Sub Humid Ecozone Of Western Kenya Biology Essay

An intercropping survey at Maseno, western Kenya investigated above-ground competitory effects of artemisia and maize intercropping in two back-to-back rain-fed turning seasons ( which old ages? ) , by measuring growing wonts and output forms from among eight different spacing governments. The competitory ratio ( CR ) and replacement value of Intercropping ( RVI ) were used in the rating of artemisinin, comparative chlorophyll content, and biomass output utilizing eight interventions ( which 1s? ) laid out in a randomised complete block ( barricading against what? ) ( RCBD ) design with 3 reproductions. Spacing had no important consequence ( P & A ; gt ; 0.05 ) on chlorophyll content of intercrops, artemisia Crown diameters, and works highs in both seasons. Treatments effects on artemisinin outputs were important ( P & A ; gt ; 0.05 ) during the short rains but had lower content of 0.74 % than the long rains ‘ season mean of 0.8 % . A positive correlativity ( r2=0.7 ) between artemisinin segregation and comparative chlorophyll content of artemisia foliages was observed at crop. There was a important consequence ( P & A ; lt ; 0.05 ) on CR of artemisia against corn among the intercrops. Unlike corn, there was a important consequence of spacing on RVI ( P & A ; lt ; 0.05 ) for artemisia. It is concluded that artemisia is more competitory than maize when the two harvests are grown together in association with optimum spacing, except when the planting form is altered to ease optimum growing wonts. By changing spacing governments and hence works densenesss for variable costs of corn and artemisia, profitable artemisia + corn intercropping may necessitate that husbandmans apply spacial agreements in which complementary effects on net end product exceed competitory abilities of artemisia.

Cardinal WORDS: Intercropping, Competitive Ratio, Replacement Value of Intercropping, Artemisin, Food Security.

Introduction

Intercropping is when two or more harvests are cultivated on the same land direction unit either in a temporal sequence or spacial agreement [ FAO, 2005 ] . Generally, intercropping systems in the sub-humid trop­ics are portion of a continuum of landscapes for interrorw harvests for intensive homegar­dens [ Abebe, 2005 ] , in which the bush com­ponent can remain in the field for a drawn-out fallow period, therefore pulling significant labor input and assorted constituent interactions. Intercropping is therefore a infinite, clip and labour dependent signifier of multi-functional agribusiness. Intercropping farther provides husbandmans the chance to diversify and heighten the rule of biodiversity preservation [ Ghosh, 2004 ] on their farms to understate hazards of net harvest failure and guarantee nutrient security.

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For intents of harvest variegation and value add-on to subsistence agriculture, artemisia ( Artemisia annua L. ) is a medicative bush whose infusions include artemisinin as the active ingredient that treats malaria when used in combination therapy [ WHO, 2008 ] ; while corn ( Zea mays L. ) is a staple nutrient harvest in Kenya. A production system that entails intercropping suited nutrient harvests and medicative bush with optimum constituent interactions could hence supply an alternate beginning of low-cost health care, income and nutrient security intervention..

The suitableness of Intercropping for application in subhumid tropical climes and agroforestry systems of Kenya for nutrient security and prolonging supports has competently been demonstrated [ Amadalo et al. , 2003 ; Gathumbi et al. , 2004 ; Sikolia et al. , 2009 ] . However, Intercropping creates component interactions between any two or more single workss that may either cut down or increase the energy of one or all of the constituent harvests. Harmonizing to Dhima et al. , [ 2007 ] , this may hold a important impact on the growing rate and output of the different species used in intercropping. Crop output variableness besides comes from complex interactions between the environment, spacing, direction, primogenitors and abiotic factors that occur across a field [ Baumann et al. , 2001 ] of intercrops. For illustration, artemisinin has phytotoxic activity, even on the artemisia works itself [ Lydon et al. , 1997 ] , doing it a suited campaigner for natural weedkiller. Interplant competition may therefore non ever ensue in a hapless public presentation of the intercrop since, apart from intra-specific competition, workss compete with persons that are to some extent different while their resource demands and their abilities for resource acquisition are non needfully the same [ Van der Meer, 1989 ] . The advantages of an intercropping system therefore include addition in production per unit country of land despite competition for infinite and growing foods.

Consequently, income from little graduated table farming to heighten nutrient security could be in footings of foregone labour man-days ; or the Replacement Value of Intercropping [ Van der Meer, 1989 ] for the clip and inputs used on a cocktail of assorted combinations of the intercrops grown either at the same time or consecutive with minimal fallow periods. Furthermore, output advantages in intercropping systems are frequently associated with the Fuller usage of environmental resources over clip by viing component harvests [ Willey and Rao, 1980 ] . The huge possible accruing from intercropping artemisia and maize on output of both harvest constituents peculiarly in respect to competitory abilities and chance costs have non been documented.

