Evaluating maize performance under varying water depletion levels in bura irrigation scheme, Kenya | IJAAR

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Int. J. Agron. Agri. R.weighed on a digital balance with precision of ±0.002grams. The obtained weights were averaged andextrapolated to biomass inMgha -1 at a croppingdensity of 53,333 plants ha -1 .Canopy CoverMaize canopy cover (CC) was determined using themeter stick method (Miller, 1969) between 11.30amand 12.30pm every two weeks starting after 90%maize emergence. Three sites were selected atrandom and marked in each plot. The CC wasdetermined from these specific points throughout theexperimental period. The meter rule was placed onflat ground at midday and the% CC estimated bytaking the sum of centimeters covered by the canopyshade on the meter rule. The meter rule was thenrotated and the procedure repeated over an angle of45 o , 90 o and 135 o . The four readings were averaged toget the percentage CC for that spot. The readingsobtained from the three spots in a plot were averagedto get the percentage CC for the plot.Grain YieldGrain yield (GY) was determined by harvesting all cobsfrom three randomly selected plants in each of the sixrows after crop attained physiological maturity. Theaverage number of ears per plant, the average number ofrows per ear and the average number of grains per rowfrom each plot were determined. The cobs were shelledand units of 1000 grains weighed to obtain the averageweight of grain at 13.5% moisture content. The dataobtained was used to estimate GY per hectare usingEquations 1 and 2.Grains per ear = Rows of grains x number of gains perrow….…...Eq. 1Mass of grain per hectare = Number of ears perhectare x grains per ear x average mass ofgrain..….. Eq 2Statistical AnalysisData collected was summarized in Microsoft Excelspreadsheets and subjected to analysis of variance(ANOVA) using Statistical Analysis System (SAS)version 9.1. Post hoc analysis to separate the meanswas carried out using LSD (P ≤ 0.05) to determine thesources of differences.Results and discussionSoil characterization of the study siteThe amount of clay in the soil increased with depthfrom 30% at 0-30cm to 35% at 31-60cm and 44% at61-120cm depths (table 1). This could probably be dueto leaching of the fine clay particles by water down theprofile because clay is considered a mobilecomponent in the soil (Charles 1977), a phenomenonknown as eluviation.This leaves the coarse sand particles at the top. Gul et al.(2011) and Adugna et al. (2011) reported similarfindings. According to FAO World Soil ResourcesReports (2001), eluviation will occur when waterpercolates through the soil carrying with it clay as well asmetals, humus and other colloidal or dissolvedsubstances and deposit them in lower depths throughilluviation process (Gemma et al., 2017).Table 1. Salient soil characteristics of the study site.Thickness ofprofileSoil texture Texture class PWP FC AWC Ksatcm Sand (%) Silt (%) Clay (%) (USDA) --------- Vol.% -------- cm hr -10-30 50 20 30 Sandy clay loam 25.1 36.85 11.75 2.2731-60 40 25 35 Clay loam 14.74 32.85 18.11 0.88261-120 38 28 44 Clay 25.61 39.47 14.86 0.461Legend: PWP - permanent wilting point, FC - field capacity, AWC - available water capacity, Ksat - saturatedhydraulic conductivity.Amount of water that can be held in the soil profile isof great importance because soil is a major waterreservoir. Water retention of the top horizon (0-30cm) was lowest compared to the horizons below. Itwas highest in the middle horizon (31-60cm), whichthen decreased in the 61-120cm horizon (Table 1).The low available water capacity in the topsoilprobably was due to high sand content that reducedavailable water capacity because water in sand’s largepores is subject to free drainage under gravity.Muigai et al. Page 22
