Sub Humid Ecozone Of Western Kenya Biology Essay

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An intercropping study at Maseno, western Kenya investigated above-ground competitive effects of artemisia and maize intercropping in two consecutive rain-fed growing seasons (which years?), by evaluating growth habits and yield patterns from among eight different spacing regimes. The competitive ratio (CR) and replacement value of Intercropping (RVI) were used in the evaluation of artemisinin, relative chlorophyll content, and biomass yield using eight treatments(which ones?) laid out in a randomized complete block (blocking against what?) (RCBD) design with 3 replications. Spacing had no significant effect (P > 0.05) on chlorophyll content of intercrops, artemisia crown diameters, and plant heights in both seasons. Treatments effects on artemisinin yields were significant (P > 0.05) during the short rains but had lower content of 0.74% than the long rains' season mean of 0.8%. A positive correlation (r2=0.7) between artemisinin sequestration and relative chlorophyll content of artemisia leaves was observed at harvest. There was a significant effect (P < 0.05) on CR of artemisia against maize among the intercrops. Unlike maize, there was a significant effect of spacing on RVI (P < 0.05) for artemisia. It is concluded that artemisia is more competitive than maize when the two crops are grown together in association with optimal spacing, except when the planting pattern is altered to facilitate optimal growth habits. By varying spacing regimes and hence plant densities for variable costs of maize and artemisia, profitable artemisia + maize intercropping may require that farmers apply spatial arrangements in which complementary effects on net output exceed competitive abilities of artemisia.

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

INTRODUCTION

Intercropping is when two or more crops are cultivated on the same land management unit either in a temporal sequence or spatial arrangement [FAO, 2005]. Generally, intercropping systems in the sub-humid trop­ics are part of a continuum of landscapes for interrorw crops for intensive homegar­dens [Abebe, 2005], in which the shrub com­ponent can stay in the field for a prolonged fallow period, thus attracting substantial labour input and various component interactions. Intercropping is hence a space, time and labour dependent form of multi-functional agriculture. Intercropping further provides farmers the opportunity to diversify and enhance the principle of biodiversity conservation [Ghosh, 2004] on their farms to minimise risks of net crop failure and ensure food security.

For purposes of crop diversification and value addition to subsistence farming, artemisia (Artemisia annua L.) is a medicinal shrub whose extracts include artemisinin as the active ingredient that treats malaria when used in combination therapy [WHO, 2008]; while maize (Zea mays L.) is a staple food crop in Kenya. A production system that entails intercropping suitable food crops and medicinal shrubs with optimal component interactions could hence provide an alternative source of affordable healthcare, income and food security intervention..

The suitability of Intercropping for application in subhumid tropical climates and agroforestry systems of Kenya for food security and sustaining livelihoods has aptly been demonstrated [Amadalo et al., 2003; Gathumbi et al., 2004; Sikolia et al., 2009]. However, Intercropping creates component interactions between any two or more individual plants that may either reduce or increase the vigour of one or all of the component crops. According to Dhima et al., [2007], this may have a significant impact on the growth rate and yield of the different species used in intercropping. Crop yield variability also comes from complex interactions between the environment, spacing, management, progenitors and abiotic factors that occur across a field [Baumann et al., 2001] of intercrops. For example, artemisinin has phytotoxic activity, even on the artemisia plant itself [Lydon et al., 1997], making it a suitable candidate for natural herbicide. Interplant competition may thus not always result in a poor performance of the intercrop since, apart from intra-specific competition, plants compete with individuals that are to some extent different while their resource requirements and their abilities for resource acquisition are not necessarily the same [Van der Meer, 1989]. The advantages of an intercropping system thus include increase in production per unit area of land despite competition for space and growth nutrients.

Consequently, income from small scale farming to enhance food security could be in terms of foregone labour man-days; or the Replacement Value of Intercropping [Van der Meer, 1989] for the time and inputs used on a cocktail of various combinations of the intercrops grown either simultaneously or sequentially with minimum fallow periods. Furthermore, yield advantages in intercropping systems are often associated with the fuller use of environmental resources over time by competing component crops [Willey and Rao, 1980]. The immense potential accruing from intercropping artemisia and maize on yield of both crop components particularly in regard to competitive abilities and opportunity costs have not been documented.