Harmonizing to Cadisch et Al. [ 2002 ] blending species with compatible and complimentary root and/or shoot growing patterns leads to a more diverse system and may besides maximize above and below land growing resources ‘ use. In this regard, Sobkowiez [ 2006 ] farther studies that two normally used intercropping schemes entail seting a deep-seated harvest with a shallow-rooted harvest, or seting a tall harvest with a shorter harvest that requires partial shadiness. In bomber humid zones on acid dirts competition between shrub-crop intercrops for visible radiation, foods and wet can be really terrible due to the consequence of shadowing [ Lawson and Kang, 1990 ] , where harvest output decreases with addition in distance from the bush rows have been reported [ Netondo, 1991 ; Chirwa et al. , 2007 ] . Since H2O and N are critical foods for works growing and productiveness for both the artemisia [ Ferreira and Janick, 2009 ] and maize constituents [ B & A ; auml ; nziger et al. , 1997 ] , competition can be more terrible peculiarly in degraded sloppy countries of western Kenya with fickle rainfall or level land with ill drained dirts and vulnerable to H2O logging.

Competition can happen between the same works species, called intraspecific competition, or between different species, called interspecific competition. Ultimately, any multifunctional agribusiness like an agroforestry intercropping system affecting corn as a nutrient harvest and artemisia as a medicative bush will imply effectual application of good agribusiness patterns ( GAPs ) for minimal pesticide use. This will guarantee the least possible impact on the environment and giving a merchandise that can be accurately traced from the field where it is grown to the consumer [ WHO, 2003 ] . These patterns should besides be geared towards minimising competition for works growing resources, and enhance or compliment any positive constituent interactions that may be.

Willey and Rao [ 1980 ] demonstrated that the competitory ratio ( CR ) could be utile in comparing the competitory ability of different harvests, step competitory alterations within a given combination and find what competitory balance between harvest constituents is most likely to give maximal output advantages. Competition may therefore non ever ensue in a hapless public presentation of the intercrop since, apart from intra-specific competition, workss compete with persons that are to some extent different while their resource demands and their abilities for resource acquisition are non needfully the same [ Mkamilo, 2004 ] . Furthermore, the CR represents the ratio of single LERs of constituent harvests and takes into history the proportion of the harvests in which they are ab initio seeded [ Putnam et al. , 1985 ] . Since the CR targets a scope of growing resources for competition, it may therefore be more applicable interchangeably in ‘Additive Series ‘ and ‘Replacement Series ‘ of intercropping [ Fukai and Trenbath, 1993 ] aiming interplant completion for one specific growing resource.

There is nevertheless scarce scientific grounds from bomber humid parts on interactions between inter-plant competition with positive effects of bush and nutrient harvests ; but one time site specific optimization of the cropping system is effected, the biological virtue of intercropping makes it an of import preservation farm pattern for smallholder husbandmans, since the system permits alimentary recycling and reduces the demand for weedkillers in most instances [ Van Noordwijk et al. , 1999 ] . Infact, intercropping is normally considered as an option for incorporate weed direction, peculiarly in farming systems with low external inputs application [ Itulya, 1998 ] and this may heighten system productiveness through desired constituent interactions and lowered variable costs.

MATERIALS AND METHODS

The experiment was carried out at Maseno University field station, UM3 – which is a seasonal semi-deciduous moist Agroforest clime [ FAO, 1978 ] . Maseno country lies at latitude 00o 01’N – 12 ‘S and longitude 34o25’E-47’E but the height at the experimental site is 1500m a.s.l. ; Latitude 00 ‘ 08 ” S, Longitude 340 35 ‘ 47 ” Tocopherol ; The experimental site receives a average one-year precipitation of 1750 millimeter with a bimodal distribution and average diurnal temperatures of 28.7 deg.C. The dirts in the country are classified as Acrisols, good drained, deep ruddy brown clay, reasonably acidic with pH runing between 4.6 and 5.4, and are deficient of P and N [ Jaetzold et al. , 2005 ] .

The experiment was carried out during the period from September 2009 to August 2010, trusting on rainfall precipitation of two back-to-back seasons interspersed with a brief dry enchantment or fallow period of 45 yearss. Land was prepared to ticket tilth before planting of certified corns seed from Kenya Seed Company of assortment H513 which matures in 120 to 150 yearss during both short rains ( SR ) and long rains ( LR ) . Artemisia was so transplanted after the first weeding of corn when at articulatio genus high, when the immature artemisia workss had grown to 50 centimeter in tallness with norm of 15 true foliages, in conformity with the patterns of Ferreira et al. , [ 2005 ] . Artemisia seedlings were clustered in a impermanent seed bed to procure unvarying highs after which transfering during both seasons took topographic point after the rains had soaked the land sufficiently to guarantee the dirt has high wet content to advance seedling energy. Holes were dug in the moisture land deep plenty to keep all the artemisia roots vertically at the base so as to understate decompression sicknesss on the roots, and pre-empt developing hapless root systems that risk fostering weak workss.

