Department of Plant Science

Permanent URI for this collectionhttps://repository.chuka.ac.ke/handle/chuka/421

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Transcriptomic and Physiological Analyses Reveal Potential Genes Involved in Photoperiod-Regulated β-Carotene Accumulation Mechanisms in the Endocarp of Cucumber (Cucumis sativus L.) Fruit
(MDPI, 2022) Obel, H. O.; Cheng, C.; Tian, Z.; Njogu, M. K.; Li, J.; Du, S.; Lou, Q.; Zhou, J.; Yu, X.; Ogweno, J. O.; Chen, J.
The accumulation of carotenoids in plants is a key nutritional quality in many horticultural crops. Although the structural genes encoding the biosynthetic enzymes are well-characterized, little is known regarding photoperiod-mediated carotenoid accumulation in the fruits of some horticultural crops. Herein, we performed physiological and transcriptomic analyses using two cucumber genotypes, SWCC8 (XIS-orange-fleshed and photoperiod-sensitive) and CC3 (white- fleshed and photoperiod-non-sensitive), established under two photoperiod conditions (8L/16D vs. 12L/12D) at four fruit developmental stages. Day-neutral treatments significantly increased fruit β-carotene content by 42.1% compared to short day (SD) treatments in SWCC8 at 40 DAP with no significant changes in CC3. Day-neutral condition elevated sugar levels of fruits compared to short-day treatments. According to GO and KEGG analyses, the predominantly expressed genes were related to photosynthesis, carotenoid biosynthesis, plant hormone signaling, circadian rhythms, and carbohydrates. Consistent with β-carotene accumulation in SWCC8, the day-neutral condition elevated the expression of key carotenoid biosynthesis genes such as PSY1, PDS, ZDS1, LYCB, and CHYB1 during later stages between 30 to 40 days of fruit development. Compared to SWCC8, CC3 showed an expression of DEGs related to carotenoid cleavage and oxidative stresses, signifying reduced β-carotene levels in CC3 cucumber. Further, a WGCNA analysis revealed co-expression between carbohydrate-related genes (pentose-phosphatase synthase, β-glucosidase, and trehalose- 6-phosphatase), photoperiod-signaling genes (LHY, APRR7/5, FKF1, PIF3, COP1, GIGANTEA, and CK2) and carotenoid-biosynthetic genes, thus suggesting that a cross-talk mechanism between carbohydrates and light-related genes induces β-carotene accumulation. The results highlighted herein provide a framework for future gene functional analyses and molecular breeding towards enhanced carotenoid accumulation in edible plant organs.
Spatiotemporal Trajectories of Invasive Tree Species Reveal the Importance of Collective Action for Successful Invasion Management
(Taylor & Francis Group., 2022) Adoyo, B.; Schaffner, U.; Mukhovi, S.; Kiteme, B.; Mbaabu, P. R.; Eckert, S.; Choge. S.; Ehrensperger, A.
Biological invasions are complex processes requiring coordinated and spatially targeted management. This study assessed spatiotemporal tra- jectories and determinants of Prosopis cover in Baringo County, Kenya. Land cover data for every seven years between 1988 and 2016 revealed the presence of Prosopis. We tested for trajectory clusters using spatial autocorrelation and overlaid the trajectory categories with landscape features. Generally, most plots were only temporarily managed or not managed at all, while continuous management of Prosopis occurred mainly near rivers and on plots suitable for cultivation. Parcels within 250 m from roads, which are dispersal pathways for Prosopis seeds, were rarely cleared of Prosopis. We conclude that successful management requires incentives for stakeholders’ engagement in collective manage- ment action at a landscape level. Trajectory mapping should be integrated into planning tools to foster the prioritization of timely and context- specific response mechanisms.
Stubborn Disease of Citrus Caused by Spiroplasma Citri: A Short Note
(EScience Press, 2021) Kiptoo, J. J.; Mubeen, M.; Usman, H. M.; Abbas, A.; Pixley, K.; Chemoiwa, E.; Kiptoo, G. J.
Citrus fruit is considered a very nutritious and delicious diet. Citrus consists of lemon, oranges, mandarin, and grapefruit which have economic value in the world. Significant losses occur in citrus due to numerous diseases. Among various diseases, citrus trees are seriously affected by a phytopathogenic mollicute Spiroplasma citri which causes stubborn disease. S. citri is transovarially transmitted by several leafhopper species. Symptoms include smaller and cupped leaves, small size, crook fruits with aborted seeds. Moreover, irregularity on the fruits such as different sizes, shapes, and typically lighter, smaller fruits than its healthy counterpart has also been observed. The affected fruits often drop before maturity. The color inversion is often seen with the stylar end remaining green and the peduncle end showing color. Various molecular and biochemical tests are conducted to identify S. citri. Under in-vitro conditions, S. citri grows on SP4 media where a fried egg-like shaped colony is observed. Keeping the importance of the stubborn citrus disease, the present short note briefly described the symptomology, detection, transmission, and management.