According to Cadisch et al. [2002] mixing species with compatible and complimentary root and/or shoot growth patterns leads to a more diverse system and may also maximise above and below ground growth resources' utilization. In this respect, Sobkowiez [2006] further reports that two commonly used intercropping strategies entail planting a deep-rooted crop with a shallow-rooted crop, or planting a tall crop with a shorter crop that requires partial shade. In sub humid zones on acid soils competition between shrub-crop intercrops for light, nutrients and moisture can be very severe due to the effect of shading [Lawson and Kang, 1990], where crop yield reductions with increase in distance from the shrub rows have been reported [Netondo, 1991; Chirwa et al., 2007]. Since water and nitrogen are critical nutrients for plant growth and productivity for both the artemisia [Ferreira and Janick, 2009] and maize components [Bänziger et al., 1997] , competition can be more severe particularly in degraded sloppy areas of western Kenya with erratic rainfall or flat land with poorly drained soils and vulnerable to water logging.

Competition can occur between the same plant species, called intraspecific competition, or between different species, called interspecific competition. Ultimately, any multifunctional agriculture like an agroforestry intercropping system involving maize as a food crop and artemisia as a medicinal shrub will entail effective application of good agriculture practices (GAPs) for minimum pesticide usage. This will ensure the least possible impact on the environment and yielding a product that can be accurately traced from the field where it is grown to the consumer [WHO, 2003]. These practices should also be geared towards minimizing competition for plant growth resources, and enhance or compliment any positive component interactions that may exist.

Willey and Rao [1980] demonstrated that the competitive ratio (CR) could be useful in comparing the competitive ability of different crops, measure competitive changes within a given combination and determine what competitive balance between crop components is most likely to give maximum yield advantages. Competition may thus not always result in a poor performance of the intercrop since, apart from intra-specific competition, plants compete with individuals that are to some extent different while their resource requirements and their abilities for resource acquisition are not necessarily the same [Mkamilo, 2004]. Furthermore, the CR represents the ratio of individual LERs of component crops and takes into account the proportion of the crops in which they are initially sown [Putnam et al., 1985]. Since the CR targets a range of growth resources for competition, it may hence be more applicable interchangeably in 'Additive Series' and 'Replacement Series' of intercropping [Fukai and Trenbath, 1993] targeting interplant completion for one specific growth resource.

There is however scarce scientific evidence from sub humid regions on interactions between inter-plant competition with positive effects of shrubs and food crops; but once site specific optimisation of the cropping system is effected, the biological merit of intercropping makes it an important conservation farm practice for smallholder farmers, since the system permits nutrient recycling and reduces the need for herbicides in most cases [Van Noordwijk et al., 1999]. Infact, intercropping is usually considered as an option for integrated weed management, particularly in farming systems with low external inputs application [Itulya, 1998] and this may enhance system productivity through desired component 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 climate [FAO, 1978]. Maseno area lies at latitude 00o 01'N - 12'S and longitude 34o25'E-47'E but the altitude at the experimental site is 1500m a.s.l.; Latitude 00' 08''S, Longitude 340 35' 47''E; The experimental site receives a mean annual precipitation of 1750 mm with a bimodal distribution and mean diurnal temperatures of 28.7 deg.C. The soils in the area are classified as Acrisols, well drained, deep reddish brown clay, fairly acidic with pH ranging 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, relying on rainfall precipitation of two consecutive seasons interspersed with a brief dry spell or fallow period of 45 days. Land was prepared to fine tilth before planting of certified maize seed from Kenya Seed Company of variety H513 which matures in 120 to 150 days during both short rains (SR) and long rains (LR). Artemisia was then transplanted after the first weeding of maize when at knee high, when the young artemisia plants had grown to 50 cm in height with average of 15 true leaves, in accordance with the practices of Ferreira et al., [2005]. Artemisia seedlings were clustered in a temporary seed bed to secure uniform heights after which transplanting during both seasons took place after the rains had soaked the ground sufficiently to ensure the soil has high moisture content to promote seedling vigour. Holes were dug in the wet ground deep enough to hold all the artemisia roots vertically at the base so as to minimise bends on the roots, and pre-empt developing poor root systems that risk nurturing weak plants.