Diamonium phosphate ( DAP ) fertiliser was applied at planting of corn in all the secret plans at the recommended rate of 50 kilograms ha-1 while Calcium ammonium nitrate ( CAN ) was used for localised top dressing of corn merely after 1st weeding besides at the rate of 50 kg ha-1. The 2nd season ( LR ) land readying incorporated into the dirt old root stumps from the intercrop harmonizing to the patterns of Okalebo et al. , [ 1999 ] and Laughlin [ 1994 ] for corn and artemisia severally. The 2nd weeding in both seasons was done by manually deracinating the few weeds that emerged so as to understate dirt perturbation. The experiment had eight interventions, laid out as a randomised complete block design ( RCBD ) in 3 replicates, with three different intrarow spacings of the artemisia i.e. 0.75m, 0.9m, and 1m severally, and unvarying supplantings of corn from the artemisia at 0.90m X 0.75m. The works spacial agreements were therefore in ‘Additive series ‘ to ensue in a changeless corn works denseness in all interventions but changing artemisia population harmonizing to the method of Fukai and Trenbath, [ 1993 ] . Each secret plan reproduction size measured 6m tens 4m including two control secret plans of pure bases for the interventions. The interventions were designed as follows:

T1 = Artemisia 1m X 1m ; Maize 0.90m X 0.75m ;

T2 = Artemisia 1m X 0.75m ; Maize 0.90m X 0.75m ;

T3 = Artemisia 1m X0.9m ; Maize 0.90m X 0.75m ;

T4 = Artemisia 0.75m X 0.75m ; Maize 0.9m X 0.75m ;

T5 = Artemisia 0.9m X 0.75m ; Maize 0.9m X 0.75m ;

T6 = Artemisia 0.9m X 0.9m ; Maize 0.9m X 0.75m ;

T7 = Maize 0.90m X 0.75m ( Pure Stand ) ;

T8 = Artemisia 1m X 1m ( Pure Stand ) ;

After the first weeding and canopy closing of artemisia in all interventions, merely maize pure base was subjected to 2nd weeding out of necessity because all artemisia interventions did non hold subsequent weeds. Above land works biomass of both corns and artemisia was determined from an country of 24m2 at crop and extrapolated to production ha-1. Artemisia was severed at the root vertex and the harvested workss placed in brown paper bags after sun drying on black polyethylene sheets, after which they were weighed utilizing an electronic deliberation balance ( Denver instrument theoretical account XL -31000 ) at Maseno botanical gardens. A similar intervention was besides done for grain corn in which measuring was done with dry whole chaffs severed at the root vertex. Relative chlorophyll content was determined from an norm of triplicate readings utilizing a SPAD metre harmonizing to the method of Peng et al. , [ 1992 ] .These readings were taken to co-occur with periods of optimum vegetive growing, for all the corn and artemisia intercrops and their several pure stands. Artemisia workss were threshed whole and resulting foliages air dried on black polyethylene sheets to 8 % wet content after which a representative sample from each intervention was analysed for artemisinin following the method of Christen and Veuthey [ 2001 ] .

The Competitive Ratio ( CR )

The competitory ratio ( CR ) is a step of comparative interspecies competition that indicated the figure of times by which one constituent harvest was more competitory than the other [ Willey and Rao, 1980 ] . Measurements to show the being or non of competition by comparing the CR among the intercrops in each intervention was hence deliberate following the method of Willey and Rao [ 1980 ] :

CRmaize = ( LERMaize / LERArtemisia ) ten ( Za / Zm ) , ( 1a )

CRArtemisia = ( LERArtemisia / LERMaize ) ten ( Zm / Za ) ( 1b )

Where, LERMaize is the Partial LER for Maize, LERArtemisia is the partial LER for Artemisia. Zm and Za are the proportions of corn and Artemisia in the mixture severally. The LER was expressed by the equation suggested by Rao and Coe [ 1992 ] :

LER = Ci/Cs + Ti/Ts ( 2 )

Where, Ci = harvest output under intercropping ; Cs = harvest output under exclusive cropping ; Ti = Shrub output under intercropping ; and Ts = Shrub output under exclusive system.

Replacement Value of Intercropping ( RVI )

As a step of comparative economic output advantage of intercropping artemisia and corn, the Replacement Value of Intercropping ( RVI ) was determined for each intervention following the method of Van der Meer [ 1989 ] while replacing for artemisia and corn interchangeably:

RVIArtemisia = ( a ten PArtemisia + B x PMaize ) / a ten MArtemisia – C ( 3a )

RVIMaize = ( a ten PMaize + B x PArtemisia ) / a ten MMaize – C ( 3b )

Where:

PArtemisia and PMaize are the outputs of artemisia and maize in the mixture severally. MArtemisia is the single-channel harvest outputs of artemisia to be used interchangeably with MMaize for Maize ; B and a are the market monetary values of corn and artemisia severally ; and, C is the variable cost associated with mono-cropping artemisia or maize interchangeably for replacing i.e. labor costs, cost of seting stuff and fertiliser. All the informations collected was subjected to analysis of discrepancy for RCBD utilizing the Costat statistical computing machine bundle. The intervention and block agencies were separated utilizing the least important differences ( LSD ) trial at 0.05 % , while homogeneousness of discrepancies was verified by Bartlett ‘s trial.

