Leaf Dimensions Research Articles

Growth and morphological responses of Halophila beccarii to low salinity

Halophila beccarii Ascherson is classified as a threatened seagrass species by IUCN because of the reductive tendency of ​​its distribution area. This seagrass is considered a euryhaline species adapted to a wide range of salinities from freshwater and brackish water to marine water. Previous studies showed that the species tends to grow better under low salinity; however, its optimum salinity has not been determined. In Vietnam, H. beccarii grows in habitats with low salinity (0–20 ppt). The results show that salinity affects the growth, survival rate, shoot density, biomass, and morphological characteristics of the grass. The leaf dimension is more prolonged and broader; the petiole and shoot length are longer at 10 ppt salinity. In contrast, both the number of shoots and biomass peak at 5 ppt and decrease at lower and higher salinities. The study reveals that H. beccarii can grow better under mesohaline conditions than freshwater and hypersaline conditions with an optimum salinity at 5–10 ppt. These findings would explain the species’ distribution dynamics in coastal environments and be helpful information for conserving the seagrass populations in habitats with fluctuating salinity as coastal lagoons in Central Vietnam.

Hydroponic kale: effects of row spacing and number of plants per cell on yield and quality

The consumption of kale is increasing, and it is sold in bunches of adult leaves. However, there is the possibility of growing in bunches of young plants in a hydroponic system with several advantages, but different densities were not tested. The aim was to generate information on the hydroponic cultivation in NFT (nutrient film technique) of curly kale in bunches of young plants, with a study of spacing (0.07, 0.11, 0.15 and 0.20 m) and several plants per cell (one, two, three and four), aiming to improve the productivity, quality and homogeneity of kale. A split-plot experiment was executed in randomized block design, with four repetitions. Agronomic characteristics were measured, and bromatological and nutrient analyses were performed. Plant height and productivity were higher with smaller spacing. With fewer plants per cell, the leaf dimensions were higher and more homogeneous were the different plants of the same cell. With four plants per cell, it was recorded, on average, 19.3 g of fresh weight of shoot in the largest plant and 6.4 g in the smallest one. The bromatological and nutrient content was consistent with literature reports. Thus, the desired product in cultivating hydroponic kale in bunches of young plants is decisive for choosing spacing and numbers of plants per cell. Larger leaves can be harvested with fewer plants per cell than more plants per cell and vice versa. The use of smaller spacing increases productivity. The hydroponic system is technically viable to produce curly kale, providing plants with good nutritional quality.

Impacts of habitat variability on the phenotypic traits of Aconitum violaceum Jacq. ex Stapf. at different altitudes and environmental conditions in the Ladakh Himalaya, India.

Aconitum violaceum Jacq. ex Stapf is endemic to the Northern Himalayan regions of India, Pakistan and Nepal. To adapt and endure the rigorous stressful situations, phenotypic features of a specific plant species vary across different climatic conditions and elevations. The aim of this study was to reveal the impact of altitude and environmental conditions on the morphological attributes of a threatened species A. violaceum. Plants at high elevations (Maan-man, 4010m asl) were short; whereas the plants grown at ecological conditions of population-I (Khawous, 3220m asl) showed better growth and development in all morphological attributes. It has been noticed that there is a considerable reduction in the plant height, rhizome, leaf dimension, flower number and leaf number at higher elevations. Regression analysis and Pearson’s correlation coefficient demonstrated a positive relationship between plant height and all other morphological attributes. Principal component analysis (PCA) revealed that the habitat, ecological conditions and elevations of population-I (Khawous) and Population-II (Numsuru) were proved to be relatively better for the luxuriant growth and development of an endemic plant species A. violaceum. From the observations, it can be inferred that A. violaceum grows successfully at an elevation ranges between 3000 to 3500m ASL. This study provides a comprehensive account of phenotypic variability concerning environmental conditions and suggested a suitable environment for sustainable cultivation of this important medicinal plant species in the Ladakh Himalaya.

Scaling the leaf length-times-width equation to predict total leaf area of shoots.