Mycotoxins in Poultry Feed and Feed Ingredients from Sub-Saharan Africa and Their Impact on the Production of Broiler and Layer Chickens: A Review
(MDPI Journals, 2021) Ochieng, P. E.; Scippo, M. L.; Kemboi, D. C.; Croubels, S.; Okoth, S.; Kang’ethe, E. K.; Antonissen, G.
The poultry industry in sub-Saharan Africa (SSA) is faced with feed insecurity, associated with high cost of feeds, and feed safety, associated with locally produced feeds often contaminated with mycotoxins. Mycotoxins, including aflatoxins (AFs), fumonisins (FBs), trichothecenes, and zearalenone (ZEN), are common contaminants of poultry feeds and feed ingredients from SSA. These mycotoxins cause deleterious effects on the health and productivity of chickens and can also be present in poultry food products, thereby posing a health hazard to human consumers of these products. This review summarizes studies of major mycotoxins in poultry feeds, feed ingredients, and poultry food products from SSA as well as aflatoxicosis outbreaks. Additionally reviewed are the worldwide regulation of mycotoxins in poultry feeds, the impact of major mycotoxins in the production of chickens, and the postharvest use of mycotoxin detoxifiers. In most studies, AFs are most commonly quantified, and levels above the European Union regulatory limits of 20 µg/kg are reported. Trichothecenes, FBs, ZEN, and OTA are also reported but are less frequently analyzed. Co-occurrences of mycotoxins, especially AFs and FBs, are reported in some studies. The effects of AFs on chickens’ health and productivity, carryover to their products, as well as use of mycotoxin binders are reported in few studies conducted in SSA. More research should therefore be conducted in SSA to evaluate occurrences, toxicological effects, and mitigation strategies to prevent the toxic effects of mycotoxins.
Enhancing Preharvest Physiology of Multi-Purpose Pumpkin Using Combined Nitrogen, Mulch and Gibberellic Acid
(African Journal of Horticultural Science, 2022) Isutsa, D.K.; Mwaura, M.M.
In recent times, it has become apparent that multi-purpose pumpkin (Cucurbita moschata Duch.) is a very important crop since its leaves, fruits and seeds can be eaten as vegetables, snacks and blended dishes to boost household food and nutritional security. However, it is regarded as a low value crop, leading to poor cultivation, comprehension of preharvest physiological behaviour, and maximization of productivity in Kenya. Consequently, a study was conducted to assess the effects of combined nitrogen, mulch and gibberellic acid (GA3) in enhancing its preharvest physiology of pumpkin. Four N rates of 0, 50, 100 and 150 kg N/ha supplied as CAN, three mulch types as none, unpainted, and black-painted rice straw, and three GA3 rates of 0, 40 and 80 mg/L were assessed. The experiment was arranged in split-split plots in randomized complete block design, replicated three times in two seasons, and each plant occupied 2 m x 2 m space. Nitrogen was applied to main plots, mulch to sub-plots, and GA3 to sub-sub plots. Pre-harvest physiological variables measured were stomatal conductance, chlorophyll, photosynthesis, and transpiration. Data values were subjected to analysis of variance using SAS Version 9.3. Separation of significant means was done using the least significant difference test at α = 0.05. Results showed that nitrogen and mulch individually and interactively did not significantly (P > 0.05) affect most pre- harvest physiological parameters. The effect of GA3 was not significant on stomatal conductance and leaf chlorophyll, but it was negative and significant on both photosynthesis and transpiration in season 1 which was drier than season 2. Based on the present results, the influence of combined nitrogen, mulch and GA3 on multi-purpose pumpkin cannot be entirely depicted by analysing preharvest physiology. Adoption and application of treatments that promote desired preharvest physiology of multi-purpose pumpkin is recommended, including 50 kg N/ha to enhance stomatal conductance and leaf chlorophyll, and unpainted rice straws to enhance leaf chlorophyll content and photosynthesis.
A Backward Regressed Capsule Neural Network for Plant Leaf Disease Classification
(Heliyon, 2021) Mugo, D. M.; Kenduiywo, B. K.; Too, E. C.