A correlativity analysis between chlorophyll ( x ) and artemisinin ( y ) content of artemisia interventions ( n=7 ) at harvest clip was done utilizing Pearson ‘s Correlation Coefficient ( R ) : –

( 4 )

RESULTS AND DICUSSION

The information on works highs, crown diameters, biomass output, competitory ratio ( CR ) , and replacing value of intercropping ( RVI ) obtained from the intercropping system of corn + artemisia in different spacing governments, every bit good as the correlativity between chlorophyll and artemisinin segregation are presented in Figures 1, 2 and 3 every bit good as Tables 1, 2 and 3 severally.

There was no important consequence ( P & A ; gt ; 0.05 ) of spacing on Chlorophyll content of both artemisia and corn during both seasons. However, comparative chlorophyll content appeared to diminish with increased works adulthood ; and had a strong positive correlativity ( r2=0.7 ) with artemisinin content ( Fig. 1 and Table 3 ) . The survey produced a average artemisinin output of 0.8 % which is above the universe norm of 0.6 % reported by Ferreira and Janick [ 2009 ] . The short rains ( SR ) interventions had a important consequence on artemisinin outputs ( P & A ; gt ; 0.05 ) but lower content of 0.74 % on norm than during the LR season mean of 0.8 % ( Table 1 ) . Apart from T8 ( pure base ) , T4, T3 and T2 exhibited the highest % artemisinin than the other interventions at 0.82 % , 0.77 % and 0.76 % severally. Since artemisinin is a secondary metabolite, climatic and geographical conditions, together with the manner and clip of seting and harvest home of A. annua can act upon its production [ Marchese et al. , 2010 ] . This may assist to explicate why the artemisia harvest grown in the short rains ( SR ) had higher biomass but less artemisinin content than the Long rains harvest, on history of the precipitation fluctuations experienced in the two seasons ( Fig 2 ) . The comparatively high artemisinin content yielded in LR compared to SR may besides hold been occasioned by mild H2O logging in the former, to the extent that artemisinin segregation may be related to the workss ‘ mechanism of battling emphasis in this instance occasioned by extra wet. The higher rainfall recorded during the LR may therefore hold had an consequence of bring oning early blossoming for increased segregation of artemisinin at the disbursal of roll uping biomass. This is consistent with Marchese et al. , [ 2010 ] who observed that biomass and artemisinin accretion are greatly affected by H2O content in the dirt during seedling phase ; and reliable rainfall or irrigation potency is indispensable for 2-3 months after transfering where distribution is more of import than absolute sums.

The works content of artemisinin besides varies during the season, independent of the developmental phase of the works [ Delabays et al. , 2001 ] but in this survey, the undistinguished fluctuation in outputs within each of the two cropping seasons in artemisinin content is in concurrency with Ferreira et al. , [ 2005 ] who reported that unlike seed, vegetetative extension of artemisia will bring forth homogeneous workss sing artemisinin content. The positive correlativity between chlorophyll content and artemisinin farther suggests that Photosynthetic activity and segregation of artemisinin are closely related in infinite and clip within leaf gill. Since foliage chlorophyll content may be a map of both dirt and foliage N at any point in clip during active vegetetative growing, leaf thickness affects the appraisal of foliage N because there is a strong additive relationship between SPAD values and foliage N concentration [ Peng et al. , 1992 ] . It may therefore be possible to find the works ‘s demand for extra N fertiliser at a specific period in clip during the growing rhythm utilizing SPAD values. The consequences indicate that the most appropriate harvest home clip for artemisia was at the blossoming phase, when the chlorophyll content was highest. In add-on, the positive correlativity between chlorophyll and artemisinin segregation, suggests that it is possible to pull strings N application degrees at critical phases of works growing and development, in order to heighten leaf artemisinin concentration. Similar consequences have been obtained from artemisia by Banyai et al. , [ 2010 ] through exogenic GA3 intervention. Artemisinin segregation in foliages has antecedently been correlated with enzymatic activities in biosynthetic tracts [ Wallaart et al. , 2000 ] and hence by deduction, some applications of chlorophyll steps can besides be used in appraisal of CR for intercropping systems where artemisia bush is a constituent.

