DATAD-R
Database of African Theses and Dissertations - Research (DATAD-R):
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- All the scholarship emanating from the ACE for Impact project
Recent Submissions
Adapting the QUEFTS model to predict attainable yields when training data are characterized by imperfect management
(Field Crops Research, 2021-03-31) Ravensbergen, Arie Pieter Paulus; Chamberlin, Jordan
Understanding yield responses to nutrient application is a key input for extension advice and strategic agricultural investments in developing countries. A commonly used model for yield responses to nutrient inputs in
tropical smallholder farming systems is QUEFTS (QUantitative Evaluation of the Fertility of Tropical Soils).
While QUEFTS has a strong conceptual foundation, a key assumption is that nutrients are the only limiting
factors. One implication of this is the required assumption of ‘perfect management’. This may be problematic in
the application of QUEFTS in smallholder farming systems with a wide variety of yield limiting factors.
In a previous study, QUEFTS was calibrated using farm trials in two major maize production zones in Nigeria.
To reduce observed variability in correlations between estimated soil nutrient (N, P, K) supply and soil parameters (e.g. soil organic carbon, soil pH; step 1 of QUEFTS) a Mahalanobis distance method was used to remove
data points not adhering to expected correlations. In this study, we assessed an alternative approach: can the
QUEFTS model be adapted to fit smallholder farming systems and associated variation in management? Using
676 observations from the same nutrient omission trials in two major maize production zones in Nigeria, we
compare a standard linear regression approach with a quantile regression approach to calibrate QUEFTS.
We find that under the standard linear regression approach, there is a poor relation between predicted and
observed yields. Using quantile regression, however, QUEFTS performed better at predicting attainable yields –
defined as the 90th percentile of observed yields – under a wide variety of production conditions. Our results
indicate that using quantile regression as a way to predict attainable yields, is a useful alternative implementation of QUEFTS in smallholder farming systems with high variability in management and other
characteristics.
Investigating the effect of in vitro gastrointestinal digestion on the stability, bioaccessibility, and biological activities of baobab (Adansonia digitata) fruit polyphenolics
(LWT, 2021) Ismail, Balarabe B.; Guo, Mingming; Pu, Yunfeng
Baobab (Adansonia digitata) fruit had received growing attention for its myriad nutritional and medicinal benefits, including those from its polyphenol-rich profile and powerful antioxidant activity. The current study evaluated the bioaccessibility of phenolic constituents and antioxidant capacity of baobab fruit pulp (BFP) and its byproduct, the baobab fruit shell (BFS), upon in vitro digestion. In general, the in vitro digestion reduced phenolic contents and antioxidant capacity; however, several flavonoids, particularly quercetin, proanthocyanidin, proanthocyanidins B1 and B2 were highly bioaccessible. Specifically, a significant increase in the bioaccessibility of proanthocyanidins (173%) in BFS was observed following gastric digestion, possibly due to hydrolysis of proanthocyanidin isomers. Moreover, a significantly higher bioaccessibility of proanthocyanidin B2 (170%) and quercetin (304%) in BFP, and proanthocyanidin (363%) in BFS was also observed following intestinal digestion probably due to pancreatin effect on the complex food matrix or the depolymerisation of insoluble proanthocyanidin and quercetin conjugates induced by the increase in pH. A considerable α-amylase and α-glucosidase inhibition in all samples (>50% inhibition) were observed following the in vitro digestion. Hence, both BFP and BFS are good sources of bio accessible polyphenolics that could be utilised as ingredients in functional foods.
