Models for predicting the mass of apricot fruits by geometrical attributes (cv. Shams,Nakhjavan, and Jahangiri)

Fruits with the similar weight and uniform shape are in high demand in terms of marketing value. Therefore, an awareness of grading fruit based on weight is crucial. A part of this research was aimed to present some physical properties of three Iranian apricot cultivars (Shams, Nakhjavan, and Jahangiri). In addition, apricot mass was predicted by different physical characteristics with linear and nonlinear models as three different classifications: (1), single or multiple variable regressions of apricot dimensional characteristics. (2), single or multiple variable regressions of apricot projected areas and (3), estimating apricot mass based on its volume. All properties considered in the current study were found to be statistically significant at the 1% probability level. The highest and the lowest dimensional characteristics were found for Jahangiri and Nakhjavan cultivars, respectively. Sphericity values had significant difference among the tested cultivars. The latter property values were 0.971, 0.917, and 0.973 for Shams, Nakhjavan, and Jahangiri cultivars, respectively. Based on the results, the surface area of the Jahangiri cultivar was found to be 6458.35 mm², followed by the Shams and Nakhjavan cultivars, which had a mean of 6115.36, and 4395.25 mm², respectively. In this paper, the coefficients of static friction of the cultivars on three different surfaces are also reported. The results showed that mass modeling of apricot based on minor diameter and three projected areas are the most appropriate models in the first and the second classifications, respectively. In third classification, the best model was obtained on the basis of the actual volume as M = 0.997V_m + 0301, R² = 0.98, R.S.E. = 1.711 with R² = 0.98. It was concluded that the suitable grading system of apricot mass is based on minor diameter as nonlinear relation: M = 0.0019c^2.693, R² = 0.96, R.S.E. = 2.2.     

Transmutation and functional representation of heterogeneous landscapes

Models of local small-scale ecological processes can be used to describe related processes at larger spatial scales if the influences of increased scale and heterogeneity are carefully considered. In this paper we consider the changes in the functional representation of an ecological process that can occur as one moves from a local small-scale model to a model of the aggregate expression of that process for a larger spatial extent. We call these changes spatial transmutation. We specifically examine landscape heterogeneity as a cause of transmutation. Spatial transmutation as a consequence of landscape heterogeneity is a source of error in the prediction of aggregate landscape behavior from smaller scale models. However, we also demonstrate a procedure for taking advantage of spatial transmutation to develop appropriately scaled landscape functions. First a mathematical function describing the process of interest as a local function of local variables is defined. The spatial heterogeneity of the local variables is described by their statistical distribution in the landscape. The aggregate landscape expression of the local process is then predicted by calculating the expected value of the local function, explicitly integrating landscape heterogeneity. Monte Carlo simulation is used to repeat the local-to-landscape extrapolation for a variety of landscape patterns. Finally, the extrapolated landscape results are regressed on landscape variables to define response functions that explain a useful fraction of the total variation in landscape behavior. The response functions are hypotheses about the functional representation of the local process at the larger spatial scale.     

The relative influence of catchment and site variables on fish and macroinvertebrate richness in cerrado biome streams

Landscape and site-scale data analyses aid the interpretation of biological data and thereby help us develop more cost-effective natural resource management strategies. Our study focused on environmental influences on stream assemblages and we evaluated how three classes of environmental variables (geophysical landscape, land use and cover, and site habitat), influence fish and macroinvertebrate assemblage richness in the Brazilian Cerrado biome. We analyzed our data through use of multiple linear regression (MLR) models using the three classes of predictor variables alone and in combination. The four MLR models explained dissimilar amounts of benthic macroinvertebrate taxa richness (geophysical landscape R ² ≈ 35 %, land use and cover R ² ≈ 28 %, site habitat R ² ≈ 36 %, and combined R ² ≈ 51 %). For fish assemblages, geophysical landscape, land use and cover, site habitat, and combined models explained R ² ≈ 28 %, R ² ≈ 10 %, R ² ≈ 31 %, and R ² ≈ 47 % of the variability in fish species richness, respectively. We conclude that (1) environmental variables differed in the degree to which they explain assemblage richness, (2) the amounts of variance in assemblage richness explained by geophysical landscape and site habitat were similar, (3) the variables explained more variability in macroinvertebrate taxa richness than in fish species richness, and (4) all three classes of environmental variables studied were useful for explaining assemblage richness in Cerrado headwater streams. These results help us to understand the drivers of assemblage patterns at regional scales in tropical areas.     