This study investigated the introduction of backward regression coupled with DenseNet features into a Capsule Neural Network (CapsNet) for plant leaf disease classification. Plant diseases are considered one of the main factors influencing food production, and therefore fast crop diseases detection and recognition is important in enhancing interventions. In the recent past, CapsNets have been used for plant leaf disease classification with some success. However, back propagation of signals to earlier layers is still a challenge due to low gradient flow, parameter and computational complexities exist due to lack of feature diversification which leads to poor patterns, and uses only higher level features while all features are necessary for classification. This work therefore adopted DenseNet intuition where a loop connectivity pattern was done in the convolution layer, a technique that made it easier for signals to be back propagated and create a strong gradient flow. The resultant model was able to attain computational and parameter efficiency because feature diversification led to richer patterns hence higher accuracy. The resultant model maintained low complexity as it used both complex and simple features. After feature collected in the convolution layer, backward regression was introduced to select only the features that had significant information to be used by the model, a technique that reduced computation time and reduced characters in the model without the loss of data. This work used the standard PlantVillage (PV) dataset comprising of ten tomato classes with a total of 9080 images and observed 99% accuracy on testing with backward regression and 87% on testing without backward regression.
Influence of Rhizobium Inoculation and Phosphate Rock Fertilizer Application on Growth and Yield Components of Green Gram in Tharaka-Nithi County, Kenya
(Meru University of Science & Technology, 2022) Mbaka, F.; Nduhu, H. O.; Oloo-abucheli, G. O.
Green gram is an important drought tolerant grain legume crop in Kenya. In Tharaka Nithi County green gram is as a major source of food security. Hence, there is need for a cheap and sustainable system of agricultural production is needed to increase its production. The legume/Rhizobium symbiosis in combination with phosphate rock offers a natural system for improving green gram nitrogen fixation. Therefore, this study was aimed at determining the effect of Rhizobium and phosphate rock fertilizer application on growth and yield attributes of N26 and KS20 varieties. The study was carried out at Chuka University Horticultural Research Farm for two seasons, November 2019 to January 2020 and February to April 2020. Factorial experiment of 2x2x2 was laid out in a Randomized Complete Block Design (RCBD). There were three factors, variety (N26 and KS20), phosphate rock (0 and 30 kg P ha-1) and Rhizobium MEA 716 (0 and 100 g ha-1). The experiment contained eight treatments which were replicated three times. The data was collected fortnightly on four randomly selected plants on parameters such as plant height, number of leaves, branches, pods, total dry biomass, shoot and root dry weight and grain yield. These data were analyzed using Statistical Analysis Software (SAS). Significant means are separated using Least Significant Difference (LSD) at probability level of 5%. Results for both seasons indicated that combined application of Rhizobium MEA 716 Rhizobium 100 g ha-1 and phosphate rock 30 Kg ha-1 phosphate under variety in treatment (R1P1KS20) showed significantly (P<0.05) higher plant height (76.07 cm), number of branches (14.08 plant-1), shoot dry biomass (52.01 g plant-1), root dry biomass (7.60 g plant-1), total dry biomass (146.4 g plant-1), number of pods (84 plant-1) and yield (2158 kg ha-1) compared to variety N26 in treatment (R1P1N26). Therefore, combination of Rhizobium MEA 716 100 g ha-1 and phosphate rock 30 Kg ha-1 under variety KS20 led to improved growth attributes equally yield components of KS20 variety over N26. From these findings, application of Rhizobium MEA716 at 100 g ha-1, and 30 Kg ha -1 phosphate rock under variety KS20 was recommended for improved and a sustainable green gram production in the study area.