Diamonium phosphate (DAP) fertilizer was applied at planting of maize in all the plots at the recommended rate of 50 kg ha-1 while Calcium ammonium nitrate (CAN) was used for localized top dressing of maize only after 1st weeding also at the rate of 50 kg ha-1. The second season (LR) land preparation incorporated into the soil previous root stumps from the intercrop according to the practices of Okalebo et al., [1999] and Laughlin [1994] for maize and artemisia respectively. The second weeding in both seasons was done by manually uprooting the few weeds that emerged so as to minimise soil disturbance. The experiment had eight treatments, laid out as a randomized complete block design (RCBD) in 3 replicates, with three different intrarow spacings of the artemisia i.e. 0.75m, 0.9m, and 1m respectively, and uniform displacements of maize from the artemisia at 0.90m X 0.75m. The plant spatial arrangements were thus in 'Additive series' to result in a constant maize plant density in all treatments but varying artemisia population according to the method of Fukai and Trenbath, [1993]. Each plot replica size measured 6m x 4m including two control plots of pure stands for the treatments. The treatments 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 closure of artemisia in all treatments, only maize pure stand was subjected to 2nd weeding out of necessity because all artemisia treatments did not have subsequent weeds. Above ground plant biomass of both maize and artemisia was determined from an area of 24m2 at harvest and extrapolated to production ha-1. Artemisia was severed at the root apex and the harvested plants placed in brown paper bags after sun drying on black polythene sheets, after which they were weighed using an electronic weighing balance (Denver instrument model XL -31000) at Maseno botanical gardens. A similar treatment was also done for grain maize in which measurement was done with dry whole stalks severed at the root apex. Relative chlorophyll content was determined from an average of triplicate readings using a SPAD meter according to the method of Peng et al., [1992].These readings were taken to coincide with periods of optimal vegetative growth, for all the maize and artemisia intercrops and their respective pure stands. Artemisia plants were threshed whole and ensuing leaves air dried on black polythene sheets to 8% moisture content after which a representative sample from each treatment was analysed for artemisinin following the method of Christen and Veuthey [2001].

The Competitive Ratio (CR)

The competitive ratio (CR) is a measure of relative interspecies competition that indicated the number of times by which one component crop was more competitive than the other [Willey and Rao, 1980]. Measurements to demonstrate the existence or not of competition by comparing the CR among the intercrops in each treatment was therefore calculated following the method of Willey and Rao [1980]:

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

CRArtemisia = (LERArtemisia / LERMaize) x (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 maize and Artemisia in the mixture respectively. The LER was expressed by the equation suggested by Rao and Coe [1992]:

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

Where, Ci = crop yield under intercropping; Cs = crop yield under sole cropping; Ti = Shrub yield under intercropping; and Ts = Shrub yield under sole system.

Replacement Value of Intercropping (RVI)

As a measure of relative economic yield advantage of intercropping artemisia and maize, the Replacement Value of Intercropping (RVI) was determined for each treatment following the method of Van der Meer [1989] while substituting for artemisia and maize interchangeably:

RVIArtemisia = (a x PArtemisia + b x PMaize)/ a x MArtemisia - C (3a)

RVIMaize = (a x PMaize + b x PArtemisia)/ a x MMaize - C (3b)

Where:

PArtemisia and PMaize are the yields of artemisia and maize in the mixture respectively. MArtemisia is the mono crop yields of artemisia to be used interchangeably with MMaize for Maize; b and a are the market prices of maize and artemisia respectively; and, C is the variable cost associated with mono-cropping artemisia or maize interchangeably for replacement i.e. labour costs, cost of planting material and fertilizer. All the data collected was subjected to analysis of variance for RCBD using the Costat statistical computer package. The treatment and block means were separated using the least significant differences (LSD) test at 0.05%, while homogeneity of variances was verified by Bartlett's test.

A correlation analysis between chlorophyll (x) and artemisinin (y) content of artemisia treatments (n=7) at harvest time was done using Pearson's Correlation Coefficient (r):-

(4)

RESULTS AND DICUSSION

The data on plant heights, crown diameters, biomass yield, competitive ratio (CR), and replacement value of intercropping (RVI) obtained from the intercropping system of maize + artemisia in different spacing regimes, as well as the correlation between chlorophyll and artemisinin sequestration are presented in Figures 1, 2 and 3 as well as Tables 1, 2 and 3 respectively.