Background and AimsAn individual plant consists of different-sized shoots, each of which consists of different-sized leaves. To predict plant-level physiological responses from the responses of individual leaves, modelling this within-shoot leaf size variation is necessary. Within-plant leaf trait variation has been well investigated in canopy photosynthesis models but less so in plant allometry. Therefore, integration of these two different approaches is needed.MethodsWe focused on an established leaf-level relationship that the area of an individual leaf lamina is proportional to the product of its length and width. The geometric interpretation of this equation is that different-sized leaf laminas from a single species share the same basic form. Based on this shared basic form, we synthesized a new length-times-width equation predicting total shoot leaf area from the collective dimensions of leaves that comprise a shoot. Furthermore, we showed that several previously established empirical relationships, including the allometric relationships between total shoot leaf area, maximum individual leaf length within the shoot and total leaf number of the shoot, can be unified under the same geometric argument. We tested the model predictions using five species, all of which have simple leaves, selected from diverse taxa (Magnoliids, monocots and eudicots) and from different growth forms (trees, erect herbs and rosette herbs).Key ResultsFor all five species, the length-times-width equation explained within-species variation of total leaf area of a shoot with high accuracy (R2 > 0.994). These strong relationships existed despite leaf dimensions scaling very differently between species. We also found good support for all derived predictions from the model (R2 > 0.85).ConclusionsOur model can be incorporated to improve previous models of allometry that do not consider within-shoot size variation of individual leaves, providing a cross-scale linkage between individual leaf-size variation and shoot-size variation.

Ethnobotanical Diversity of Cassava (Manihot esculenta Crantz) in the Peruvian Amazon

Cassava is a key tropical crop that serves as a major source of nutrition throughout equatorial South America, Africa, and Asia. Genetic and paleoethnobotanical findings indicate that it was first domesticated on the southern margin of Amazonia ~10,000 years ago. However, anthropogenic processes underlying its subsequent diversification remain unclear. To shed light on them, we investigated agricultural practices and phenotypic variation in cassava on the upper Amazon River, in Loreto, Perú. We interviewed subsistence growers on five Amazon tributaries and collected data on the husbandry, morphology, and nutritional composition of their crops. We found 45 distinct cultivars. Many of their morphological features, such as stature and leaf dimensions, exhibited expected phenotype–phenotype associations. However, starch content showed no association with any other phenotype (mean p = 0.57), suggesting it has been under selective pressure exerted by growers. In addition, all cultivars’ tubers had cyanide content under 25 ppm, a low level of toxicity by global standards. Evidence of sexual reproduction and cultivar hybridization was common and a probable source of new variation. However, cultivars from different rivers showed little evidence of differentiation, possibly as the result of human transport. Thus, human influences in the region simultaneously enhance and constrain variability in the crop.

First Form, Then Function: 3D Reconstruction of Cucumber Plants (Cucumis sativus L.) Allows Early Detection of Stress Effects through Leaf Dimensions

Detection of morphological stress symptoms through 3D examination of plants might be a cost-efficient way to avoid yield losses and ensure product quality in agricultural and horticultural production. Although the 3D reconstruction of plants was intensively performed, the relationships between morphological and physiological plant responses to salinity stress need to be established. Therefore, cucumber plants were grown in a greenhouse in nutrient solutions under three salinity treatments: 0, 25, and 50 mM NaCl. To detect stress-induced changes in leaf transversal and longitudinal angles and dimensions, photographs were taken from plants for 3D reconstruction through photogrammetry. For assessment of physiological stress responses, invasive leaf measurements, including the determination of leaf osmotic potential, leaf relative water content, and the leaf dry to fresh weight ratio, were performed. The transversal and longitudinal leaf dimensions revealed statistically significant differences between stressed and control plants after 60 °Cd (day 3) for the leaves which appeared before stress imposition. Strong correlations were found between the transversal width and some investigated physiological traits. Morphological changes were shown as indicators of physiological responses of leaves under salinity stress.

Morphological and biochemical responses of tropical seagrasses (Family: Hydrocharitaceae) under colonization of the macroalgae Ulva reticulata Forsskål.