Genome-Wide Identification of GASA Gene Family in Ten Cucurbitaceae Species and Expression Analysis in Cucumber
(MDPI, 2022) Zhang, K.; ; Li, Z.; Njogu, M.K.; Wang, X.; Jia, L.; Hu, Y.; Yang, D.; Yan, C.; Li, N.; Li, Z.; Njogu, M. K.; Wang, X.; Jia, L
Gibberellic acid-stimulated in Arabidopsis (GASA), a unique small molecular protein of plants, plays an essential role in plant growth and development. The GASA family genes have been identified and studied in many plants. However, the identification of GASA gene family in Cucurbitaceae species has not been reported yet. Therefore, in this study, based on the available genome information on the Cucurbitaceae species, the GASA family genes in 10 Cucurbitaceae species including cucumber (Cucumis sativus), watermelon (Citrullus lanatus), melon (Cucumis melo), pumpkin (Cucurbita moschata), wax gourd (Benincasa hispida), sponge gourd (Luffa cylindrica), bottle gourd (Lagenaria siceraria), bitter gourd (Momordica charantia), chayote (Sechium edule), and snake gourd (Trichosanthes anguina) were identified with bioinformatics methods. To understand the molecular functions of GASA genes, the expression pattern analysis of cucumber GASA family genes in different tissues and stress responses were also analyzed. The results showed that a total of 114 GASA genes were identified in the 10 Cucurbitaceae species, which were divided into three subfamilies. Synteny analysis of GASA genes among cucumber, Arabidopsis and rice showed that nine cucumber GASA genes were colinear with 12 Arabidopsis GASA genes, and six cucumber GASA genes were colinear with six rice GASA genes. The cis-acting elements analysis implied that the cucumber GASA genes contained many cis-elements associated with stress and hormone response. Tissue-specific expression analysis of cucumber GASA family genes revealed that only the CsaV3_2G029490 gene was lowly or not expressed in all tissues, the CsaV3_3G041480 gene was highly expressed in all tissues, and the other seven GASA genes showed tissue-specific expression patterns. Furthermore, nine cucumber GASA family genes exhibited different degrees of regulatory response under GA, abiotic and biotic stresses. Two cucumber GASA genes, CsaV3_3G042060 and CsaV3_3G041480, were differentially expressed under multiple biotic and abiotic stresses, which indicated that these two GASA genes play important roles in the growth and development of cucumber.
Modelling Plant Growth Based on Gompertz, Logistic Curve, Extreme Gradient Boosting and Light Gradient Boosting Models Using High Dimensional Image Derived Maize (Zea mays L.) Phenomic Data
(Science and Education Publishing, 2022) Gachoki, P.; Muraya, M.; Njoroge, G.
Modelling of plant growth is vital for hypotheses testing and carrying out virtual plant growth and development experiments, which may otherwise take a long time under field conditions. Modelling of plant growth has been aggravated by new phenotyping platforms that generate high dimensional data non-destructively over the entire growth time of a plant using a set of camera system. Such platforms generate high-throughput phenomic data, which is complex and constitute many features collected at multiple growth points for the same plant. However, the classical models are limited in that they can only model a single feature at a time. The objective of this study was to apply dynamic plant growth models that could be used to dissect complex relationships between plant growth and development using several modelling strategies. These included sigmoid, light GBM and XGBoost models. The image derived phenomic data was obtained from the Leibniz Institute of Plant Genetics and Crop Plant Research Gatersleben, Germany. The models were fitted using R statistical software and compared based on RMSE, R-squared, AIC and BIC performance metrics. The results showed that the XGBoost (RMSE = 2.1641) and Light GBM (RMSE = 2.7776) performed better than the Gompertz (RMSE = 3.8378) and the logistic function (RMSE = 3.8378) models in modelling maize plant growth. The XGBoost model (RMSE = 2.1641) showed better performance than Light GBM model (RMSE = 2.7776) in modelling maize plant growth. The Gompertz model using plant volume had AIC and BIC values for 139738.3 and 139763.4, respectively. The Gompertz model for plant side area had AIC and BIC values for 98436.15 and 98461.31, respectively. The logistic function model for plant volume had AIC and BIC values for 139749.2 and 139774.4, respectively. The logistic function model for plant side area had AIC and BIC values for 98415.95 and 98441.11, respectively. The Gompertz model and logistic function models showed almost the same performance in modelling maize plant growth. The non-parametric models, the XGBoost and light GBM, were found to perform better than the classical models (Gompertz and logistic functions) in modelling maize plant growth. Therefore, the study recommends the use of XGBoost as a generic model to fit high dimensional and complex phenotypic data in modelling plant growth and prediction of plant biomass yield at different growth points.
Features Selection in Statistical Classification of High Dimensional Image Derived Maize (Zea Mays L.) Phenomic Data
(Science and Education Publishing, 2022) Gachoki, P.; Muraya, M; Njoroge, G
Phenotyping has advanced with the application of high throughput phenotyping techniques such automated imaging. This has led to derivation of large quantities of high dimensional phenotypic data that could not have been achieved using manual phenotyping in a single run. Hence, the need for parallel development of statistical techniques that can appropriately handle such large and/or high dimensional data set. Moreover, there is need to come up with a statistical criteria for selecting the best image derived phenotypic features that can be used as best predictors in modelling plant growth. Information on such criteria is limited. The objective of this study is to apply feature importance, feature selection with Shapley values and LASSO regression techniques to find the subset of features with the highest predictive power for subsequent use in modelling maize plant growth using high- dimensional image derived phenotypic data. The study compared the statistical power of these features extraction methods by fitting an XGBoost model using the best features from each selection method. The image derived phenomic data was obtained from Leibniz Institute of Plant Genetics and Crop Plant Research, -Gatersleben, Germany. Data analysis was performed using R-statistical software. The data was subjected to data imputation using 𝑘 Nearest Neighbours technique. Features extraction was performed using feature importance, Shapley values and LASSO regression. The Shapley values extracted 25 phenotypic features, feature importance extracted 31 features and LASSO regression extracted 12 features. Of the three techniques, the feature importance criterion emerged the best feature selection technique, followed by Shapley values and LASSO regression, respectively. The study demonstrated the potential of using feature importance as a selection technique in reduction of input variables in of high dimensional growth data set.