There was no significant effect (P>0.05) of spacing on Chlorophyll content of both artemisia and maize during both seasons. However, relative chlorophyll content appeared to decrease with increased plant maturity; and had a strong positive correlation ( r2=0.7) with artemisinin content (Fig. 1 and Table 3). The study produced a mean artemisinin yield of 0.8% which is above the world average of 0.6% reported by Ferreira and Janick [2009]. The short rains (SR) treatments had a significant effect on artemisinin yields (P>0.05) but lower content of 0.74% on average than during the LR season mean of 0.8% (Table 1). Apart from T8 (pure stand), T4, T3 and T2 exhibited the highest % artemisinin than the other treatments at 0.82%, 0.77% and 0.76% respectively. Since artemisinin is a secondary metabolite, climatic and geographical conditions, together with the way and time of planting and harvesting of A. annua can influence its production [Marchese et al., 2010]. This may help to explain why the artemisia crop grown in the short rains (SR) had higher biomass but less artemisinin content than the Long rains crop, on account of the precipitation variations experienced in the two seasons (Fig 2). The relatively high artemisinin content yielded in LR compared to SR may also have been occasioned by mild water logging in the former, to the extent that artemisinin sequestration may be related to the plants' mechanism of combating stress in this case occasioned by excess moisture. The higher rainfall recorded during the LR may thus have had an effect of inducing early flowering for increased sequestration of artemisinin at the expense of accumulating biomass. This is consistent with Marchese et al., [2010] who observed that biomass and artemisinin accumulation are greatly affected by water content in the soil during seedling stage; and reliable rainfall or irrigation potential is essential for 2-3 months after transplanting where distribution is more important than absolute amounts.

The plant content of artemisinin also varies during the season, independent of the developmental stage of the plant [Delabays et al., 2001] but in this study, the insignificant variation in yields within each of the two cropping seasons in artemisinin content is in concurrence with Ferreira et al., [2005] who reported that unlike seed, vegetetative propagation of artemisia will produce homogenous plants regarding artemisinin content. The positive correlation between chlorophyll content and artemisinin further suggests that Photosynthetic activity and sequestration of artemisinin are closely related in space and time within leaf lamellae. Since leaf chlorophyll content may be a function of both soil and leaf N at any point in time during active vegetetative growth, leaf thickness affects the estimation of leaf N because there is a strong linear relationship between SPAD values and leaf nitrogen concentration [Peng et al., 1992]. It may thus be possible to determine the plant's need for additional nitrogen fertilizer at a specific period in time during the growth cycle using SPAD values. The results indicate that the most appropriate harvesting time for artemisia was at the flowering stage, when the chlorophyll content was highest. In addition, the positive correlation between chlorophyll and artemisinin sequestration, suggests that it is possible to manipulate N application levels at critical stages of plant growth and development, in order to enhance leaf artemisinin concentration. Similar results have been obtained from artemisia by Banyai et al., [2010] through exogenous GA3 treatment. Artemisinin sequestration in leaves has previously been correlated with enzymatic activities in biosynthetic pathways [Wallaart et al., 2000] and hence by implication, some applications of chlorophyll measures can also be used in estimation of CR for intercropping systems where artemisia shrub is a component.

The Competitive Ratio (CR)

The CR is an ideal means of determining the degree to which one crop competes with the other in an intercropping system [Willey and Rao, 1980] so that if CR < 1, there is a positive benefit for maize relative to artemisia; and if CR > 1, there is a negative benefit to the secondary crop relative to the main crop [Putnam et al., 1984; Ghosh et al., 2004]. The different spacing regimes had a significant effect (P<0.05) on the competitive ratio of artemisia against maize among the intercrops during both seasons (Table 2).T3 exhibited the highest mean CR at 1.75 while T1 had the Lowest at 0.85 and were statistically different from the control. T1 maize (CRSR=1.5, CRLR=0.9) had a higher CR than artemisia (CRSR=0.67, CRLR=1.03). The results suggest that artemisia was a better competititor than maize in all treatments except T1. This implies that intercropping not only compares the competitive ability of different crops but also influences interspecies complimentarity. On average, artemisia was 1.3 (or 30%) more competitive than maize during both cropping seasons in this study. It is noteworthy from these CR values that maize exhibited significantly lower competitive ability than artemisia, even though it had the highest intercropping densities among the treatments and was provided with an early competitive advantage by being sown first semi-sequentially. Thus, both competition and interplant facilitation occurs in any intercropping system as was reported by Van der Meer, [1989]. Since complimentary or facilitative component interactions in T1 resulted in significantly higher maize biomass yields (Table 1), T1 intercrop arrangement may thus represent a propensity towards facilitative component interactions in favour of maize under this spacing regime, by exhibiting parity in competition with artemisia for growth resources. T1 intercropping arrangement could hence be more desirable for plant architectural arrangements if maize is to be considered as the main crop in the mixture for optimal yields. This is the opposite of T2, T3, T4, T5 and T6 when artemisia is targeted as the main crop. Shahid and Saeed [1997] also used CR values >1.0 to report that lentil was a better competitor when sown in association with wheat.