BackgroundCoastal land development has deteriorated the habitat and water quality for seagrass growth and causes the proliferation of opportunist macroalgae that can potentially affect them physically and biochemically. The present study investigates the morphological and biochemical responses of seagrass from the Hydrocharitaceae family under the macroalgal bloom of Ulva reticulata, induced by land reclamation activities for constructing artificial islands.MethodsFive seagrass species, Enhalus acoroides, Thalassia hemprichii, Halophila ovalis, Halophila major, and Halophila spinulosa were collected at an Ulva reticulata-colonized site (MA) shoal and a non-Ulva reticulata-colonized site (MC) shoal at Sungai Pulai estuary, Johor, Malaysia. Morphometry of shoots comprising leaf length (LL), leaf width (LW), leaf sheath length (LSL), leaflet length (LTL), leaflet width (LTW), petiole length (PL), space between intra-marginal veins (IV) of leaf, cross vein angle (CVA) of leaf, number of the cross vein (NOC), number of the leaf (NOL) and number of the leaflet (NOLT) were measured on fresh seagrass specimens. Moreover, in-situ water quality and water nutrient content were also recorded. Seagrass extracts in methanol were assessed for total phenolic content (TPC), total flavonoid content (TFC), 2,2-diphenyl-1-picrylhydrazyl radical scavenging activity (DPPH), 2,2′-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid radical cation scavenging activity (ABTS), and ferric reducing antioxidant power (FRAP).ResultsSeagrasses in the U. reticulata-colonized site (MA) had significantly higher (t-test, p < 0.05) leaf dimensions compared to those at the non-U. reticulata colonized site (MC). Simple broad-leaved seagrass of H. major and H. ovalis were highly sensitive to the colonization of U. reticulata, which resulted in higher morphometric variation (t-test, p < 0.05) including LL, PL, LW, and IV. Concerning the biochemical properties, all the seagrasses at MA recorded significantly higher (t-test, p < 0.05) TPC, TFC, and ABTS and lower DPPH and FRAP activities compared to those at MC. Hydrocharitaceae seagrass experience positive changes in leaf morphology features and metabolite contents when shaded by U. reticulata. Researching the synergistic effect of anthropogenic nutrient loads on the interaction between seagrasses and macroalgae can provide valuable information to decrease the negative effect of macroalgae blooms on seagrasses in the tropical meadow.

When architectural plasticity fails to counter the light competition imposed by planting design: an in silico approach using a functional–structural model of oil palm

Abstract Functional–structural plant modelling approaches (FSPM) explore the relationships between the 3D structure and the physiological functioning of plants in relation to environmental conditions. In this study, we present a methodological approach that integrated architectural responses to planting design in an oil palm FSPM, and test the impact of planting design and architectural plasticity on physiological responses such as light interception and carbon assimilation. LiDAR-derived and direct measurements were performed on five planting designs to assess the phenotypic plasticity of architectural traits, and allowed evaluating the variations of the main parameters of an existing 3D plant model. Accordingly, we proposed a neighbourhood index (NI) as a simple explanatory variable of architectural plasticity, and used NI-based allometries to simulate architectural variations in 3D virtual plants. Light interception and carbon assimilation were then simulated on virtual plots reproducing the five studied designs. We found that the main traits affected by plant proximity were leaf dimensions, leaf weight and leaf erectness, whereas other structural traits like the frequency of leaflets along the rachis or biomechanical properties of leaves remained unchanged. Our simulation study highlighted model compliance to reproduce architectural plasticity and illustrated how architectural plasticity improved light interception via leaf area expansion, but how the competition for light imposed by the design can counterbalance this benefit in terms of carbon assimilation at stand scale. We conclude on the importance of planting patterns for plants with low architectural plasticity such as oil palm, and how in silico experiments can help in designing innovative planting patterns.