Integrated Analysis of Transcriptome and Metabolome Reveals New Insights into the Formation of Purple Leaf Veins and Leaf Edge Cracks in Brassica juncea
(MDPI, 2022) Zhang, K; Yang, D; Hu, Y; Njogu, M. K; Qian, J; Jia, L; Yan, C; Li, Z; Wang, X; Wang, L
Purple leaf veins and leaf edge cracks comprise the typical leaf phenotype of Brassica juncea; however, the molecular mechanisms and metabolic pathways of the formation of purple leaf veins and leaf edge cracks remain unclear. In this study, transcriptome and metabolome analyses were conducted to explore the regulation pathway of purple leaf vein and leaf edge crack formation based on four mustard samples that showed different leaf colors and degrees of cracking. The results showed genes with higher expression in purple leaf veins were mainly enriched in the flavonoid biosynthesis pathway. Integrating related genes and metabolites showed that the highly expressed genes of ANS (BjuA004031, BjuB014115, BjuB044852, and BjuO009605) and the excessive accumulation of dihydrokaempferol and dihydroquercetin contributed to the purple leaf veins by activating the synthetic pathways of pelargonidin-based anthocyanins and delphinidin-based anthocyanins. Meanwhile, “alpha-farnesene synthase activity” and “glucan endo-1, 3-beta-D-glucosidase activity” related to the adversity were mainly enriched in the serrated and lobed leaves, indicating that the environmental pressure was the dominant factor controlling the change in leaf shape. Overall, these results provided new insights into the regulation pathways for formation of purple leaf veins and leaf edge cracks, which could better accelerate the theoretical research on purple leaf vein color and leaf edge cracks in mustard.
Evaluation of the Effect of Farmers’ Experience on Optimization of Coffee Yields in Chuka Sub-County, Tharaka Nithi County, Kenya
(RDP, 2023) Kihoro, D. M; Gathungu, G. K; Wainaina, M. G; Wairimu, V. N
Many farmers in the coffee-growing areas are determined to maintain production despite the challenges associated with the sector. Despite the efforts made by National and County governments to maximize coffee production in terms of quantity and quality, yields have shown a downward trend. The study's objective was to assess the factors affecting farmers’ experience optimizing coffee production in Chuka Sub-County, Kenya. Variables such as the years of coffee farming, the number of trainings attended, and the number of journals read on coffee production were evaluated. Proportional stratified random sampling was used to select a sample of 150 respondents from a population of 7,428 coffee farmers from ten cooperatives in the Chuka Sub-County, where each cooperative was treated as a stratum. The Chi- square test was used to establish an association between the effects of farmers' experience and optimization of coffee yield. The logit model also found the relationship between farmer experience and coffee yield optimization. Farmers' knowledge had a chi-square mean of 60.3%, indicating that it significantly affected coffee optimization. Out of the three factors evaluated, the few numbers of the training attended had a positive association with a chi-square of 36.643. The few years of coffee farming had chi-square values of 33.714, while the number of journals reads had a chi-square value of 24.21. The study also established that the number of years of coffee farming and the training attended positively and significantly affected yield optimization, while the number of articles read negatively and significantly affected optimization. Therefore, the research recommends that coffee farmers practice coffee farming for many years and increase training attendance to optimize coffee production.
Factors Leading to Decline of Coffee in Vihiga County, Kenya
(Asian Journal of Agricultural Extension, Economics & Sociology, 2017-05-04) Lugado, C and Omukoko, C; ; ;
Coffee is grown in many countries in the world including Africa and America. Kenyan coffee has been known to be among the country’s agricultural exports and contributes greatly to the growth of Kenyan economy. Coffee production yields has been declining from a peak of 128,700 metric tons per year to an average of 49,088 metric tons. Many industries have tried to address the issues identified to be contributors to the decline but the problem of production of coffee has not been fully solved though there is slight increase in production. The establishment that was under study was small scale farmers of coffee in Vihiga County, Vihiga Sub-county. The primary sources used during data collection include; interviews, observation and questionnaire while secondary sources used were; library research journals, textbook and factory publications. The target population of the study was 300 small scale farmers in Vihiga Sub-county. Ratified sampling technique was used to compare views among coffee producers from various coffee societies and farmers in the area. Data analysis was both quantitative and qualitative using descriptive statistics and data collected was analyzed using statistical program for social as (SPSS).Pests and diseases as well as poor management if adequately addressed by the government can help to increase production.
