406 60606 and 74074 plants/ha) arranged in a factorial randomized complete block design with three replications. The results indicated that corm size had a highly significant (p<0.001) influence on plant height, leaf number, shoot number , leaf area index, corm and cormels number/plant, corm and cormels yield/ha of taro. All the parameters were increased with increased in corm size. Plant population density exertsignificant influence (p<0.001) on all the studied parameter except on plant height and number of leaf/plant.The interaction effect of corm size and population density was none significant on all the studied parameters. The highest average corm yield/ha (44.07 t/ha) was achieved at a population of 60,606 plants/ hausing seed corms having 51-100g. These could be recommended for farmers in production area similar with the study site.
equivalent to a yield of 21,000 kg sugar per hectare. Agricultural factors such as spacing have critical effects on quantitative and qualitative characteristics of plants (Naghdi badi et al., 2004). Leaf yield increased with increasing density up to 83000 and 111000 plant/ha of Stevia for the first years of production (Madan et al., 2010). The optimum per acre plant population is pre- requisite for higher yield of Stevia like other plants. It enables the plant to utilize land, light and other input resources uniformly and efficiently. Increasing plant population per unit area beyond a certain limit results in competition among the plants for sunlight, nutrients, moisture etc. and may cause severe lodging. So it is imperative to develop such a spacing pattern which may help avoiding excessive crowding and thereby enabling the Stevia plant to utilize these resources more effectively and efficiently towards increased production. Plant density is one of the most important cultural practices determining herbage yield, as well as other important agronomic attributes of this crop (Taleie et al., 2012). Linear increase in biomass yield has been reported with increase in plant density until other production factors become limiting (Norsworthy and Emerson, 2005). The effect of plant spacing on growth, and biomass yield of Stevia has not been intensively investigated. Stevia in Ethiopia being a new medicinal plant most of the farmers and large scale producers are not aware of its basic agronomy and growing requirements. Keeping in view the potential of Stevia, the present study was planned with the objective to determine intra-row and inter-row spacing of optimum plant population density for obtaining maximum biomass production of Stevia.
To the best of our knowledge, this study was the first of its kind to investigate the effect of variation in plant population density on biomass production of a large perennial that had demonstrated high biomass production and associated enhancement of ecosystem goods and services in the northern Great Plains  and Midwest . In its natural environment, we have observed cup plant occur- ring in relatively dense stands or in isolated clumps. Its growth habit tends to be caudexal and very erect. Individual proaxes produce three short rhizomes during autumn; generally, only one or two produces a new shoot the following spring (A. Boe, unpublished data).
produced per g nitrogen absorbed by plant. It may also be expressed as grain yield per unit of available nitrogen (van Beem & Smith, 1997). In cereals, NUE hardly exceeds 50% under field conditions. It varies from 25-34%, with maize being no exception (Mosier, 2002; Raun & Johnson, 1998). Under various environments, predicting NUE for maize is difficult due to the possibility of significant interactions between management practices such as plant density and N fertilization (Ciampitti & Vyn, 2011). Magen and Nosov (2008) indicated that a 1% increase in NUE is worth as much as US$ 234,000,000. In a study conducted by Muchow and Davis (1988), RUE increased with higher rates of N applied and maximum RUE was greater in maize than in sorghum. Thus, maize when compared with sorghum is more responsive to N, leading to higher NUE, averaging 55kg DM/kg N applied for the initial 50kg N/ha applied (Williams et al., 2010). Plant population density affects the ratio of total above ground N content to green area index such that the ratio decreases with increasing plant densities (Barbieri et al., 2006). The NUE of maize increases with narrow row spacings (12-15%) which is often expressed as dry matter or grain yield per unit of available N due to the increased recovery efficiency (Barbieri et al., 2006).