Uso de modelos matemáticos para estimar a área foliar total de bananeiras

Abstract The objective of this work was to adjust and validate a mathematical equation to estimate the total leaf area of banana plants of the cultivars Maça BRS Princesa, Prata BRS Platina, Prata Gorutuba and Prata-Anã together, through the linear dimensions of the third leaf and the total number of leaves. For that, the linear first degree and power models were tested, where was used a dependent variable (y) the total leaf area (TLA) an independent variable (x) the multiplication of the length with the total number of leaves (LN), multiplication of the width with the total number of leaves (WN), and multiplying the length by the width with the total number of leaves (LWN). Analysis of covariance was used to test the possibility of using a single equation to estimate the total leaf area of the analyzed cultivars. For all equations, the mean absolute error, the root mean square error and the Willmott d index were obtained as validation criteria. The power model equation TLA = 3.9292(WN)1.5851 can be used simply and quickly to determine the total leaf area of plants of the four cultivars under study.

Allometric equations to estimate the leaf area of Psychotria colorata (Willd. Ex Schult.) Müll.Arg.

Estimating leaf area using non-destructive methods from regression equations has become a more efficient, quick, and accurate way. Thus, this study aimed to propose an equation that significantly estimates the leaf area of Psychotria colorata (Rubiaceae) through linear leaf dimensions. For this purpose, 200 leaves of different shapes were collected, and length (L), width (W), product of length by width (L.W), and real leaf area (LA) of each leaf blade were determined. Then, equations were adjusted for predicting leaf area using simple linear, linear (0.0), quadratic, cubic, power, and exponential regression models. The proposed equation was selected according to the coefficient of determination (R²), Willmott's agreement index (d), Akaike's information criterion (AIC), mean absolute error (MAE), mean squared error (RMSE) and BIAS index. It was noted that the equations adjusted using L.W met the best criteria for estimating leaf area, but the equation LA = 0.59 * L.W from linear regression without intercept was the most suitable. This equation predicts that 59% of leaf area is explained by L.W. Concluding, the leaf area of P. colorata can be estimated using an allometric equation that uses linear leaf blade dimensions.

Comparison of methods for estimating leaf area in pornunça (Manihot sp.)

ABSTRACT Leaf area measurements are used in agronomic studies to evaluate plant growth, light interception, photosynthetic rates, and plant transpiration. It constitute an important indicator of crop productivity, for which the evaluation method must be fast, accurate, and of low cost. The objective of this study was to compare different indirect methods to estimate leaf area in pornunça (Manihot sp.). The research was carried out under field conditions from August 2017 to January 2019 in the semiarid region of Pernambuco State, Northeastern Brazil. Three methods were tested: linear dimensions of leaf (length, width, and the number of lobes), digital image, and leaf scanned image, analyzing 150 healthy leaves from 120 plants of pornunça at different growth stages. The criteria used to determine the best model(s) were a high coefficient of determination, low Akaike information criterion, low sum of squares of residuals, and high Willmott index. Independent of the method of determination, the power models showed the best criteria of adequacy for estimating the leaf area of the pornunça. The digital image, using the power model (Y=LW0.77NL0.49, where L and W are the leaf length and width, and NL is the number of lobes in the leaf) was the best non-destructive method for estimating the leaf area in pornunça plants.

Effects of forest stand structure on population of endangered orchid species Cypripedium calceolus L.

Lady’s slipper orchid (Cypripedium calceolus L.) has suffered a dramatic decline and is one of the most endangered orchid species in Europe. It grows mainly on calcareous soils in deciduous and mixed forests. Although numerous studies have contributed to our understanding of the causes of C. calceolus decline, surprisingly, little is known about the effects of the forest stand structure on the spatial distribution and morphometric characteristics of C. calceolus ramets. In this study, we analyzed how the spatial distribution of tree species and several structural characteristics of the forest stand affect the distribution and morphology of ramets of C. calceolus. For this, we used a remnant population of this species located in extensively managed forests in the Krowiarki Range (the Sudetes, SW Poland). The alarming decline in C. calceolus in this region over the last century is commonly attributed to forest management and land-use changes (abandonment of pastoralism in forests). We analyzed the morphometric characteristics and spatial distribution of C. calceolus ramets in this population in relation to the spatial distributions of trees, canopy gaps, saplings and structural characteristics of the forest stand. For this, we combined precise measurements of the forest stand structure, spatial analyzes in GIS and multivariate logistic regression modeling.The probability of the occurrence of C. calceolus was best predicted by its proximity to silver fir trees. We attributed this mainly to a positive effect by silver fir on the topsoil moisture, which can be especially beneficial to C. calceolus as this species is sensitive to drought. The occurrence of C. calceolus ramets was negatively affected by the basal area and positively affected by the diameter at the breast height of trees growing in a 5 m buffer zone. The structural attributes of the forest stand structure also affected the orchid’s morphology. Ramets growing close to beech or sycamore had lower leaf dimensions than ramets close to fir, and a pattern of decreasing leaf size with proximity to beech or sycamore was visible.This study spotlights the relationship between forest stand structure and the population of the endangered orchid C. calceolus. Based on the results of this and previous research, we have formulated several recommendations for the protection of the remnant population of this species in managed forests. These include maintaining mixed beech-fir forests rather than pure beech forest stands, supporting forest regeneration by species other than European beech, cutting young beech trees to prevent overgrowing the orchid ramets, fencing remnant populations of C. calceolus to exclude browsing pressure and maintaining spatial heterogeneity to support wild pollinators.