Effect of maize-cowpea cropping patterns on soil moisture conservation in Meru and Tharaka nithi counties
(Chuka university, 2023-07-20) K. I. Mwenda1#, S. W. Munyiri2, H. O. Ndukhu3; ; ;
Given the frequent drought pressure caused by the unpredictable and limited precipitation concurrent with global climate change, highly efficient cultivation technologies have been increasingly recognized by various levels of scientific communities. Maize (Zea mays L.) based intercropping systems are widely practiced in Kenya, but only a few studies have focused on cowpea (Vigna unguiculata L.) as the companion intercrop in moisture conservatory strategy. This study was conducted during the 2018 long rains of March-April at the Kenya Agricultural and Livestock Research Organization (KALRO) Igoji Research Station and Magutuni Primary school in Meru and Tharaka-Nithi Counties, respectively. The objective of the study was to assess the effect of incorporating cowpea into the maize production pattern on crop cover and soil moisture content. The experiment was laid in a randomized complete block design with three replications in 3 x 4 m plots. The treatments comprised of pure maize stand, maize intercropped with inoculated cowpea, maize intercropped with non-inoculated cowpea and pure non-inoculated cowpea. A generalized linear model was used to determine the effects of cropping patterns on ground cover, leaf area index and soil moisture content, using GenStat 19th edition. Means were separated using Fischer’s protected least significant difference (LSD) test, with differences considered significant at P≤ 0.05. Significantly (P≤ 0.05) higher (82%) crop cover was exhibited at kernel development stage in maize intercropped with inoculated cowpea compared to 78, 64 and 53% in maize intercropped with non-inoculated cowpeas , sole stand of non-inoculated cowpeas and sole maize stand, respectively. Similarly, the highest soil moisture content was recorded at kernel development stage: 210.3, 209.3, 200.2 and 196.4 mm in maize intercropped with inoculated cowpea, maize intercropped with non-inoculated cowpeas, sole stand of non-inoculated cowpeas and sole maize stand, respectively. Relative to sole maize stand and sole stand of non-inoculated cowpeas, maize intercropped with inoculated cowpea recorded the peak leaf area index of 3.75 at 70 days after planting at Igoji and 3.16 at 63 days after planting in Magutuni. The study showed that cowpea is a promising legume crop that could be integrated into maize cropping patterns to improve moisture conservation
Heavy Metal Phytoremediation Potential of Wild Plant Species Naturally Growing on Dumpsite, Kenya
(chuka university, 2024-12-04) Orao LA1 , Muraya MM2 and Ombaka CO3; ; ;
Soils form an essential part of life and the main sink of pollutants. Intense industrial and anthropogenic activities have led to serious environmental threats, resulting in increased heavy metal concentration in soils and, consequently, a phytotoxicity effect on plants. Phytoremediation can offer effective and eco-friendly remedies for polluted sites. This study characterized the diversity of various plants that spontaneously grow in a dumpsite and scrutinized their phytoremediation potential. The plants evaluated for phytoremediation potential were Ricinus communis, Parthenium hysterophorus, Cassia didymobotrya, and Datura stramonium. The location of the research was Kang’oki dumpsite, Kenya. Species diversity was studied using quadrat sampling thrown randomly throughout the dump site. The bioaccumulation factor (BF) and the translocation factor (TF) were calculated to determine the accumulation and mobility of the heavy metals in the plants. To determine the ability of the plants to remove, accumulate, and mobilize the selected heavy metals, soil and plant sampling was conducted within the 14 sampling sites. The samples were acid-digested, and concentrations of Pb, Zn, Cu, and Cd were analyzed using Atomic Absorption spectrophotometry. Data obtained was subjected to statistical analysis using SAS version 94. Shannon-Weaver diversity index (H’) was used for species diversity. An H’ of 0.94 and species evenness of 0.45 was found showing a high species diversity on the dumpsite. Cadmium concentration in soil samples ranged from ND to 1.63 mg/kg of soils and 0.4418 to 0.6939 mg/kg of plant tissues. Nickel concentration ranged from 7.9 to 36.33 mg/kg in soils and 9.31 to 11.38 mg/kg in plant tissue, respectively. Copper was found between 3.41 to 121.18 mg/kg of soils and 3.74 to 10.89 mg/kg of plant tissues, respectively. Lead in soils ranged from 13.25 to 8.013 mg/kg of soils and 11.48 to 13.89 of plant tissues. Leaves accumulated significantly (p < 0.05) higher amounts of heavy metals than roots and stems. The leaves and stem of Datura stramonium showed the highest concentration of cadmium and copper, while its stem showed the maximum concentration of Nickel and lead. Datura stramonium showed BCF and TF >1; hence, it can be used for phytoextraction of cadmium. All plants showed TF>1; hence, these plants can be used as hyperaccumulators.