Characterization of Triticum aestivum/Psathyrostachys juncea derivatives by genomic in situ hybridization

Using the genomic in situ hybridization (GISH) technique, one translocation line, seven translocation-addition lines, five translocation plus translocation addition lines and two ditelosomic addition lines were identified in backcross progenies of Triticum aestivum L. -Psathyrostachys juncea (Fisch.) Nevski intergeneric hybrids. No complete P. juncea chromosomes were detected in the 25 lines studied. The results suggest that intact P. juncea chromosomes may be difficult to isolate in a wheat background. This revised version was published online in July 2006 with corrections to the Cover Date.     

Breeding for yield and quality in durum wheat

Three populations of an intervarietal durum wheat cross IWP5308/PDW208, F₅, F₅BIP₁ (population derived after intermating in F₂) and F₅BIP₂ (population derived after intermating in BIPF₁), were evaluated under three different agronomic environments for mean performance and stability of genotypes for grain yield, yield components and protein content. Though the biparental progenies indicated a higher mean performance, they did not differ significantly from progenies of the pedigree method for almost all characters. The biparental progenies, however, produced a higher number of stable genotypes for grain yield per plant, grains per ear and protein content. The F₅ population had a higher number of stable genotypes for 1000 grain weight and number of tillers per plant. The BIP progenies also had a higher number of genotypes with above average mean performance, and many were significantly higher than the checks WH896 and WH542, compared with F₅ progenies. Hence, in spite of high G x E interactions, the use of cycles of biparental mating and selection of top yielding lines on the basis of yield components can enable selection of stable genotypes with high protein content. Number of tillers per plant and 1000 grain weight were the yield component characters which made maximum contribution to phenotypic stability of the genotypes. This revised version was published online in August 2006 with corrections to the Cover Date.     

GGE biplot analysis to evaluate genotype, environment and their interactions in sorghum multi-location data

Sorghum [Sorghum bicolor (L.) Moench] is a very important crop in the arid and semi-arid tropics of India and African subcontinent. In the process of release of new cultivars using multi-location data major emphasis is being given on the superiority of the new cultivars over the ruling cultivars, while very less importance is being given on the genotype?×?environment interaction (GEI). In the present study, performance of ten Indian hybrids over 12 locations across the rainy seasons of 2008 and 2009 was investigated using GGE biplot analysis. Location attributed higher proportion of the variation in the data (59.3–89.9%), while genotype contributed only 3.9–16.8% of total variation. Genotype?×?location interaction contributed 5.8–25.7% of total variation. We could identify superior hybrids for grain yield, fodder yield and for harvest index using biplot graphical approach effectively. Majority of the testing locations were highly correlated. ‘Which-won-where’ study partitioned the testing locations into three mega-environments: first with eight locations with SPH 1606/1609 as the winning genotypes; second mega-environment encompassed three locations with SPH 1596 as the winning genotype, and last mega-environment represented by only one location with SPH 1603 as the winning genotype. This clearly indicates that though the testing is being conducted in many locations, similar conclusions can be drawn from one or two representatives of each mega-environment. We did not observe any correlation of these mega-environments to their geographical locations. Existence of extensive crossover GEI clearly suggests that efforts are necessary to identify location-specific genotypes over multi-year and -location data for release of hybrids and varieties rather focusing on overall performance of the entries.     