Teknologi Pengolahan Citra Digital Untuk Ekstraksi Ciri pada Citra Daun untuk Identifikasi Tumbuhan Obat

The leaf image identification process depends on the feature extraction results. Each medicinal plant has different shapes and patterns of leaf venation. But for one type of medicinal plants have the same pattern of venation shape and pattern even though the size is different. One of the methods for extraction of leaf image form characteristics is by fractal-based feature extraction. Through fractal can be calculated the value of leaf dimensions and searched parts of leaves that have similarities between one part with other parts. As for the method of extracting the characteristics of venation pattern using B-Spline method. Benefits of research conducted is to help people identifying the types of medicinal plants found, knowing the benefits and ways of brewing. While the research contribution is prototype software application based on information technology that can be used by the people through mobile phones for the identification of medicinal plants. To identify or match the results of feature extraction on the leaf found whether included in the medicinal plant, conducted by Euclidean Distance method. In the experiments we used 1100 data consist of 55 variety of medicinal plants for each 20 samples.The experimental result show that the accuracy of identification using of fractal and b-spline is 85.30%.

Functional-Structural Plant Modeling Highlights How Diversity in Leaf Dimensions and Tillering Capability Could Promote the Efficiency of Wheat Cultivar Mixtures.

Increasing the cultivated diversity has been identified as a major leverage for the agroecological transition as it can help improve the resilience of low input cropping systems. For wheat, which is the most cultivated crop worldwide in terms of harvested area, the use of cultivar mixtures is spreading in several countries, but studies have seldom focused on establishing mixing rules based on plant architecture. Yet, the aerial architecture of plants and the overall canopy structure are critical for field performance as they greatly influence light interception, plant interactions and yield. The very high number of trait combinations in wheat mixtures makes it difficult to conduct experimentations on this issue, which is why a modeling approach appears to be an appropriate solution. In this study, we used WALTer, a functional structural plant model (FSPM), to simulate wheat cultivar mixtures and try to better understand how differences between cultivars in key traits of the aerial architecture influence mixture performance. We simulated balanced binary mixtures of cultivars differing for different critical plant traits: final height, leaf dimensions, leaf insertion angle and tillering capability. Our study highlights the impact of the leaf dimensions and the tillering capability on the performance of the simulated mixtures, which suggests that traits impacting the plants' leaf area index (LAI) have more influence on the performance of the stand than traits impacting the arrangement of the leaves. Our results show that the performance of mixtures is very variable depending on the values of the explored architectural traits. In particular, the best performances were achieved by mixing cultivars with different leaf dimensions and different tillering capability, which is in agreement with numerous studies linking the diversity of functional traits in plant communities to their productivity. However, some of the worst performances were also achieved by mixing varieties differing in their aerial architecture, which suggests that diversity is not a sufficient criterion to design efficient mixtures. Overall, these results highlight the importance of simulation-based explorations for establishing assembly rules to design efficient mixtures.