Optimization of Groundnuts (Archis hypogeal) Yield through Response Surface Methodology
(Asian Journal of Probability and Statistic, 2024-04-10) Dennis Kiprotich a,b* , Dennis K. Muriithi a,b and Martin K. Njogu a,; ; ;
Groundnut production faces several constraints, including poor soil fertility, small land sizes, and inappropriate agricultural techniques. The study aimed to optimize groundnut (Archis hypogeal) yield using response surface methodology (RSM). It explored the use of CCD and RSM to determine the optimal application of rabbit, poultry, and sheep manure for maximum yield, a method not previously applied in groundnut production. The study was conducted at the Chuka University Teaching and Training Farm, Kairani. The experimental design was developed using Central Composite Design (CCD), with 20 experimental runs derived from 2 3 full factorial designs with six axial points and six center points. Data was collected on the weight of the groundnuts yield harvested in each experimental plot measured by use of a weighing scale. Response Surface Methodology techniques was adopted for data analysis in R-statistical software and R studio programing language. The study findings indicated that organic manures had a significant effect (P < 0.05) on the yield of groundnuts crop. The study revealed that application of 13.6097 t ha-1, 10.582 t ha-1 and 11.0814 t ha-1 of poultry, rabbit and sheep manure respectively are the optimum levels that would lead to maximum weight of groundnuts in the study area. The finding of this study could have an economic benefit to farmers in the study area which aligns with broader national goals of poverty reduction, rural development, and economic growth. This study recommended that farmers should adopt organic farming practices to reduce reliance on chemical fertilizers, improve soil health, and contribute to environmental sustainability.
Analysis of Technical Efficiency on Orange Fleshed Sweet Potatoes Production Among the Smallholder Farmers in Migori County Kenya
(Scvience of PG, 2024-10-18) Lawrence Otieno Jabuya1, * , Shelmith Wanja Munyiri2 , Martin Kagiki Njogu2; ; ;
Sweet potatoes (Ipomea batatas L.), particularly the orange fleshed variety, have become increasingly popular due to their ability to thrive in various environmental conditions with minimal inputs. Orange fleshed sweet potatoes (OFSPs) show potential for productivity, yet smallholder farmers in Kenya still struggle to maximize their yields. The factors influencing OFSP production efficiency among these farmers in Western Kenya have not been thoroughly examined. This study evaluated the technical efficiency of OFSP production among smallholder farmers in Migori County. Using a descriptive research design, a sample of 225 OFSP farmers was randomly selected by a cluster sampling technique. Data was collected through a structured questionnaire on inputs and selected socio-economic factors. The data was analyzed using the frontier stochastic model in STATA. Smallholder farmers estimated mean technical efficiency was 77.82% significant variables were; size of the land, availability of planting vines, access to hired labour, gender of the household decision maker, farming experience, household size, land ownership status, participation in training programs and extension services, and proximity to markets, indicating a need to improve OFSP production by 22.18%. These findings suggest that to reduce inefficiencies among smallholder OFSP farmers, targeted training programs are needed to enhance farmers' agronomic knowledge specific to OFSP production. Further, policy interventions should prioritize the provision of extension services to support and improve the performance of OFSP smallholder farmers.
