Farmers' perception and evaluation of brachiaria Grass (brachiaria spp.) genotypes for smallholder cereal-livestock production in East Africa

Brachiaria (Urochloa) is a genus, common name brachiaria, of forage grasses that is increasingly transforming integrated crop-livestock production systems in East Africa. A study was undertaken to (i) assess smallholder farmers’ perception on benefits of brachiaria in cereal-livestock production, (ii) identify brachiaria production constraints, and (iii) identify farmer preferred brachiaria genotypes. A multi-stage sampling technique was adopted for sample selection. Data were collected through semi-structured individual questionnaire and focus group discussions (FGDs). The study areas included Bondo, Siaya, Homabay and Mbita sub-counties in Western Kenya and the Lake zone of Tanzania. A total of 223 farmers participated in individual response questionnaires while 80 farmers participated in the FGDs. The respondents considered brachiaria mainly important in management of cereal pests (70.4% of respondents) and as an important fodder (60.8%). The major production constraint perceived by both male and female respondents is attacks by arthropods pests (49.2% and 63%, respectively). Spider smites had been observed on own farms by 50.8% of men and 63.1% of women, while sorghum shoot flies had been observed by 58.1% of men and 67.9% of women. These pests were rated as a moderate to severe problem. Xaraes was the most preferred genotype, followed by Mulato II and Piata. These genotypes are important in developing new crop pest management strategies, such as push-pull, and for relatively rapid improvements in crop management and yield increases, particularly in developing countries

Field evaluation of a new third generation push-pull technology for control of striga weed, stemborers, and fall armyworm in western Kenya

Production of cereal crops in sub-Saharan Africa is threatened by parasitic striga weeds and attack by stemborers and the invasive fall armyworm (FAW), compounded by increasing hot and dry conditions. A climate-smart push-pull technology (PPT) significantly reduces effects of these biotic challenges. To improve further resilience of the system to climate change, more adapted and suitable companion plants were identified and integrated in a new version of PPT, termed ‘third generation PPT’. Our study evaluates field performance and farmer opinions of this new version in comparison with the earlier version, climate-smart PPT, and farmers’ own practices of growing maize in controlling stemborers, FAW, and striga weeds. Trials were conducted across five locations in western Kenya for two cropping seasons in the year 2019 following a one-farm one-replicate completely randomized design. We assessed infestation on striga, stemborers, and FAW, and yield performance of the three cropping systems. We also sought the opinions of the hosting farmers through semi-structured questionnaires that were administered through individual interviews. Both PPT plots recorded significantly (P < 0.05) lower striga count, FAW, and stemborer damage, and higher grain yield than in plots that followed farmers’ own practices. There was no statistically significant difference between the two PPT plots except for stemborer damage for which the third generation PPT recorded higher damage than the climate-smart PPT. However, farmers preferred the third generation PPT for important traits possessed by its companion plants which their counterparts in climate-smart PPT are deficient. The cultivar Xaraes was rated as ‘very good’ for resistance to spider mites, biomass yield, and drought tolerance while Desmodium incanum was rated ‘very good’ for seed production and drought tolerance. The third generation PPT is based on companion crops that are more resilient to hot and dry conditions which are increasing rapidly in prevalence with climate change. This version therefore presents a better option to upscale the technology and meet different needs of farmers especially in arid and semi-arid conditions

Genotypic response of brachiaria (Urochloa spp.) to spider mite (Oligonychus trichardti ) (Acari: Tetranychidae) and adaptability to different environments

Grasses in the genus Urochloa, commonly known as brachiaria, are grown as forage crops in sub-Saharan Africa, with some genotypes being used in management of insect pests. However, spider mite, Oligonychus trichardti Meyer (Acari: Tetranychidae), has recently been reported as its major pest in the region. We evaluated 18 brachiaria genotypes to identify sources of resistance to O. trichardti, and to determine their adaptability to different environments in western Kenya. Response to artificial infestation with O. trichardti was evaluated under controlled conditions in a screenhouse while adaptability to different environments and field resistance to mites was evaluated in three locations for two cropping seasons in 2016 and 2017 under farmers’ conditions. The parameters evaluated as indicators of resistance to pest damage included leaf damage, chlorophyll content reduction, plant height, leaf area, number of tillers and shoot biomass. Rainfall played a role in reducing mite infestation and increasing biomass yield of the genotypes. Significant correlations between parameters were only observed between leaf damage and yield (r = -0.50), and leaf damage and chlorophyll loss (r = 0.85). The cultivar superiority index (Pi) ranked Xaraes, Piata, ILRI 12991 and ILRI 13810 as reliable genotypes that combined moderate resistance to the mite (Pi ≤ 48.0) and high biomass yield (Pi ≤ 8.0). Since this is the first documentation of interactions between O. trichardti and different brachiaria genotypes, we propose these genotypes as potential candidates for improved forage yields in areas prone to O. trichardti infestation in Africa