Increasing temperature elevates the variation and spatial differentiation of pesticide tolerance in a plant pathogen
(Evolutionary Applications, 2021-01-13) Lurwanu, Yahuza; Wang, Yan-Ping; Wu, E-Jiao
,Climate change and pesticide resistance are two of the most imminent challenges
human society is facing today. Knowledge of how the evolution of pesticide resistance may be affected by climate change such as increasing air temperature on the
planet is important for agricultural production and ecological sustainability in the
future but is lack in scientific literatures reported from empirical research. Here,
we used the azoxystrobin-Phytophthora infestans interaction in agricultural systems
to investigate the contributions of environmental temperature to the evolution of
pesticide resistance and infer the impacts of global warming on pesticide efficacy
and future agricultural production and ecological sustainability. We achieved this
by comparing azoxystrobin sensitivity of 180 P. infestans isolates sampled from nine
geographic locations in China under five temperature schemes ranging from 13 to
25°C. We found that local air temperature contributed greatly to the difference of
azoxystrobin tolerance among geographic populations of the pathogen. Both amongpopulation and within-population variations in azoxystrobin tolerance increased as
experimental temperatures increased. We also found that isolates with higher azoxystrobin tolerance adapted to a broader thermal niche. These results suggest that
global warming may enhance the risk of developing pesticide resistance in plant pathogens and highlight the increased challenges of administering pesticides for effective management of plant diseases to support agricultural production and ecological
sustainability under future thermal conditions.
Evaluation of Traits’ Performance Contributing to Drought Tolerance in Sorghum
(Agronomy, 2021-08-26) Mwamahonje, Andekelile; Eleblu, John Saviour Yaw; Ofori, Kwadwo
: Sorghum (Sorghum bicolor [L.] Moench) is an important food crop for people in semi-arid
Africa. The crop is affected by post-flowering drought; therefore, the study was conducted to screen
traits contributing to drought tolerance using BC2F4 sorghum genotypes in stressed and unstressed
water conditions in a split-plot design. Water stress (0 mm/day) was applied at post-flowering to
plant maturity in water-stressed treatment. The genotype SE438 produced the highest grain yield
(2.65 ton ha−1
) in water-stressed environment and NA316C yielded highest (3.42 ton ha−1
) under well-watered (7 mm/day) environment. There were significant differences of most traits evaluated at
p < 0.01 across environments. The mean squares of traits for genotypes by environments revealed
interactions at p < 0.05 and p < 0.01. The indices geometric mean productivity (GMP) and mean
productivity (MP) were highly correlated with yield under well-watered (YP) and water-stressed
condition (YS) and each other. The first principal axis (PC1) explained 59.1% of the total variation.
It is the best indicator of yield potential and drought tolerance of sorghum genotypes in this study.
Therefore, further improvement is needed to strengthen drought tolerance and yield in sorghum.
Production and Quality Evaluation of Cookies from Wheat, Almond Seed and Carrot Flour Blends
(International Journal of Food Science and Biotechnology, 2020-10-30) Guyih, Mulak Desmond; Dinnah, Ahure; Eke, Mike Ojotu
Cookies are a form of baked food which is usually sweet. Wheat, almond and carrot flours were used to produce
cookies in the following blend ratios: 100:0:0, 90:10:0, 90:0:10, 80:15:5, 70:20:10 and were labeled A, B, C, D and E. The
control sample A was without treatment. Analyses of antinutrients, functional properties, physical, proximate, minerals, and
sensory attributes were carried out using standard methods. All the results show statistical difference. The functional properties
of flours: bulk density, WAC, OAC, swelling capacity and foaming capacity ranged respectively from 0.71 to 0.81 g/cm3
, 1.60
to 4.31 g/mL, 1.10 to 3.67 g/L, 2.30 to 2.66 mL, 5.10 to 6.62%. The antinutritional properties: oxalate, tannin and cyanide
content of flours ranged from 0.03 to 0.14 mg/100g, 0.18 to 0.64%, 0.12 to 0.13%, phytate content was not detected. The
spread ratio of cookies ranged from 3.32 in sample A to 4.04 in sample E. The proximate composition of cookies: moisture,
ash, fiber, fat, protein and carbohydrate content ranged respectively: from 6.42 to 8.04%, 1.62 to 2.72%, 0.36 to 0.97%, 1.94 to
6.02%, 6.14 to 10.23% and 71.27 to 81.18%. The energy value of cookies ranged from 371.22 to 391 kCal. The mineral
composition ranged from 185.77 to 230.16 mg/100g for calcium, 877.62 to 984 mg/100g for potassium, 5.75 to 7.12 mg/100g
for zinc, 58.96 mg/100g to 77.16 mg/100g for magnesium and 47.03 to 56.12 for sodium. All cookies samples were generally
accepted by sensory panelist. The study provides evidence that wheat, almond and carrot are suitable for cookies production
and at optimal substitution levels of 70:20:10 and 80:20:10.