In general, the more a competitive ratio of each treatment approached unit value, the more the maize+artemisia intercrop balanced the competition between both species, suggesting further that there is an advantage in maize intercropped with artemisia in single hedgerows of each plant species. This yield advantage is probably due to different above-ground growth habits and morphological characteristics of intercrop components for causing optimal use of growth resources/ factors. This argument corroborates that of Awal et al., [2007], who report that as CR approaches unit values intercrop associations in barley+peanut effectively counterbalance the competition for growth resources between these species. A comparative maize+beans system in western Kenya was also found by Woomer et al., [2004] to allow larger light penetration, which likely benefits the maize as well as the legume. The rationale here is that since the two species rely on the growth resource differentially, for example light on account of their variation in growth rate, then facilitative component interactions may be possible.

In addition, the CR represents the ratio of individual LERs of component crops and takes into account the proportion of the crops in which they are initially sown [Putnam et al., 1984]. Higher CR values for artemisia suggest that the crop was a better competitor and utilized the growth resources more aggressively than maize, despite having been planted sequentially. Artemisia T3 had an exceptionally higher CR value than other treatments, suggesting that this intercropping regime represents a comparatively strong competitive ability for artemisia against maize, and is hence expected to reduce maize yields when grown as an inter­crop. A similar observation was made by May, [1982] while working on green grams (Phaseolus Aureus) and bulrush millet (Pennisetum Americanum) intercropping. Since both competition and complimentarity occurred in the maize+artemisia system, CR could also be useful in determining what competitive balance between components is most likely to give maximum yield advantages [Willey and Rao, 1980]. Since artemisia T3 had the lowest plant density (Table 1) among all treatments, another possible implication of high T3 CR values is that artemisia crops' in this spatial arrangement had more than ample space for growth and development, and may have concentrated on physiological mechanisms to optimise use of growth resources. Banik et al., [2000] also reported similar trends in competition and recorded depressed intercropping yields of mustard+pea, mustard+lentil, and mustard+gram mixtures over sole cropping. Generally, both complimentarity and competitive ability of component crops in this study forms a basis for recommending improved agroeconomic productivity. A similar proposition was made by Mkamilo [2004], in the ecological and socioeconomic context of maize+sesame intercropping. However, the mechanism of the different competitive abilities between artemisia+maize intercropped plant species has not been recorded, and the determination of this mechanism may assist further in manipulating interspecific competition for improved management practices that overcome production constraints to enhance intercrop productivity.

Replacement Value of Intercropping (RVI)

After canopy closure of artemisia, the maize+artemisia intercrop had no incidence of weed infestation in contrast to maize monocrop. As a measure of the relative complimentary effects of biological and economic yield potential of intercropping, Moseley [1994] proposed that the Replacement Value of Intercropping (RVI) by Van der Meer [1989] could be modified to better interpret food crop and shrubs intercropping improvements with predetermined fallow periods, and variable costs for labour and inputs used in the production process of the intercropping system. The RVI is thus the factor by which the polyculture is more or less valuable than the monoculture [Moseley, 1994]. In case the fallow period is less than unit value (i.e. one year) for either the monoculture or polyculture situation, then the RVI result will represent the extent to which the artemisia+maize intercrop is more or less valuable than the respective monocrop in an annual growth cycle. There was no significant effect of spacing on RVI (P>0.05) during both seasons (Table 1). Maize T7 produced the least RVI value of 1.1 was statistically different from the other treatments which recorded a mean RVI of 1.5. There was a significant effect of spacing on RVI (P<0.05) during both seasons. Artemisia T6 recorded the highest RVI value at 1.6 and was statistically different from T1 (1.3) but not different statistically from treatments 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 not statistically different from each other, but higher than T1 and lower than T8 the control, the mean RVI of 1.45 was used for artemisia from both the SR and LR seasons. This indicates that the profit from the intercrop is 45% higher than monocrops, to the extent that farmers who planted artemisia and maize could make a profit of 45% more than the farmers who are involved in monocropping of artemisia. This may be attributable to both the shortened fallow period and the consequent reduction or replacement in variable costs of labour and fertilizer that are associated with artemisia+maize intercrops. The man-days used in weeding of the intercrops may thus have been reduced considerably as a result of inherent ability of the companion crop of artemisia to suppress weeds. Since seasonal variation did not have a significant effect on RVI, another implication of high values may indicate efficient use of available time in the growing season since both crops can be grown twice annually with a shortened fallow period.

