, aridity index, and rainfall influenced the attained tuber yields. Results: Intercropping significantly (p < 0.05) reduced sweet potato yields of Kabode and Bungoma varieties by 19.3% and 44%, respectively. Monocropped Kabode yielded 31.4 t ha-1, significantly (p< 0.05) higher than monocropped Bungoma with 23.9 t ha-1 whereas their common bean intercrops yielded 26.2 t ha-1 and 18.1 t ha-1,respectively. Correlation analysis showed that rainfall, ETo, LAI, vine length, and percent canopy cover negatively affected tuber yields. Implication: Land equivalent ratio revealed that intercropping sweet potato varieties with common beans was biologically efficient and that the percentage of the land saved averagely ranged from 8% to 33%. More studies should be conducted to determine the extent of sweet potato allelopathy on companion crops and nutrient use under intercropping systems. Conclusion: Yield stability analysis showed that orange-fleshed Kabode was the most stable variety across seasons to be grown in Katumani.

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Section: Introductionmentioning

confidence: 99%

GROWTH AND YIELD OF SWEET POTATO (Ipomoea batatas L.) MONOCROPS VERSUS INTERCROPS IN THE SEMI-ARID KATUMANI, KENYA

Mbayaki

Karuku

2021

Trop Subtrop Agroecosyst

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“…Here, the intercropped system showed the lowest competitive pressure, as indicated by high land equivalent ratios 1.78 and 1.75 in 2010 and 2011, respectively (Ijoyah and Dzer 2012). In Makurdi, all five improved maize varieties intercropped with sweet potato gave a Land Equivalent Ratio above 1.0 (Idoko et al 2018a) and a land equivalent coefficient above 0.25. See also the chapter about maize in intercrops (Adewopo Chapter 7).…”

Section: Intercroppingmentioning

confidence: 90%

Multifunctional Land Uses in Africa

Simelton¹,

Ostwald²

2019

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The multifunctional land use cases presented in this book reaffirm the urgent need to invest in diverse farming systems as we work to develop sustainable, productive, climate smart agricultural systems. More importantly, the research highlights the importance of considering the varying circumstances of vulnerable communities when devising interventions and actions.' Sithembile Ndema Mwamakamba, Food, Agriculture and Natural Resources Policy Analysis Network (FANRPAN) 'This case-study approach to shifting patterns of cultivation and multifunctional land use lends new insights into food security. From peri-urban agroforestry to watershed approaches to soil conservation, the book demonstrates the potential of both landowner initiated and state sponsored schemes to simultaneously improve ecosystem services and food provision.'

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“…Chief among these is the availability of high-quality data and the need for robust data infrastructure and analytics capabilities. Many farmers and agricultural organizations lack access to the necessary technology, expertise, and resources to collect, store, and analyze data effectively [27][28] . Addressing these challenges will require investment in data infrastructure, capacity-building initiatives, and partnerships between public and private stakeholders, machine learning holds tremendous promise for revolutionizing agriculture and addressing the complex challenges facing the global food system.…”

Section: Machine Learning and Predictive Modelingmentioning

confidence: 99%

Exploring big data innovations in food and agriculture research: An in-depth analysis

Doggalli,

Kulkarni,

Meti

et al. 2024

Int. J. Res. Agron.

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In recent years, the integration of big data technologies has revolutionized various industries, including food and agriculture. This article provides an in-depth analysis of the impact of big data innovations on research within the food and agriculture sector. It explores how big data analytics, IoT (Internet of Things), machine learning, and other advanced technologies are reshaping agricultural practices, and improving productivity, sustainability, and food security. Through case studies and examples, this article delves into the transformative potential of big data in addressing key challenges facing the global food system. Big data innovations have sparked a transformative wave in food and agriculture research, offering unprecedented opportunities to address pressing challenges and enhance sustainability. This article provides a comprehensive examination of the impact of big data technologies on agricultural practices, decision-making processes, and research methodologies. Through the integration of case studies and examples, it explores the role of big data analytics, IoT, and machine learning in optimizing crop management, predicting yield outcomes, and improving supply chain efficiency. The article also highlights key challenges and future directions for leveraging big data in agricultural research, emphasizing the importance of collaboration, investment, and capacity-building initiatives. Overall, it underscores the potential of big data to revolutionize food production systems and contribute to global food security and environmental sustainability.

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Evaluation of Five Improved Maize Varieties for Intercropping with Sweet Potato in Makurdi, Southern Guinea Savanna Ecology of Nigeria

Abstract: A field experiment was carried out during the cropping seasons of 2014 and 2015 at the Teaching and

Cited by 10 publications

References 7 publications

GROWTH AND YIELD OF SWEET POTATO (Ipomoea batatas L.) MONOCROPS VERSUS INTERCROPS IN THE SEMI-ARID KATUMANI, KENYA

GROWTH AND YIELD OF SWEET POTATO (Ipomoea batatas L.) MONOCROPS VERSUS INTERCROPS IN THE SEMI-ARID KATUMANI, KENYA

Multifunctional Land Uses in Africa

Exploring big data innovations in food and agriculture research: An in-depth analysis

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