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In both harvesting seasons and pooled mean analysis result showed that, Above ground biomass and Leaf fresh weight were highly significantly (p>0.01) influenced by intra-row, inter-row spacing and their interaction. These indicate that the effects of different levels of intra-row spacing were affected by different levels of inter-row spacing. The maximum above ground biomass 72605 gm and leaf fresh weight 9510 gm were observed at 40*60cm and the minimum above ground biomass 15726.17 gm and leaf fresh weight 3162.39 gm were observed at 100*120 intra and inter-row spacing. The increasing trend of above ground biomass and leaf fresh weight per hectare observed in this study is in agreement with the result of Rao (2002) on rose scented geranium, Zewdinesh (2010) on A. annua. Similarly, the current investigation supports the previous research findings conducted by (Abebe Terefe, 2007) on Vernonia galamensis. Highest herbage resulted by the highest population (narrow spacing) and the lowest ones resulted by the lowest population (wider spacing). This is probably due to the occurrence of higher number of branch and leaves contributed from greater number of plants per unit area; resulted in higher use of light in that experiment.
Producers need information about cost and re- turn trade-offs with different PPDs to evaluate the economic feasibility of UNRC and to optimize net revenues from this system. The objective of this study was to evaluate the impact of PPD on net revenues for UNRC production. Factors considered in this analysis were lint yield response to PPD, lint price adjustments for ﬁber quality as inﬂuenced by PPD, plant survival rates, transgenic cultivar seed costs and technology fees, and the potential effects of PPD on ﬁnger stripper harvest efﬁciency as measured by vegetative branch size.
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generally characterized by uncertain rainfall distribution of 300-500 mm, a hot dry spell which extends from March to May (Alhassan et. al., 2012) and limited diversity in the choice of the associated crops or varieties. Desert gourd or bitter gourd (Citrullus colocynthis (l.) Schrad) popularly known as guna melon in Nigeria belongs to the family Cucurbitaceae is widely grown in Yobe state, north-east, Nigeria. Guna melon, a drought-tolerant; trailing crop that requires little water continues to grow and fruit virtually up to the on-set of the next rainy season. It provides effective soil cover in the season when most other vegetation cover had dried -up, also protect the soil from adverse wind erosion and increase the soil organic matter when the dead guna plant decomposes (NEAZDP, 1992; Gwandzang, 1995, Amshi and Odo (2001). The economic importance of guna melon lies in their seeds, which are processed to produce edible oil, cosmetics, pharmaceuticals and other industrial purposes (Penuel et. al., 1998, Menon et. al., 2014 and Amshi, 2015). Amaza et. al., (2006) further reported that guna melon production in semi-arid environment ensures suitable subsistence returns from low inputs. The choice of pearl millet intercropped with guna melon was made to determine whether guna melon component could form the basis for an alternative to pearl millet-cowpea intercropping system which had been very popular in the state, but recently suffering persistent yield reduction due to environmental hazards. In pearl millet – guna melon intercropping, the combined yields of the crops could be greater than either of the sole crops due to increased plant population. Consequently, the need to increase and sustain the growing interest towards cultivation of guna melon (oil seeds) as pearl millet (food grains) intercrop cannot be over emphasized. Unfortunately, little is currently known about the extent some improved cultural practices could play in the productivity in the semi-arid zone of Nigeria. An understanding of the effect of plant population density on the various components may therefore help in evolving an efficient crop yield. In view of the above, a two-year study (2017 and 2018 cropping seasons) was conducted to identify the attributes that could be considered agronomically desirable to suit the farmers’ needs and objectives.
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density increased with increasing in corm size at all the measurement months (Table 3). The highest mean shoot number/plant at all three growth periods were produced by seed corms with 201-250 g sizes. Shoots number/plant decreased with the decrease in size of corms and reached a minimum in seed corms with ≤ 50 g. An increase in corm size from 50 to 250 g increased mean shoot number/plant by 35.94, 29.17 and 26.72% at 2, 4 and 6 MAP, respectively. The largest number of shoot is produced by large seed corms. The finding confirms the results obtained by (Ameyaw et al., 1991) who reported that the number of shoot per plant increased as the size of sett increases in yam plant. Similarly, Onwueme (1978) reported that the number of sprout/sett in yam crop increased with sett size. The increase in shoot numbers is apparently due to greater number of potential buds and more assimilates being available in large sized seed corms. Likewise, large seed corms emerged earlier than smaller seed corms (Table 2).