Int. J. Agron. Agri. R.As the soil particles size decrease, the pores becomefiner and hold more water against free drainage,increasing water-holding capacity as was seen withthe second profile. A fine textured soil therefore holdsmore water than a coarse textured one because smallpores have higher matrix potential than large pores(Jon, 2015). The bottom layer (61-120cm) had thehighest clay content (44%) in comparison to thehorizons above but in contrast, available water capacityof this horizon was found to be lower. This could bebecause clay creates a complex soil matrix of muchsmaller pores, which makes it hold more water, but thewater is held at greater suction pressure leading toincreased permanent wilting point, hence reducing theamount of available water. According to Nathalie et al.(2001), although clay soils can hold 280 mm of waterper metre depth, only 70 mm of it is available to plants.The rest of water is held so tightly and unavailable foruse by crops. This is also in agreement with findings byJeff (2001), O’Geen (2013), Ministry of Agriculture -British Columbia (2015) and Zachary (2016).The observed high Ksat values in the study indicatehigh rate of water movement. These Ksat values werefound to decrease with depth, as the amount of claycontent increased (table 1). This is an indication ofincreasing resistance to water movement down theprofile. Ksat is important in the study of soilinfiltration and drainage, aspects that are vital inirrigation water management (Tayfun, 2005) and inthe study of nutrient movement in the soil (Philip etal., 2014). The value is also important as it dictatesthe plant type to be grown in a soil, spacing anderosion control. Behzad (2015) also says that Ksat isimportant in modeling flow and contaminanttransport in the soil. Others such as Lin (2003) andWest et al. (2008) talk of importance of Ksat inmodeling and determination of water budget, soilleaching potential and its suitability for agriculture.The notable drop in Ksat value between the surface 0-30cm and the horizons below could be an indicator ofcompaction. This low Ksat in the lower horizon willcause resistance to plant root penetration and waterpercolation, which is likely to cause ponding andrunoff during rain or irrigation. Ponding indicatessaturated soils and most crops don’t do well inwaterlogged soils due to anaerobic conditions. SinceKsat in agricultural lands is influenced by, among otherfactors, cropping and tillage practices (Das et al.,2010), farmers can correct this by using better farmingmethods such as deep tillage to loosen the soil andapplication of manure that will improve soil structure.Effect of water depletion on maize performanceTreatments T75 and T50 had no significancedifference between them on above ground biomass(15.6 and 15.5Mgha -1 , respectively), canopy cover(67.6% and 64.7%, respectively) and grain yield (6.3and 6.2Mgha -1 , respectively). The two treatmentshowever had statistically (P≤0.05) higher aboveground biomass, canopy cover and grain yield ascompared to T25 (6.5Mgha -1 , 50.5% and 2.74Mgha -1 ,respectively) (Table 2). The good performance oftreatments T75 and T50 was probably because thetwo treatments didn’t suffer moisture stress becausethe available water capacity (AWC) didn’t fall below50%, the critical point for crops such as maize(Thomas et al., 2019).Table 2. Means of above ground biomass, canopycover, harvest index, stover and grain yield.Treat AGBSTY GYments (Mgha -1 CC (%) HI (%)) (Mgha -1 )(Mgha )T75 15.6 a 67 a 40.6 b 9.2 a 6.29 aT50 15.5 a 64.7 a 40.3 b 9.2 a 6.188 aT25 6.5 b 50.5 b 42.0 a 3.8 b 2.74 bP <0.0001 <0.0001 <0.0001 <0.0001 <0.0001LSD 0.42 4.62 1.13 0.391 0.136R 2 0.997 0.917 0.768 0.99 0.99CV 2.3 5.2 1.89 3.63 1.84Legend: T75 - irrigation to or near field capacity when25% of available water capacity (AWC) is depleted,T50 - irrigation to or near field capacity when 50% ofAWC is depleted, T25 - irrigation to or near fieldcapacity when 75% of AWC is depleted, ABM-aboveground biomass, CC-canopy cover, HI-harvest index,SY-stover yield and GY-grain yield.‘Water engine’ model (Yang et al., 2004) suggests thatthere is a linear relationship between yield to amountof water transpired and that enough water led to highrate of photosynthesis hence higher vegetativegrowth. Treatment T25 received 305mm ofsupplemental irrigation water against an evaporativedemand of 523mm for the growing season (Table 4),Muigai et al. Page 23
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Evaluating maize performance under varying water depletion levels in bura irrigation scheme, Kenya | IJAAR

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