A high mean RVI of 1.55 from maize suggests that the increased benefit of the farmers involved in these intercrops may thus be facilitated by more efficient use of growth resources, as well as reduction in the variable costs upto a maximum of 55%, through manipulation of labour attributes like the weeding regimes that are reduced by half as a result of single labour input to cover two crops, and reduction in cost of fertilizer by single application in inter-cropping compared to monocropping. Complementarity of resource use may also have occurred through synergistic effect of applying commercial fertilizer to maize intercrops, as demonstrated by the significant effect of spacing (P<0.05) on biomass yields (Table 1). The RVI was determined in this trial to evaluate the relative economic yield advantage of maize and artemisia monocultures against respective intercrop replacements for the different spacing regimes, indicating which pattern was more or less profitable in the use of specific resources in the intercropping system. The increased profit (or gain) obtained in these intercrops may have been occasioned by shortening of the fallow period as was postulated by Moseley, [1994]; Or facilitated with reduction in variable costs by 45 to 55% as was similarly observed with Njoroge et al. [1993], who estimated the net benefit of intercropping coffee with food crops by accounting for total variable costs from the gross profits.

The mean RVI of 1.55 for maize recorded between the two seasons further indicates that the profit from the intercrop is 55% higher than maize monocrops meaning that farmers who planted artemisia and maize could make a profit of 55% more than the farmers who are involved in monocropping of maize. A similar argument may also hold for artemisia visa-a-vis maize, in addition to fact that lower RVI of artemisia (1.45) compared to maize (1.55) suggest that replacing maize with artemisia will not add value to maize monoculture. As labour becomes scarce with respect to available land, Intercropping may become more attractive due to the savings in cash inputs; and shrubs (as cash crop) increase in value relative to food crops cultivated by small scale farmers. By varying variable costs of maize and artemisia, successful intercropping may thus require that farmers design efficient systems in which complementary effects of intercropping on net returns exceed competitive effects as was reported by Ong, [1996]. While working on maize+okra intercrops, Alabi and Esobhawan [2005] also concluded that any strategy that reduces cost of production in these intercrops will increase its profitability and attractiveness to farmers. The RVI index captures some of the limitations associated with evaluating biological yield advantage by accounting for crop duration and the relative economic advantage of an AF intercropping system that includes variable costs in the production process.

CONCLUSIONS AND RECOMMENDATIONS

Intercropping in this study demonstrates complimentarity of maize and artemisia, as well as higher competitive ability of artemisia over maize in artemisia+maize system for higher income and food security, through an informed choice of spacing options to produce desired yields. The CR and RVI can aid researchers/extension agents in selecting intercropping practices that are most suitable on basis of optimal component interactions for recommendation to farmers. These indices provided an improved estimate of the cumulative effects of above-ground component interactions for relative advantage of an intercropping system employing short fallow periods. Due to the small average farm sizes in western Kenya and high capacity for intensification hence the need for optimal land use practices, the suitable spatial arrangements from this study ranges from T1, T3, T4, T5 and T6 depending on level of intensification and desired output by the farmer. For farmers with a preference for artemisia or maize, a spacing regime 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) respectively will be ideal; An artemisia+maize intercrop with a spacing regime of T6 0.9m Artemisia X 0.9m; Maize 0.90m X 0.75m is recommended for planting during the short rains' season. This spacing regime provided the highest replacement value of intercropping. For farmers with more intensified forms of Intercropping, a spacing regime 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 extra application of foliar fertilizer is applied at critical growth stages prior to harvest to produce high artemisinin content.

ACKNOWLEDGEMENTS

We thank Maseno University for availing the Research Farm to conduct the study and are grateful to the East African Botanical Extracts Ltd., for facilitating the use of their laboratories 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 replications

+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: Effect 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 yields(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

-

Ns

Ns

Ns

*

*

{Mean values in a column followed by dissimilar letter(s) indicate differences at 0.05 (*) level of significance.

Ns =Not significant at P>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. Effect 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

*

*

*

*

Ns

*

Season

Ns

*

{Mean values in a column followed by dissimilar letter (s) indicate significant differences at 0.05 (*) level of significance; Ns=not significant at P>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: Effect 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

ns

**

-

-

-

-

∑ (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 letter (s) indicate significant differences at 0.05 (*) level of significance; r2 = Pearson's correlation 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 effect of spacing Artemisia and Maize on Maize Plant Heights. Data points are the mean of three replications and bars represent standard errors.

+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 effect of spacing Artemisia and Maize on Artemisia Plant Heights. Data points are the mean of three replications and bars represent standard error.

+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)

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