Seeding rates which determine the population density and consequently the area available to individual plant has been shown to affect crop growth and yield performance (Ntare, 1990). High density cropping in groundnut is known to reduce weed competition for space and growth resources (Lee et al., 1994). It was reported by Dalley et al. (2004) and Yelverton & Coble (1991) to exhibit greater light interception compared to low density cropping. The adoption of high density cropping has primarily been driven by the potential for higher yields obtained from such systems compared to low density production systems. Reports of studies confirming high yields in high density corn and soybean (Mickelson et al., 1997) attributed such performance to decreased weed competition, disease and pest occurrence, and increased light interception (Board et al., 1992; Wells et al., 1993; Dalley et al., 2004). A decade of groundnut research in Senegal revealed a continuous increase in pod yield with increasing plant population density, which became multiples with the addition of chemical fertilizers (Schilling, 2002). Buchanan & Hauser (1980) had earlier reported higher yields (42 to 52 %) as density increased. In another study, Norden & Lipscomb (1974) reported that pod yield in high density cropping system was 16 % higher when compared to conventional low density system. Similarly, Duke & Alexander (1964) had reported that yields from large seeded Virginia bunch types were 14 % higher in high density compared to the conventional low density crop. A study by Jaaffar & Gardner (1988) showed that higher seeding rates gave greater ground cover, leaf area indices, canopy light interception, crop growth rates and ultimately higher pod yields when compared to conventional low density groundnut crop. These findings were later confirmed by Stewart et al. (1997) and recently by Ahmad et al. (2007).
The results of this experiment are straightforward: increasing population density leads to an increasing yield of sweet corn ears that could be sold, with a corresponding decrease in the overall quality of the ear of corn. In the world of processing sweet corn, recent studies have indicated that maximum yield occurs at ultra-high population densities. An experiment conducted in Washington state in 2012 on irrigated processing sweet corn indicated that the highest yields of processing sweet corn were achieved at the ultra-high population density of 86,450 plants ha -1 (Waters et al., 2012). This result corresponds with the predictions of the regression analysis of this experiment: that maximum yield of ears greater than 17.8 cm would occur at a predicted ultra-high population density, 81,700 plants ha -1 in the case of this experiment. Had the focus of this experiment been on processing sweet corn, where ear quality is less of a factor in determining value, the recommendation of this experiment would be that a plant population density of 79,040 plants ha -1 would be ideal for this particular producer. This experiment was not conducted on processing sweet corn, however, and for fresh-market sweet corn, there are more factors at play at determining an ideal plant population than just yield.
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Poor Cry1Ac protein expression was com- mon in the first years of transgenic (Bt) cotton in Australia, when single-gene Cry1Ac cotton (called Ingard in Australia and Bollgard in USA) was grown. Two-gene cultivars (called Bollgard II in both countries) show enhanced Cry1Ac protein expression compared with Ingard cultivars. En- vironment, soil properties, and agronomic man- agement are believed to affect Cry1Ac protein expression. This research evaluated the impact of crop nutrition, plant population density, light in- tensity, water management, herbicide application, soil fertility, plant growth regulator application, and cotton cultivars on Cry1Ac protein expression in field and glasshouse experiments, as measured in cotton leaves using commercial quantitative ELISA assays. Cultivars provided the major source of variation in leaf Cry1Ac protein expres- sion. Cry1Ac protein concentration ranged from 0.27 to 6.01 mg kg -1 in 15 experiments conducted
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In the polyhouse photosynthetically active radiation (PAR) was quantified within canopies simulated by arrang- ing container grown plants along a bench. This was done to estimate how population density might affect light within the canopy micro-environment in field grown plants, and to help select population densities for field ex- perimentation. The container grown conventional or erect leafed mutant sorghum lines were arranged along two benches centered within and along the north-south axis of the polyhouse. Forty eight plant containers were ar- ranged in a 6 × 8 rectangular array with the long axis of the array oriented north-south. The benches were placed along the center-line of the polyhouse one to the north of the other with a four meter space between the two ca- nopies to minimze shading. Linear quantum sensors were horizontally and equidistantly suspended from a structural central beam within each canopy at 30, 60, 90, and 120 cm above the surface of the rooting medium to quantify PAR. A separate linear PAR sensor was mounted above the canopy on the horizontal lower chord of the polyhouse roof truss. The ambient light sensor was oriented, east-west, perpendicular to the canopy PAR sensors.