Allometric relationship and leaf area modeling estimation on chia by non-destructive method

ABSTRACT This study aimed to obtain equations to estimate leaf area from linear leaf dimensions and establish the allometric relationship between leaf area and the number of leaves on the main stem of chia (Salvia hispanica L.) at different sowing times. The experiment was conducted in the agricultural year 2016/2017 on five sowing times in Santa Maria, RS, Brazil, in a randomized block design with four repetitions. In each plot, ten random plants were marked weekly during the vegetative phase to determine the number of leaves (NL) in the main stem, and three of these for the determination of leaf area (LA). A total of 70 leaves of different sizes were used to calibrate the model. Another 106 leaves were used to test the predictive capacity of the equations by various statistical indices. The length (L) and the largest leaf width (W) were measured. Leaf collection was carried out during the cycle, in all sowing times to represent all leaf sizes. The linear, quadratic, exponential, and potential models were adjusted. The non-destructive method, through the linear dimensions of the leaf, is appropriate for estimating the leaf area in chia. The general equation LA = 0.642 (L x W) can be used to estimate the leaf area of the chia plants without loss of precision. The potential model is appropriate to characterize the allometric relationship between leaf area evolution and the number of leaves accumulated in the main stem of chia at different sowing times.

Morpho-agronomic traits variability, allelic polymorphism and diversity analysis of African yam bean: towards improving utilization and germplasm conservation

AbstractThis study assessed the genetic diversity of African yam bean (AYB) accessions using morphological and molecular markers. The accessions were grown, and morphological data collected were subjected to analysis of variance and multivariate analyses. Genomic DNA extracted from the accessions were amplified with inter simple sequence repeat (ISSR) markers. The diversity analysis was conducted using MEGA4 software. The accessions varied significantly (P &lt; 0.05) in growth, flowering and seed-related parameters. Flowering commenced early in most accessions. Weight of 100-seed range from 15.01 to 21.15 g with the mean value of 18.30 g. Significant correlations existed between stem height, the number of leaves and leaf dimensions. Also, days to flowering correlated with pod formation; likewise, seed dimension had a positive association with seed weight. The principal biplot revealed that two components accounted for 41.77% of the observed variation. Analysis of the electropherogram showed 95 loci comprising 1351 alleles were detected by the ISSR markers with 65.26% polymorphism and combined polymorphic information content of 0.85. The principal coordinate analysis placed accessions together on a plane based on their spatial relationship. The dendrogram showed accession pairs (TSs-77, TSs-95) and (TSs-111, TSs-84) are closely related. The phylogram identified three kinships with a total length of 454. Accession TSs-115 is likely the progenitor while TSs-82 and TSs-86 are the most recent. The study concluded that a combination of morphological and ISSR markers is effective for the diversity study of AYB and the existing, genetic diversity in the accessions could be harnessed for its improvement, conservation and utilization.

Estimation of buckwheat leaf area by leaf dimensions

The objective of this work was to model and identify the best models for estimating the leaf area, determined by digital photos, of buckwheat (Fagopyrum esculentum Moench) of the cultivars IPR91-Baili and IPR92-Altar, as a function of length (L), width (W) or length x width product (LW) of the leaf blade. Ten uniformity trials (blank experiments) were carried out, five with IPR91-Baili cultivar and five with IPR92-Altar cultivar. The trials were performed on five sowing dates. In each trial and cultivar, expanded leaves were collected at random from the lower, middle and upper segments of the plants, totaling 1,815 leaves. In these 1,815 leaves, L and W were measured and the LW of the leaf blade was calculated, which were used as independent variables in the model. The leaf area of each leaf was determined using the digital photo method (Y), which was used as a dependent variable of the model. For each sowing date, cultivar and thirds of the plant, 80% of the leaves (1,452 leaves) were randomly separated for the generation of the models and 20% of the leaves (363 leaves) for the validation of the models of leaf area estimation as a function of linear dimensions. For buckwheat, IPR91-Baili and IPR92-Altar cultivars, the quadratic model (Ŷ = 0.5217 + 0.6581LW + 0.0004LW2, R2 = 0.9590), power model (Ŷ = 0.6809LW1.0037, R2 = 0.9587), linear model (Ŷ = 0.0653 + 0.6892LW, R2 = 0.9587) and linear model without intercept (Ŷ = 0.6907LW, R2 = 0.9587) are indicated for the estimation of leaf area determined by digital photos (Y) based on the LW of the leaf blade (x), and, preferably, the linear model without intercept can be used, due to its greater simplicity.