The Competitive Ratio ( CR )

The CR is an ideal agencies of finding the grade to which one harvest competes with the other in an intercropping system [ Willey and Rao, 1980 ] so that if CR & A ; lt ; 1, there is a positive benefit for corn relation to artemisia ; and if CR & A ; gt ; 1, there is a negative benefit to the secondary harvest relation to the chief harvest [ Putnam et al. , 1984 ; Ghosh et al. , 2004 ] . The different spacing governments had a important consequence ( P & A ; lt ; 0.05 ) on the competitory ratio of artemisia against corn among the intercrops during both seasons ( Table 2 ) .T3 exhibited the highest average CR at 1.75 while T1 had the Lowest at 0.85 and were statistically different from the control. T1 corn ( CRSR=1.5, CRLR=0.9 ) had a higher CR than artemisia ( CRSR=0.67, CRLR=1.03 ) . The consequences suggest that artemisia was a better competititor than maize in all interventions except T1. This implies that intercropping non merely compares the competitory ability of different harvests but besides influences interspecies complimentarity. On norm, artemisia was 1.3 ( or 30 % ) more competitory than corn during both cropping seasons in this survey. It is notable from these CR values that maize exhibited significantly lower competitory ability than artemisia, even though it had the highest intercropping densenesss among the interventions and was provided with an early competitory advantage by being sown first semi-sequentially. Therefore, both competition and interplant facilitation occurs in any intercropping system as was reported by Van der Meer, [ 1989 ] . Since complimentary or facilitative constituent interactions in T1 resulted in significantly higher maize biomass outputs ( Table 1 ) , T1 intercrop agreement may therefore stand for a leaning towards facilitative constituent interactions in favor of corn under this spacing government, by exhibiting para in competition with artemisia for growing resources. T1 intercropping agreement could therefore be more desirable for works architectural agreements if corn is to be considered as the chief harvest in the mixture for optimum outputs. This is the antonym of T2, T3, T4, T5 and T6 when artemisia is targeted as the chief harvest. Shahid and Saeed [ 1997 ] besides used CR values & A ; gt ; 1.0 to describe that lentil was a better rival when sown in association with wheat.

In general, the more a competitory ratio of each intervention approached unit value, the more the maize+artemisia intercrop balanced the competition between both species, proposing further that there is an advantage in corn intercropped with artemisia in individual hedgerows of each works species. This output advantage is likely due to different above-ground growing wonts and morphological features of intercrop constituents for doing optimum usage of growing resources/ factors. This statement corroborates that of Awal et al. , [ 2007 ] , who report that as CR approaches unit values intercrop associations in barley+peanut efficaciously compensate the competition for growing resources between these species. A comparative maize+beans system in western Kenya was besides found by Woomer et al. , [ 2004 ] to let larger light incursion, which probably benefits the corn every bit good as the leguminous plant. The principle here is that since the two species rely on the growing resource differentially, for illustration visible radiation on history of their fluctuation in growing rate, so facilitative constituent interactions may be possible.

In add-on, the CR represents the ratio of single LERs of constituent harvests and takes into history the proportion of the harvests in which they are ab initio seeded [ Putnam et al. , 1984 ] . Higher CR values for artemisia suggest that the harvest was a better rival and utilized the growing resources more sharply than maize, despite holding been planted consecutive. Artemisia T3 had an exceptionally higher CR value than other interventions, proposing that this intercropping government represents a relatively strong competitory ability for artemisia against corn, and is therefore expected to cut down maize outputs when grown as an inter­crop. A similar observation was made by May, [ 1982 ] while working on green gms ( Phaseolus Aureus ) and bulrush millet ( Pennisetum Americanum ) intercropping. Since both competition and complimentarity occurred in the maize+artemisia system, CR could besides be utile in finding what competitory balance between constituents is most likely to give maximal output advantages [ Willey and Rao, 1980 ] . Since artemisia T3 had the lowest works denseness ( Table 1 ) among all interventions, another possible deduction of high T3 CR values is that artemisia harvests ‘ in this spacial agreement had more than ample infinite for growing and development, and may hold concentrated on physiological mechanisms to optimize usage of growing resources. Banik et al. , [ 2000 ] besides reported similar tendencies in competition and recorded down intercropping outputs of mustard+pea, mustard+lentil, and mustard+gram mixtures over exclusive cropping. By and large, both complimentarity and competitory ability of constituent harvests in this survey forms a footing for urging improved agroeconomic productiveness. A similar proposition was made by Mkamilo [ 2004 ] , in the ecological and socioeconomic context of maize+sesame intercropping. However, the mechanism of the different competitory abilities between artemisia+maize intercropped works species has non been recorded, and the finding of this mechanism may help further in pull stringsing interspecies competition for improved direction patterns that overcome production restraints to heighten intercrop productiveness.