Production of Mineral Nutrient-Rich Multipurpose Pumpkin Leafy Vegetables Using Integrated Nitrogen, Mulch and Ga3
(Journal of Environmental Sustainability Advancement Research, 2022) Mwaura, M. M., Isutsa, D. K. and Munyiri, S. W.; ; ;
Understanding the effect of nitrogen, mulch and gibberellic acid on minerals and metabolites in multipurpose pumpkin (Cucurbita moschata Duch) is important since it is a dependable source of food, providing families producing it with various diets that contribute to household food and nutrition security. However, production of the pumpkin using optimal or integrated inputs has not yet been embraced in most African countries, resulting in underrealization of its maximum potential. To respond to this challenge, a split-split plot experiment arranged in randomized complete block design and replicated three times was conducted for two seasons from January 2019 to July 2020. The nitrogen (0, 50, 100 and 150 kg N/ha) was assigned to main plots, mulch (no mulch, black-painted and unpainted rice straws) to sub-plots, and gibberellic acid (GA3) (0 mg/L, 40 mg/L and 80 mg/L) to split-plots. Nitrogen was applied as calcium ammonium nitrate (CAN) in two equal doses for each rate at three weeks postemergence and at the beginning of flowering. The black-painted and unpainted rice straws were placed on plots after land preparation. The GA3 solution was sprayed to plants using a 1-L sprayer, starting with 40 mg/L, followed by 80 mg/L, once during the fourth week post-emergence. Data collection was done fortnightly from the fourth week after emergence up to fruit harvest stage. Data values were subjected to analysis of variance using SAS software version 9.3 and means separated using the least significant difference test at α=0.05. All the measured parameters were significantly (P<0.05) different. Highest levels of K and Mg were obtained for 100 kg N/ha. On the other hand, P and beta-carotene were highest where unpainted rice straws were used, while application of 80 mg/L GA3 yielded high amounts of P and K. Results further showed that combined N fertilizer, mulch and GA3 consistently had significant (P<0.05) effects on N, P, K, Mg and beta-carotene (highest 23 ppm was for N1M1GA1). Therefore, sole nitrogen fertilizer, mulch, GA3, and combined rates that promote the desired mineral nutrient and beta-carotene contents in multi-purpose pumpkin leaves should be adopted and applied, depending on the kind.
A Comparative Study of Caffeine Levels in Coffee and Cocoa in Kenyan Supermarkets and Shops
(Pan-African Journal of Health and Environmental Science, 2024-05-20) Alex Muthengi1*, Silas Njiru1 and Juster Mungiria; ; ;
Background: Caffeine is an alkaloid belonging to the methylxanthine family. An overdose of caffeine causes the following side effects: restlessness, nervousness, excitement, insomnia, flushed face, diuresis, gastrointestinal disturbances, muscle twitching, rambling flow of thought and speech, and tachycardia or cardiac arrhythmia. This study aimed to determine the caffeine levels of various brands of coffee and cocoa and enlighten people on the safe and healthy consumption of the two products. Methods: Different brands of coffee and cocoa products were randomly sampled and purchased from supermarkets and shops in Nairobi, Kenya. Five samples of coffee and four brands of cocoa were purchased from a supermarket and taken to the laboratory for analysis. Caffeine was extracted, and quantitative analysis was done using High Performance Liquid Chromatography (HPLC). Results: The study found that coffee has a higher concentration of caffeine than cocoa. Coffee Brand A recorded the lowest level of caffeine with 30.9845 µ g/g, while Coffee Brand C recorded the highest level of caffeine with 426.9639 µ g/g. Among the Cocoa brands, Cocoa Brand B recorded the lowest level of caffeine (2.6367 µg/g), while Cocoa Brand C recorded the highest level of caffeine at 19.03 µ g/g. Conclusion: Therefore, there is a need to reduce coffee consumption per day because caffeine overdose can cause high blood pressure and other illnesses. Cocoa is recommended for consumption since it contains less caffeine per servin
Optimization of Groundnuts (Archis hypogeal) Yield through Response Surface Methodology
(Asian Journal of Probability and Statistic, 2024-04-10) Dennis Kiprotich a,b* , Dennis K. Muriithi a,b and Martin K. Njogu; ; ;
Groundnut production faces several constraints, including poor soil fertility, small land sizes, and inappropriate agricultural techniques. The study aimed to optimize groundnut (Archis hypogeal) yield using response surface methodology (RSM). It explored the use of CCD and RSM to determine the optimal application of rabbit, poultry, and sheep manure for maximum yield, a method not previously applied in groundnut production. The study was conducted at the Chuka University Teaching and Training Farm, Kairani. The experimental design was developed using Central Composite Design (CCD), with 20 experimental runs derived from 2 3 full factorial designs with six axial points and six center points. Data was collected on the weight of the groundnuts yield harvested in each experimental plot measured by use of a weighing scale. Response Surface Methodology techniques was adopted for data analysis in R-statistical software and R studio programing language. The study findings indicated that organic manures had a significant effect (P < 0.05) on the yield of groundnuts crop. The study revealed that application of 13.6097 t ha-1, 10.582 t ha-1 and 11.0814 t ha-1 of poultry, rabbit and sheep manure respectively are the optimum levels that would lead to maximum weight of groundnuts in the study area. The finding of this study could have an economic benefit to farmers in the study area which aligns with broader national goals of poverty reduction, rural development, and economic growth. This study recommended that farmers should adopt organic farming practices to reduce reliance on chemical fertilizers, improve soil health, and contribute to environmental sustainability

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