Non-Wettable Surfaces – From Natural to Artificial and Applications: A Critical Review
(Rev. Adhesion Adhesives,, 2019) Tyowua, Andrew Terhemen; Targema, Msugh; Emmanuel Etim Ubuo, Emmanuel Etim
Non-wettable surfaces have recently attracted significant attention due to
their enormous promising applications. These applications are primarily
due to their ability to repel liquid drops and remain unwetted. In this
review, the various names used in describing non-wettable surfaces are
given. This is followed by the fundamental theories of wetting. Natural
non-wettable surfaces are then considered, along with their importance.
Thereafter, we discuss how artificial non-wettable (biomimetic) surfaces are
prepared. Next, the basic properties of non-wettable surfaces, which make
them promising candidates for a wide range of applications, are discussed.
Furthermore, the various applications of non-wettable surfaces are
discussed, with references made to review articles with specific coverage of
named applications. We conclude with a summary, challenges limiting the
application of non-wettable surfaces to some real-life situations and possible
suggestions to mitigate them as well as opportunities for future work.
Modelling the Impact of Key Pests of Watermelon on its Performance Using Linear Regression Models
(Walailak J Sci & Tech, 2020-06-05) Emmanuel, OKRIKATA; OGUNWOLU, Emmanuel Oludele; ODIAKA, Ngozi Ifeoma
Despite the economic, health, and nutritional values of watermelon, insect pests remain a key limitation to its production globally. However, there has, hardly been any research that has statistically modeled the impact of insect pests on its performance. Therefore, this study aims to determine the relationship between the performance of watermelon and the density of its key pests with the aid of correlation and linear regression models, thereby presenting models for forecasting crop performance vis-à-vis pest density for optimum pest management. Data were collected from 40 m2 plots grouped into 4 replicates (10 plots/replicate) in field experiments (arranged in a randomized complete block design) in the early- and late-sown crops of 2016 and 2017 in the Research Farm of Federal University, Wukari, Nigeria. Plant survival rate (%) negatively and significantly (P≤ 0.05) correlated with each of mean number leaf-feeding beetles (r = −0.80, R2 = 63.5 %, Y = 92.023 – 3.145x; r = −0.79, R2 = 62.1 %, Y = 95.986 – 5.975x), A. gossypiidensity (r = −0.67, R2 = 44.9 %, Y= 184.048 – 50.444x; r = -0.65, R2 = 42.4 %, Y= 131.852 – 14.618x), and B tabacidensity (r = −0.67, R2 = 45.2 %, Y= 188.832 – 11.138x; r = −0.66, R2 = 43.3 %, Y= 178.738 – 3.701x) in both the early- and late-sown crop of 2016, respectively, with a similar trend in those of 2017. All parameters significantly (P ≤ 0.05) fitted the linear regression model. Densities of all major pests consistently correlated negatively and significantly with fruit yield. Student’s t-test detected significant differences between the early- and late-sown crops of both years. We therefore conclude that watermelon experiences multiple pest infestations whose compositions and intensities vary between seasons, and that their influence on agronomic performance, as shown by the coefficient of determination (R2) values (which were indicative of the reliability of the models with respect to the effect of pests on crop performance), were largely close or > 50 %.