Replacement Value of Intercropping ( RVI )

After canopy closing of artemisia, the maize+artemisia intercrop had no incidence of weed infestation in contrast to maize monocrop. As a step of the comparative complimentary effects of biological and economic output potency of intercropping, Moseley [ 1994 ] proposed that the Replacement Value of Intercropping ( RVI ) by Van der Meer [ 1989 ] could be modified to better construe nutrient harvest and shrubs intercropping betterments with preset fallow periods, and variable costs for labor and inputs used in the production procedure of the intercropping system. The RVI is therefore the factor by which the polyculture is more or less valuable than the monoculture [ Moseley, 1994 ] . In instance the fallow period is less than unit value ( i.e. one twelvemonth ) for either the monoculture or polyculture state of affairs, so the RVI consequence will stand for the extent to which the artemisia+maize intercrop is more or less valuable than the several monocrop in an one-year growing rhythm. There was no important consequence of spacing on RVI ( P & A ; gt ; 0.05 ) during both seasons ( Table 1 ) . Maize T7 produced the least RVI value of 1.1 was statistically different from the other interventions which recorded a average RVI of 1.5. There was a important consequence of spacing on RVI ( P & A ; lt ; 0.05 ) during both seasons. Artemisia T6 recorded the highest RVI value at 1.6 and was statistically different from T1 ( 1.3 ) but non different statistically from interventions T2, ( 1.4 ) T3, ( 1.4 ) and T4, T5 that recorded a RVI of 1.5 each. Since T2, T3, T4, T5 and T6 were non statistically different from each other, but higher than T1 and lower than T8 the control, the average RVI of 1.45 was used for artemisia from both the SR and LR seasons. This indicates that the net income from the intercrop is 45 % higher than monocrops, to the extent that husbandmans who planted artemisia and corn could do a net income of 45 % more than the husbandmans who are involved in monocropping of artemisia. This may be attributable to both the shortened fallow period and the attendant decrease or replacing in variable costs of labor and fertiliser that are associated with artemisia+maize intercrops. The man-days used in weeding of the intercrops may therefore hold been reduced well as a consequence of built-in ability of the comrade harvest of artemisia to stamp down weeds. Since seasonal fluctuation did non hold a important consequence on RVI, another deduction of high values may bespeak efficient usage of available clip in the turning season since both harvests can be grown twice yearly with a sawed-off fallow period.

A high mean RVI of 1.55 from corn suggests that the increased benefit of the husbandmans involved in these intercrops may therefore be facilitated by more efficient usage of growing resources, every bit good as decrease in the variable costs upto a upper limit of 55 % , through use of labour properties like the weeding governments that are reduced by half as a consequence of individual labor input to cover two harvests, and decrease in cost of fertiliser by individual application in inter-cropping compared to monocropping. Complementarity of resource usage may besides hold occurred through interactive consequence of using commercial fertiliser to maize intercrops, as demonstrated by the important consequence of spacing ( P & A ; lt ; 0.05 ) on biomass outputs ( Table 1 ) . The RVI was determined in this test to measure the comparative economic output advantage of corn and artemisia monocultures against several intercrop replacings for the different spacing governments, bespeaking which form was more or less profitable in the usage of specific resources in the intercropping system. The increased net income ( or addition ) obtained in these intercrops may hold been occasioned by shortening of the fallow period as was postulated by Moseley, [ 1994 ] ; Or facilitated with decrease in variable costs by 45 to 55 % as was likewise observed with Njoroge et Al. [ 1993 ] , who estimated the net benefit of intercropping java with nutrient harvests by accounting for entire variable costs from the gross net incomes.

The average RVI of 1.55 for corn recorded between the two seasons further indicates that the net income from the intercrop is 55 % higher than maize monocrops intending that husbandmans who planted artemisia and corn could do a net income of 55 % more than the husbandmans who are involved in monocropping of corn. A similar statement may besides keep for artemisia visa-a-vis corn, in add-on to fact that lower RVI of artemisia ( 1.45 ) compared to maize ( 1.55 ) suggest that replacing maize with artemisia will non add value to maize monoculture. As labour becomes scarce with regard to available land, Intercropping may go more attractive due to the nest eggs in hard currency inputs ; and shrubs ( as hard currency harvest ) addition in value relation to nutrient harvests cultivated by little graduated table husbandmans. By changing variable costs of corn and artemisia, successful intercropping may therefore necessitate that husbandmans design efficient systems in which complementary effects of intercropping on net returns exceed competitory effects as was reported by Ong, [ 1996 ] . While working on maize+okra intercrops, Alabi and Esobhawan [ 2005 ] besides concluded that any scheme that reduces cost of production in these intercrops will increase its profitableness and attraction to husbandmans. The RVI index captures some of the restrictions associated with measuring biological output advantage by accounting for harvest continuance and the comparative economic advantage of an AF intercropping system that includes variable costs in the production procedure.