Current land devoted to organic soybean is approximately two percent of total soybean production in the USA. This small hectarage may be indicative of market demand, but may also reflect that conventional cultivars are not well suited to high yield production under organic conditions. The results of the present study indicate that high-population planting density and larger planting seed, coupled with the appropriate genotype, can enhance early season ground cover in ultra-narrow rows, and potentially improve weed control and overall profitability. In organic systems, farmers often save or ‘brown bag’ their seed from one season to the next, because typically most non-GMO cultivars are not patented and, thus, no legal restrictions apply. If a farmer sorted out and saved the largest seed size of their cultivar for planting seed, then this tactic may offer an easy approach for optimizing an ultra-narrow row spacing and high density production system.
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Fig. 4 Mean number (±S.E.) of Amrasca devastans on different true alternative host plant types (pooled data for 2010 and 2011, nymphs plus adults). The numbers of A. devastans differed significantly across host plant types overall but comparisons were not significantly different between vegetables, crops and ornamentals, and not also between weeds and ornamentals.
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We performed no-choice experiments in clean gauze covered cages (1 m × 1 m × 1 m) in a sandy field where all vegetation had been removed. The results of the preference test described above showed that O. asiati- cus tended to be a grass (S. Krylovii, L. chinensis and C. squarrosa) specialist that avoided forbs (A. frigida, N. pectinata, C. microphylla, C. ammannii, and K. pros- trata). We used a subset of different preferred grasses and a forb, specifically S. krylovii, L. chinensis (grasses), and A. frigida (forb), for further investigation. We collected plants from the grassland close to the field and placed 20 g of each single plant species into plastic containers (14 cm × 20 cm) filled with distilled water. The containers were buried so that the top of the containers were flush with the ground surface. We placed 20 individual third- instar grasshoppers from the grasshopper pool (sex ratio 1:1) into each cage. The numbers of surviving grasshop- pers in each treatment were recorded every 3 days until grasshoppers reached adulthood. After the grasshoppers reached adulthood, we conducted a plant consumption test. During the consumption test, we weighed an addi- tional five bundles of each plant species before adding plants to the cages without grasshoppers. After weigh- ing, plants were dried for 48 h and weighed again to esti- mate original dry mass (O) and the water content of the plant material. The remaining portions of uneaten leaves (U) were collected after 48 h, dried for 24 h at 80 °C, then weighed to determine the plant dry mass consumed. Plant consumption (C) was calculated by subtracting the dry mass of the uneaten leaves (U) from the dry mass of the original (O). We calculated the dry plant: wet plant ratio from a control group of an additional five leaf bun- dles for each plant species that were treated equivalently but without grasshoppers. Every 2 days, we quantified the amount of plant material consumed by the grasshoppers and replaced old leaves with new leaves of the same spe- cies. The consumption test lasted 2 weeks. We repeated the experiment five times so that the results of each 48-h foliage replacement provided three data sets for analysis.