Estimating the contribution of plant traits to light partitioning in simultaneous maize/soybean intercropping.

Spatial configuration and plant phenotypic plasticity contribute to increased light capture in relay intercropping, but there is little information on whether these factors also increase light capture in simultaneous intercropping. We developed and validated a three-dimensional functional-structural plant model to simulate light capture in maize and soybean sole crops and intercrop scenarios, using species traits observed in sole crops and intercrops. The intercrop maize phenotype had 2% greater light capture than the sole crop phenotype in a pure stand. The soybean intercrop phenotype had 5-10% lower light capture than the sole crop phenotype in a pure stand. The intercrop configuration increased the light capture of maize by 29% and reduced the light capture of soybean by 42%, compared with the light capture expected from sole crops. However, intercrop configuration only marginally affected total light capture by the intercrop system (+1%). Testing of individual soybean plant traits revealed that plasticity in leaf dimensions was the main reason for differences in light capture by soybean in simulated sole crops and intercrops. The results of this study illustrate a major shift of light capture from shorter species (soybean) to the taller component (maize) in a simultaneous strip intercrop. Plastic plant traits modulate this overall effect, but only marginally.

Using soft computing and leaf dimensions to determine sex in immature Pistacia vera genotypes

Pistachio (Pistacia vera) is a dioecious tree species in the cashew family originating from Central Asia and the Middle East. The sex of pistachio genotypes cannot be established until inflorescence growth during the reproductive stage. The ability to determine sex before flowering would be extremely beneficial for pistachio growers and breeders. In this study, different methods of soft computing, using classifiers (i.e. KNN, SVM, SOM, ANFIS and RBF) were employed to determine pistachio sex based on geometric features of mature leaves. Data were collected from more than 900 leaves representing 45 pistachio genotypes before sexual maturation. Separate training data set sizes (20, 40, 60 and 80%) were used to evaluate the generalizability of each classifier. Results indicated the KNN classifier was the most accurate (>95%) for sex determination during training phases however, accuracy during testing phases varied from 52 to 60% for the four training data set sizes. Training phase accuracy with the 80% data set ranged from 83 to 64% with the respective arrangement of RBF, ANFIS, SVM, and the SOM classifiers. In the test phase, classifier accuracy varied from 88.33% (RBF) to 60% (KNN). Our results indicated RBF could reliably be used to differentiate between male and female pistachio genotypes. Thus, soft computing models are useful tools for predicting sex in pistachio based on leaf dimensions.

Evaluation of Vegetative and Reproductive Characteristics of Some Quince (Cydonia Oblonga Mill.) Genotypes from Central Regions of Iran

ABSTRACT Identification and differentiation of quince cultivars and genotypes are more difficult than other members of the pomoideae sub-family due to the more limited range of traits of this species. This research was conducted to study the vegetative and reproductive traits of quince germplasm in the central regions of Iran and to identify important traits in the differentiation of these cultivars and genotypes. For this, 11 cultivars and genotypes collected from Isfahan province in the collection of the Agricultural Research Center were compared during 2018 to 2020 according to the National Guideline for Distinctness, Uniformity, and Stability (DUS) in quince. Fifty-five traits related to this guideline were considered along with 10 vegetative and fruit complementary traits. The results showed significant diversity in all plant organs and the general shape of the tree. Traits such as growth vigor, pubescence density, internode length, leaf dimensions, angle of leaf apex, flower size, petal arrangement, the undulation of petal margin, flowering time, fruit size, neck length, prominences of around the eyes, and fruit ripening time played an essential role in the differentiation of cultivars and genotypes. Cluster analysis divided cultivars and genotypes into four main groups. This grouping was able to divide the studied germplasm based on quantitative and qualitative characteristics as well as their collection location. NB4 and KVD2 genotypes are among the promising genotypes due to the quantitative and qualitative characteristics of the fruit.