CONCLUSIONS AND RECOMMENDATIONS

Intercropping in this survey demonstrates complimentarity of corn and artemisia, every bit good as higher competitory ability of artemisia over corn in artemisia+maize system for higher income and nutrient security, through an informed pick of spacing options to bring forth coveted outputs. The CR and RVI can help researchers/extension agents in choosing intercropping patterns that are most suited on footing of optimum constituent interactions for recommendation to husbandmans. These indices provided an improved estimation of the cumulative effects of above-ground constituent interactions for comparative advantage of an intercropping system using short fallow periods. Due to the little mean farm sizes in western Kenya and high capacity for intensification hence the demand for optimum land usage patterns, the suited spacial agreements from this survey ranges from T1, T3, T4, T5 and T6 depending on degree of intensification and desired end product by the husbandman. For husbandmans with a penchant for artemisia or maize, a spacing government of T3 ( 1m Artemisia X 0.75m ; Maize 0.90m X 0.75m ) or T1 ( 1m Artemisia X 1m ; Maize 0.90m X 0.75m ) severally will be ideal ; An artemisia+maize intercrop with a spacing government of T6 0.9m Artemisia X 0.9m ; Maize 0.90m X 0.75m is recommended for seting during the short rains ‘ season. This spacing government provided the highest replacing value of intercropping. For husbandmans with more intensified signifiers of Intercropping, a spacing government of T4 ( 0.75m Artemisia X 0.75m ; Maize 0.90m X 0.75m ) and T5 ( 0.90m Artemisia X 0.75m ; Maize 0.90m X 0.75m ) is recommended if excess application of foliar fertiliser is applied at critical growing phases prior to reap to bring forth high artemisinin content.

Recognitions

We thank Maseno University for availing the Research Farm to carry on the survey and are thankful to the East African Botanical Extracts Ltd. , for easing the usage of their research labs at Athi River, Kenya for artemisia sample analysis.

Fig. 1: Chlorophyll content and Artemisia Yield Comparison ; r2 = 0.7 Data points are the mean of three reproductions

+LEGEND:

T1 = Artemisia 1m X 1m ; Maize 0.90m X 0.75m ; T2 = Artemisia 1m X 0.75m ; Maize 0.90m X 0.75m

T3 = Artemisia 1m X0.9m ; Maize 0.90m X 0.75m ; T4 = Artemisia 0.75m X 0.75m ; Maize 0.9m X 0.75m

T5 = Artemisia 0.9m X 0.75m ; Maize 0.9m X 0.75m ; T6 = Artemisia 0.9m X 0.9m ; Maize 0.9m X 0.75m

T8 = Artemisia 1m X 1m ( Pure Stand )

Table 1: Consequence of spacing Maize and Artemisia on Mean Crown diameter of Artemisia, Biomass Yields and Chlorophyll Content of the Intercrops

Spacing+

Intercrop Population

( 24m2 )

Crown Diameter ( Cm )

Chlorophyll Content

( SPAD Units )

Biomass outputs ( t/ha )

Artemisia

Artemisia

Maize

Maize

Artemisia

T1

85

111.3ab

5.95a

35.5ab

2.38bc

7.36bc

T2

78

108.7ab

6.67a

37.9ab

2.10c

7.29bc

T3

74

116.8a

5.98a

37.6ab

2.78bc

5.39d

T4

90

99.9b

6.30a

37.7ab

2.35bc

9.67a

T5

90

106.7ab

6.12a

37.5ab

2.25bc

8.975a

T6

85

108.2ab

6.10a

38.7ab

2.38bc

7.08c

T7

50

39.1a

3.85a

T8

35

108.4ab

6.65a

8.75ab

CV %

11.8

14.8

7.38

19.96

16.45

LSD0.05

22.7

1.1

4.3

0.31

0.81

Significance

Nitrogen

Nitrogen

Nitrogen

*

*

{ Average values in a column followed by dissimilar missive ( s ) indicate differences at 0.05 ( * ) degree of significance.

Ns =Not important at P & A ; gt ; 0.05 }

+LEGEND:

T1 = Artemisia 1m X 1m ; Maize 0.90m X 0.75m ; T2 = Artemisia 1m X 0.75m ; Maize 0.90m X 0.75m

T3 = Artemisia 1m X0.9m ; Maize 0.90m X 0.75m ; T4 = Artemisia 0.75m X 0.75m ; Maize 0.9m X 0.75m

T5 = Artemisia 0.9m X 0.75m ; Maize 0.9m X 0.75m ; T6 = Artemisia 0.9m X 0.9m ; Maize 0.9m X 0.75m

T7 = Maize 0.90m X 0.75m ( Pure Stand ) T8 = Artemisia 1m X 1m Artemisia ( Pure Stand )

Table 2. Consequence of Spacing Maize and Artemisia on Competitive Ratio ( CR ) and Replacement Value of Intercropping ( RVI ) .

Spacing+

RVIArte

RVIMaze

CRArte

CRMaize

% ArtLR

% ArtSR

T1

1.3c

1.6a

0.85c

1.20a

0.76ab

0.65b

T2

1.4bc

1.5a

1.47b

0.69bc

0.83a

0.74ab

T3

1.4bc

1.5a

1.75a

0.52bd

0.76ab

0.78a

T4

1.5ab

1.5a

1.30b

0.76bc

0.84a

0.80a

T5

1.5ab

1.5a

1.16b

0.95b

0.71ab

0.68ab

T6

1.6ab

1.7a

1.24b

0.80c

0.82a

0.68ab

T7

1.1b

0e

T8

1.0d

0d

0.89a

0.86a

Mean

1.40bc

1.55a

1.3b

0.8c

0.8a

0.74ab

CV ( % )