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Also, the migration loss of cities between 50 thousand and 100 thousand inhabitants intensified. Thus, in a short period from 1991 to 1994 the traditional pattern has been totally changed: small communities/towns having from 2000 to 5000 inhabitants gain via migration, while towns over 20 thousand lose their population through migration movements (Table 3). This pattern can be explained, in part, by the relationship between settlement size and economic performance. Some of the highly urbanised regions (having big centres) suffer the negative consequences of economic restructuring (the decline of employment in coal mining and heavy industry) which is reflected to some extent, in net migration losses. On the other hand, small size settlements in western and southern borderland districts take advantage of their geographical position - to profit in the broad sense of the word from close contact with Germany and Austria. The collapse of housing construction has mainly hit the largest cities, where the construction of traditional housing estates (prefabricated block of flats) has nearly ceased. The construction of individual family houses in the hinterlands of the largest cities and in rural areas has decreased much less. Hence, migration growth of smaller towns partly due to difficulties in migrating out of these areas rather than with their increasing migration attractiveness as such. On the other hand, migration losses of the highly urbanised areas are not caused by increasing intensity of outmigration but decreasing in-migration streams (see also Cermak, forthcoming).
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In this paper, drawing from population dynamics and density dependency literature (Organizational Ecology literature in general), we examine the interaction between two different hotel populations. Five-star hotels have either a chain affiliation or they are independent hotels. We examined the hotel populations between 1976 and 2014 because the first exit from the population was in 1990, and hotels organizations that exited from the industry were established in 1976. Crisis that were experienced in the country and had negative effects on the hotel populations are regarded as period effects. Hotels with chain have the advantage of having operating knowledge and economies of scale. They have high reputation. They also can access vital resources to continue their life. These factors contribute to the viability of the chain members. Westudied the population of chain hotels and the population of independent hotels to see the interactions between populations. To be able to do this, we compute the densities of the two populations using the number of entries and exits into or out of the populations, room capacities and geographic locations of the hotels for each year. Based on these findings, we exhibit the differences between the two populations in terms of densities, size, and location. Our examination of five-star hotel populationstellsus when the density of chain hotels growths above average, the density of independent hotels declines. The study also indicates when the density of independent hotels growths above average, the density of chain hotels is not affected. Based on our examination of five-star hotel populations between 1976 and 2014 and by drawing from the theory, we formulated exploratory hypotheses to be tested on how the interaction between the two populations may affect their founding rates. Organizational strategists, thus, may benefit from the future findings when they are confronted with location choices and also organizational form choices for their establishments.
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The National Statistical Service of Greece has recorded the data used here. They refer to the Census of the last three decades (1980, 1990, and 2000) for all Greek prefectures (see Figure 1). The data are provided by All Media Database  (Profile of Greek Regions) 2 . For the purpose of the analysis we code each of the 50 prefectures as shown in Table 1. This table also provides information on key characteristics of the prefectures (NUTS 3) (population, area in km 2 , area in miles 2 ). These prefectures form thirteen administrative regions (NUTS 2), whose basic characteristics are also presented in Table 1. The region of Attica is the most populated region with 3.522.769 citizens, whereas the region with the lower levels of population are been recorded for the region of North Aegean (containing the prefectures of C50-HIO, C31-LES and C42-SAM) with 198.241 recorded citizens 3 .
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Abstract Population density models that are used to describe the evolution of neural populations in a phase space are closely related to the single neuron model that de- scribes the individual trajectories of the neurons of the population and which give in particular the phase-space where the computations are made. Based on a transforma- tion of the quadratic integrate and fire single neuron model, the so-called theta-neuron model is obtained and we shall introduce in this paper a corresponding population density model for it. Existence and uniqueness of a solution will be proved and some numerical simulations are presented. The results of existence are compared to previ- ous results of existence or nonexistence (burst) for populations of leaky integrate and fire neurons.
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The seeds produced at lower density were superior due to over all better growth of the individual plants which explore higher inputs. Also, supply of assimilates to the seeds under low population was more which inhibited abscission layer formation and delayed senescence and thus chlorophyll content of seeds was improved.