Horticulture

Permanent URI for this collection

https://repository.nrf.go.ke/handle/123456789/796

Browse

Browsing Horticulture by Funder "NACOSTI"

Now showing 1 - 4 of 4
  • Thumbnail Image
    Publication
    Climate-resilient horticulture for sustainable county development in Kenya
    (Wageningen University and Research, 2020-04) Patrick, Esther M.; Koge, Jessica; Zwarts, Emiel; Wesonga, John M.; Atela, Joanes O.; Tonui, Charles; Kilelu, Catherine; Goosen, Hasse; Coninx, Ingrid; Koomen, Irene
    mmary Climate change presents one of the greatest challenges to the productivity and sustainable growth of the agricultural sector in Kenya due to extreme events such as droughts and floods as well as changes in temperature. Horticultural crops are particularly sensitive to climate change because of their high water demand and strict temperature requirements. Increased or decreased rainfall and increased temperature result in drought or flooding, lack of water for irrigation, and pests and diseases epidemic can affect the suitability of areas for growing horticultural crops. Understanding the impacts of climate for a given crop under specific conditions is key to supporting further development of the horticulture sector. While horticulture is a priority economic subsector in many counties, it is not known how the counties position themselves with regard to dealing with climate change threats in the sector. A review of the literature shows how climate change significantly affects the performance of horticultural crops across a variety of climatic zones and that counties need to be better prepared to address these effects. Horticulture covers myriad crops (including fruits and vegetables), which are affected by climate change in different ways. Seasonal patterns, both for temperature as well as (onset of) rainfall are changing. Temperature thresholds for specific crops are being exceeded, while some areas are now more favourable for growing certain crops where previously temperatures were too low. Suboptimal temperatures affect both the yield and quality of produce. The horticulture sector has also experienced incidences of pests, such as Tuta absoluta on tomato; climate change is a confounding factor to the spread and establishment of these pests. Agriculture which is highly affected by climate change is devolved to counties; as such, policies relevant to it are expected to be implemented at county level. An analysis of the County Integrated Development Plans showed that horticulture is a high-value subsector that plays a major role in generating revenue for county development. Most counties have prioritized horticulture and made substantial investments. Climate change is acknowledged as a threat to different sectors, but there is only scant analysis of the factors causing it, effects it will have and proposed responses to it. Farmers and crop officers from Kiambu and Kajiado counties are aware of climate change and its effects on horticulture. However, understanding of the relationship between cause and effect and of possible mitigating actions is weak. We observed that at all levels, in the field as well as at county level, preparedness for climate change is low and government support to the farmers is also limited. Due attention and informed decision-making based on, for example the Kenya Climate Atlas that is currently being developed, is required.
  • Thumbnail Image
    Publication
    Effects of deficit irrigation on yield and quality of Onion crop
    (University of Eldoret, 2014) Rop, David Kiplangat
    There is shortage of onions in Uasin Gishu and Nandi counties during dry season from October to March when the demand is high. Rainfall during the period is inadequate for crop development. This study aimed at testing Deficit Irrigation technology as an appropriate irrigation management strategy that could improve crop water productivity and give optimum Onion crop yield. A field trial was conducted in Nandi County with drip irrigation system and six irrigation treatments replicated three times in a randomized complete block design. Full supply of crop water requirement to meet 100% ETc (T100) acted as a control. The crop was subjected to five stress levels T90, T80, T70, T60 and T50 at vegetative and late season growth stages. Establishment and yield formation stages were given adequate water to meet normal crop water demand (ETc). The treatments were protected from receiving extra water from the rain. The yield, biomass, quality and irrigation water use efficiency were determined. The data collected were statistically analyzed using ANOVA. The variation in yield ranged from 34.4 ton/ha to 18.9 ton/ha and that of quality from 64 mm to 35 mm diameter for T100 and T50 respectively. The treatments T90, T80, T70, and T60 gave yields of 33 ton/ha, 32 ton/ha, 25 ton/ha and 23 ton/ha with corresponding bulb diameter of 60 mm, 58 mm, 53 mm and 40 mm. Water stress of 20% led to optimum yield with water saving of 10.7%. The results obtained from the field trial were used to calibrate and validate the performance of AquaCrop Model using separate data sets. Statistical indices, Model efficiency (E), root mean squared error (RMSE), coefficient of residuals (CRM) and coefficient of determination (R2 ) were used to evaluate the performance of AquaCrop model in simulating yield, biomass, canopy cover and soil moisture parameters. The model performance statistical index was found for R2 as 0.912 for canopy and 0.798 for soil moisture in confirming model calibration. Similarly, the index (R2 ) for confirming model validation for canopy and soil moisture was 0.892 and 0.616 respectively. The model was applied to derive full (T100) and deficit (T80) irrigation schedules for three weather regimes from October-March growing seasons between 2003 and 2012 giving rise to 34 and 30, 38 and 34, 45 and 40 irrigation events each of 13 mm respectively. It was concluded from the results that deficit irrigation (DI) at vegetative and late growth stages significantly influenced yields. DI influenced the size and size distribution of fresh Onion bulbs significantly (Fcalculated = 96.28, Fcritical = 3.12). However, it did not significantly affect the shape of onion. AquaCrop model performance in simulating yield, green canopy cover and soil moisture declined at higher stress levels. The model is useful in developing irrigation schedules for different weather regimes that can be applied by farmers through extension services. It was recommended that the model be used to simulate yield at lower stress levels and adopted for irrigation scheduling by farmers and field extension staff. DI technology should be adopted for optimum yield and maximum water productivity.
  • Thumbnail Image
    Publication
  • Thumbnail Image
    Publication
    Mapping of Quantitative Trait Loci (QTL) Related to Drought Tolerance in Common Bean (Phaseolus vulgaris L.) Using F2 Population from (KATB1 Χ GLP2)
    (International Annals of Science, 2018-10-13) Charles Langat; Omwoyo-Ombori; Richard Cheruiyot; Moses Gathaara; David Karanja; Philip Leley
    Many of the common bean growing regions around the world are prone to drought stress, making drought the major challenge to production and yield stability in rainfed environments. Mapping of yield-associated loci under drought stress will offer a better understanding of the genetics of drought tolerance to the plant breeders and therefore, will accelerate the selection of drought tolerant crop varieties through marker assisted selection (MAS).The current study reports identification of quantitative trait loci (QTL) linked to physiological, phenological, yield and yield related traits using 120 F2 population derived from a cross between two common bean genotypes, KAT B1 (drought tolerant) and GLP2 (drought susceptible) evaluated under drought stress and well-watered conditions. The research was conducted at the Agricultural and Mechanization Institute, Machakos, Kenya. The F2 population showed significant variation in traits under drought stress. From the 374 polymorphic SNP markers surveyed, 20 genomic regions were identified for various traits under drought stress, individually explaining 2.6 to 21.3% of phenotypic variation. The number of QTLs identified per trait were: 2-grain/seed yield (GY); 1-number of branches (NBP); 2-stem biomass (SB); 1-leaf biomass (LB); 1-pod biomass (PB); 3-days to flowering; 2-days to maturity (DM); 4- number of pods per plant (NPP); 1-seed weight (SW); 2-stomatal conductance (SMTL) and 1-leaf water potential (LWP). QTLs for number of pods per plant, number of grains/seeds per pod, days to flowering, leaf biomass and stem biomass were found co-locating with QTLs for grain yield on chromosome Pv02 under drought stress treatment. The cumulative effects of these QTLs on chromosomes 2 resulted in higher grain/seed yield. This study has provided information on QTLs in common bean that could be used in selection purpose for grain yield under drought conditions.