Methods for Improving Inference in Clinical Outcomes

Advances in technology have allowed for the collection of diverse data types along with evolution in computer algorithms. This dissertation focuses on the development and application of novel methodologies to model and improve inference on clinical outcomes. First, a new prognostic approach of modeling time-to-event data using Bayesian Networks (BNs) is developed and illustrated using publicly available cancer data. This approach allows for flexible modeling of different structural relationships that might exist between variables at different periods, hence, improving our understanding of critical prognostic factors that can inform patient care and development of targeted interventions. As a prognostic model, BNs demonstrated better or comparable performance as compared to other equivalent models for bladder and lung cancer data. In this dissertation, we also reviewed application of predictive modeling algorithms in randomized clinical trials (RCTs). RCTs are costly and time-consuming. Predictive modeling has the potential to mitigate challenges associated with clinical trial failures and facilitate efficient clinical trial conduct in areas such as patient recruitment, trial optimization, and safety & efficacy evaluations. Finally, we present a new approach for estimating causal treatment effect in RCTs that are prone to post-randomization intercurrent events (ICE). Examples of ICE include treatment switch, treatment discontinuation, or adverse events. Here, we adopt the principal stratification framework where we first predict the latent strata membership using baseline covariates and then estimated causal treatment effects using appropriate stratum having a homogeneous group of subjects. Using simulations, our approach demonstrated a better performance in estimating treatment effects as compared to the standard intent-to-treat (ITT) strategy

A Hybrid Model for Detecting Phishing Attack Using Recommedation Decision Trees

Phishing performs by trying to trick the victim into accessing any computing information which looks original, then instructing them to send important data to unrestricted/unwanted privacy resource. For prevention, it is essential to develop a phishing detection system. Recent phishing detection systems are based on data mining and machine learning techniques. Most of the related work literature require collection of previous phishing attack logs, analyze them and create a list of such activities and block traffic from such sources. But this is a cumbersome task because the data size is very large, continue changing and dynamic nature. [1]. Instead of using single algorithm approach it would be better to use a hybrid approach. A hybrid approach would be better at mitigating phishing attacks because classification of different format of data is handled; whether the intruder want to use images or textural input to gain into another user system for phishing. Hybrid recommendation decision tress enhances any of machine learning and deep learning algorithms performance. The decision path of the model followed a series of if/else/then statements that connect the predicted class from the root of the tree through the branches of the tree to detect true positive and false negatives of phishing attempts. 10 decision trees were considered and used the features to train the recommendation decision regression model. The developed hybrid recommendation decision tree approach provided an overall true positive rate of the model of 92.28 % and false negative rate is 7.4%

Farmers' perception and evaluation of brachiaria Grass (brachiaria spp.) genotypes for smallholder cereal-livestock production in East Africa

Brachiaria (Urochloa) is a genus, common name brachiaria, of forage grasses that is increasingly transforming integrated crop-livestock production systems in East Africa. A study was undertaken to (i) assess smallholder farmers’ perception on benefits of brachiaria in cereal-livestock production, (ii) identify brachiaria production constraints, and (iii) identify farmer preferred brachiaria genotypes. A multi-stage sampling technique was adopted for sample selection. Data were collected through semi-structured individual questionnaire and focus group discussions (FGDs). The study areas included Bondo, Siaya, Homabay and Mbita sub-counties in Western Kenya and the Lake zone of Tanzania. A total of 223 farmers participated in individual response questionnaires while 80 farmers participated in the FGDs. The respondents considered brachiaria mainly important in management of cereal pests (70.4% of respondents) and as an important fodder (60.8%). The major production constraint perceived by both male and female respondents is attacks by arthropods pests (49.2% and 63%, respectively). Spider smites had been observed on own farms by 50.8% of men and 63.1% of women, while sorghum shoot flies had been observed by 58.1% of men and 67.9% of women. These pests were rated as a moderate to severe problem. Xaraes was the most preferred genotype, followed by Mulato II and Piata. These genotypes are important in developing new crop pest management strategies, such as push-pull, and for relatively rapid improvements in crop management and yield increases, particularly in developing countries

Suitability of brachiaria grass as a trap crop for management of Chilo partellus

The cereal stemborer Chilo partellus (Swinhoe) (Lepidoptera: Crambidae) is a major insect pest of sorghum (Sorghum bicolor L. Moench) and maize (Zea mays L.) in Africa. Trap cropping systems have been shown to be a valuable tool in management of this pest. To optimize trap cropping strate- gies, an understanding of host-plant preference for moth oviposition and host suitability for larval survival on potential trap plants is a prerequisite. Therefore, we assessed seven brachiaria accessions (Poaceae) for preference by C. partellus moths and subsequent larval performance. In two-choice tests with a local open-pollinated maize variety (cv. Nyamula), significantly higher numbers of eggs were deposited on brachiaria accessions Marandu, Piata, and Xaraes than on maize, whereas fewer eggs were recorded on plants of Mulato II, Mulato I, and Cayman. There was a significant and nega- tive correlation between the trichome density on plant leaves and C. partellus oviposition preference for brachiaria. In addition to poor larval performance on brachiaria, there was no clear ranking in the accessions regarding larval orientation, settling, arrest, and food ingestion and assimilation. First instars did not consume leaf tissues of brachiaria plants but consumed those of maize, which also suf- fered more stem damage than brachiaria plants. No larvae survived on brachiaria plant tissue for longer than 5 days, whereas 79.2% of the larvae survived on maize. This study highlights the prefer- ential oviposition of C. partellus on brachiaria plants over maize and the negative effects that these accessions have on subsequent larval survival and development. Our findings support the use of bra- chiaria as a trap crop for management of C. partellus through a push-pull technolog