10.78

21.25

19.3

26.49

8.12

7.51

LSD 0.05

0.09

0.16

0.385

0.29

0.13

0.12

Spacing

*

*

*

*

Nitrogen

*

Season

Nitrogen

*

{ Average values in a column followed by dissimilar missive ( s ) indicate important differences at 0.05 ( * ) degree of significance ; Ns=not important at P & A ; gt ; 0.05, Art=artemisinin ; LR=long rains ; SR=short rains }

+LEGEND:

T1 = Artemisia 1m X 1m ; Maize 0.90m X 0.75m ; T2 = Artemisia 1m X 0.75m ; Maize 0.90m X 0.75m

T3 = Artemisia 1m X0.9m ; Maize 0.90m X 0.75m ; T4 = Artemisia 0.75m X 0.75m ; Maize 0.9m X 0.75m

T5 = Artemisia 0.9m X 0.75m ; Maize 0.9m X 0.75m ; T6 = Artemisia 0.9m X 0.9m ; Maize 0.9m X 0.75m

T8 = Artemisia 1m X 1m ( Pure Stand )

Table 3: Consequence of Spacing Artemisia and Maize on Chlorophyll and % Artemisinin Content ( Art. )

Treatment+

Art.LR

Art.SR ( Y )

Chl ( X )

X*Y

X2

Y2

T1

0.76ab

0.65b

5.95

3.87

35.40

0.422

T2

0.83a

0.74ab

6.67

4.94

44.49

0.547

T3

0.76ab

0.78a

5.98

4.66

35.76

0.608

T4

0.84a

0.81a

6.30

5.04

39.69

0.640

T5

0.71ab

0.68ab

6.12

4.16

37.45

0.462

T6

0.82a

0.68ab

6.10

4.15

37.21

0.462

T8

0.89a

0.86a

6.65

5.72

44.22

0.740

CV %

8.12

7.51

Mean

0.80

0.741

6.25

4.65

39.17

0.555

LSD 0.05

0.13

0.12

Significance

N

**

? ( T1-T8 )

5.19

43.77

32.54

274.23

3.883

?

?Y =0.54

?X =5.01

?XY =3.90

?X2=36.11

?Y2=0.42

r2

0.7

{ +see Legend below. LR- long Rains ; SR- Short Rains ; Mean values in a column followed by dissimilar missive ( s ) indicate important differences at 0.05 ( * ) degree of significance ; r2 = Pearson ‘s correlativity coefficient }

+LEGEND:

T1 = Artemisia 1m X 1m ; Maize 0.90m X 0.75m ; T2 = Artemisia 1m X 0.75m ; Maize 0.90m X 0.75m

T3 = Artemisia 1m X0.9m ; Maize 0.90m X 0.75m ; T4 = Artemisia 0.75m X 0.75m ; Maize 0.9m X 0.75m

T5 = Artemisia 0.9m X 0.75m ; Maize 0.9m X 0.75m ; T6 = Artemisia 0.9m X 0.9m ; Maize 0.9m X 0.75m

T8 = Artemisia 1m X 1m ( Pure Stand )

Fig.2 Rainfall Pattern Maseno Area ( Aug 2009 – July 2010 ) .Source: Maseno Agricultural Training Centre.

Fig. 3: The consequence of spacing Artemisia and Maize on Maize Plant Heights. Data points are the mean of three reproductions and bars represent standard mistakes.

+LEGEND:

T1 = Artemisia 1m X 1m ; Maize 0.90m X 0.75m ; T2 = Artemisia 1m X 0.75m ; Maize 0.90m X 0.75m

T3 = Artemisia 1m X0.9m ; Maize 0.90m X 0.75m ; T4 = Artemisia 0.75m X 0.75m ; Maize 0.9m X 0.75m

T5 = Artemisia 0.9m X 0.75m ; Maize 0.9m X 0.75m ; T6 = Artemisia 0.9m X 0.9m ; Maize 0.9m X 0.75m

T7 = Maize 0.90m X 0.75m Maize ( Pure Stand ) T8 = Artemisia 1m X 1m Artemisia ( Pure Stand )

Spacing

Fig 4. The consequence of spacing Artemisia and Maize on Artemisia Plant Heights. Data points are the mean of three reproductions and bars represent standard mistake.

+LEGEND:

T1 = Artemisia 1m X 1m ; Maize 0.90m X 0.75m ; T2 = Artemisia 1m X 0.75m ; Maize 0.90m X 0.75m

T3 = Artemisia 1m X0.9m ; Maize 0.90m X 0.75m ; T4 = Artemisia 0.75m X 0.75m ; Maize 0.9m X 0.75m

T5 = Artemisia 0.9m X 0.75m ; Maize 0.9m X 0.75m ; T6 = Artemisia 0.9m X 0.9m ; Maize 0.9m X 0.75m

T7 = Maize 0.90m X 0.75m Maize ( Pure Stand ) T8 = Artemisia 1m X 1m Artemisia ( Pure Stand )

x

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