Developing standardized methods for breeding preharvest sprouting resistant wheat, challenges and successes in Canadian wheat

Preharvest sprouting (PHS) in spring wheat (Triticum aestivum L.) and durum wheat (T. turgidum L. var durum) causes significant economic losses due to a reduction in grain yield, grain functionality and viability of seed for planting. Average annual estimated losses in Canada are about $100 million. Genetic resistance to PHS reduces these losses. Development of PHS resistant cultivars is complicated by the effects of factors under genetic control, such as spike morphology, seed dormancy, environment, and kernel diseases. Resistance to PHS has been a breeding priority since the late 1960s. Development of RL4137, which is the primary source of PHS resistance in the Canada Western Red Spring market class, has led to cultivar improvements. A white-seeded derivative of RL4137 is the primary source of PHS in the Canada Prairie Spring White and Canada Western Hard White Spring wheat market classes. Procedures to select for PHS resistance vary among breeding programs, market classes and by degree of inbreeding. Methods include artificial sprouting of intact spikes, germination tests, natural weathering in field trials, artificial weathering trials, and indirect assessment of sprouting by measuring Hagberg falling number. Although many genetic loci have been attributed to preharvest sprouting resistance, application of molecular markers is currently limited due to the complex inheritance of the trait. In Canada, cultivars are characterized for their relative level of PHS resistance and the information is made available to producers.     

An experimental test of the habitat amount hypothesis reveals little effect of habitat area but transient or indirect effects of fragmentation on local species richness

Landscape Ecology - The habitat amount hypothesis (HAH) posits that local species richness is driven more by the amount of habitat in the surrounding landscape than by local patch size or habitat...     

Greenhouse tomato limited cluster production systems: crop management practices affect yield

Limited-cluster production systems may be a useful strategy to increase crop production and profitability for the greenhouse tomato (Lycopersicon esculentum Mill). In this study, using an ebb-and-flood hydroponics system, we modified plant architecture and spacing and determined the effects on fruit yield and harvest index at two light levels. Single-cluster plants pruned to allow two leaves above the cluster had 25% higher fruit yields than did plants pruned directly above the cluster; this was due to an increase in fruit weight, not fruit number. Both fruit yield and harvest index were greater for all single-cluster plants at the higher light level because of increases in both fruit weight and fruit number. Fruit yield for two-cluster plants was 30% to 40% higher than for single-cluster plants, and there was little difference in the dates or length of the harvest period. Fruit yield for three-cluster plants was not significantly different from that of two-cluster plants; moreover, the harvest period was delayed by 5 days. Plant density (5.5, 7.4, 9.2 plants/m2) affected fruit yield/plant, but not fruit yield/unit area. Given the higher costs for materials and labor associated with higher plant densities, a two-cluster crop at 5.5 plants/m2 with two leaves above the cluster was the best of the production system strategies tested.     

Hybrid detection and characterization of Curcuma spp. using sequence characterized DNA markers

The tropical flower Curcuma alismatifolia of the family Zingiberaceae is widely valued as a cut flower and potted plant due to its range of vibrant colors and large long-lasting inflorescences. Much of this diversity has been cultivated through extensive hybridization of wild varieties since hybrids often exhibit dramatic phenotypic differences from the parents. This phenotypic diversity though has led to difficulties identifying and classifying the relatedness of Curcuma varieties particularly between hybrids. One Curcuma variety called ‘Patumma’ is of particular importance since it has strong stalks, large symmetric inflorescences, is moderately resistant to fungal blight, has a high yield, and has been used to produce numerous high quality hybrids. Since Patumma is one of the key Curcuma varieties from which many hybrid crosses and induced mutation varieties were developed, we chose it as a target to be characterized using a molecular marker. Starting with a set of 11 unique decamer primers, polymorphic bands ranging from 100 to 2500 base pairs were used to examine 20 Curcuma varieties from which banding patterns of interest were selected for conversion to the more reproducible and robust sequence characterized amplified region (SCAR) markers. In particular, one SCAR marker amplified a region 600 bp in length which was conserved in all Patumma varieties and hybrids and as an independent test did not amplify an additional series of 24 distinct Curcuma varieties. Since new varieties of Curcuma are often dissimilar from their progenitors, this genomic analysis allows a cost-effective morphologically independent characterization of Curcuma hybrids.