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Soybean is an important food crop after rice and maize. Soybean production in East Kalimantan based on the estimated 2014 rate is estimated at 1,263 tons of dry seeds. Compared to 2013 production there was a decrease of 139 tons (9.91%) (BPS, 2014). The low productivity is because soybean cultivation is still not optimal. One of the cultivation that can be done is by using Fish Waste and Solid POC. The purpose of this study was to determine the growth response of soybean (Glycine max l. Merril) by giving poc fish waste and solids. This research was conducted in Sidorejo Hamlet, Bilah Hilir District, Labuhan Batu Regency, North Sumatra Province. The research method used was factorial randomized block design (RBD) consisting of 2 factors, 9 combinations and 3 replications. The first factor was the provision of POC fish waste (P) consisting of 3 levels, namely: P0 = 0 ml / planting hole, P1 = 100 ml / planting hole, P2 = 200 ml / planting hole. The second factor is the provision of solid (S) consisting of 3 levels, namely: S0 = 0 ml / planting hole, S1: 100 ml / planting hole, S2: 200 ml / planting hole. Parameters observed were plant height, number of leaves, leaf width and stem diameter. Based on the results of research in the field, it shows that the provision of fish waste poc and solid has no significant effect on all observed parameters. Meanwhile, the interaction between poc and solid fish waste also had no significant effect on all observed parameters. Keywords: Soybean, POC Fish Waste, and Solid

The generation of morphological traits of plants such as the leaf length, width, perimeter, area, and petiole length are fundamental features of herbarium specimens, thus providing high-quality data to investigate plant responses to ongoing climatic change and plant history evolution. However, the existing measurement methods are primarily associated with manual analysis, which is labor-intensive and inefficient. This paper proposes a deep learning-based approach, called Deep Leaf, for detecting and pixel-wise segmentation of leaves based on the improved state-of-the-art instance segmentation approach, Mask Region Convolutional Neural Network (Mask R-CNN). Deep Leaf can accurately detect each leaf in the herbarium specimen and measure the associated morphological traits. The experimental results indicate that our automated approach can segment the leaves of different families. Compared to manual measurement done by ecologist and botanist experts, the average relative error of leaf length is 4.6%, while the average relative error of leaf width is 5.7%.

Leaf area measurement is pivotal for plant physiologists. Hence, accurate measurement of their leaf area is incredibly relevant in agronomic terms. The plant Stevia rebaudiana is a sucrose-free plant species that is now vital to the global production of sucrose-free foods. Here, we estimated S. rebaudiana leaf area using a nondestructive methodology comprising allometric equations. Through leaf length (L), leaf width (W), and/or their product (LW) the leaf area was determined. One thousand leaves were sampled from four distinct S. rebaudiana genotypes for model construction. Linear or power models were generated, and the best equation was selected using a statistical criterion. The statistical criteria indicated that the linear models best suited all genotypes tested, included a function of LW, exhibited increased stability, and precisely estimated coefficients. ANOVA revealed that both generalized and combined equations were feasible. Nevertheless, grouping all genotypes into a single model was not possible as the genotype leaf architectures were very dissimilar.

Estimation of leaf area by using leaf length and leaf width variables could be done without destruction of the leaves from plants and more practical than using the leaf areameter. Surface area is a function of the variable length and width, so the leaf area can be measured based on leaf length and leaf width variables. The purpose of this research is to get the leaf area estimator model with nondestructive method. Taro plants were observed by using 12 accessions/varieties taken from the germplasm collection in Gene Bank Collection of ICABIOGRAD, IAARD. Observations of the length, width, and area of leaf were carried out on 10-12 leaf samples for each accession/variety from taro cultivation which was about 4 months old. The length (P), width (L), and area (Y) of each taro leaf were measured. The estimation of taro leaves area by regression equation was analyzed by using one (P or L) and two (P and L) independent variables. Estimation using two variables, leaf length and width, is better than only use one variable. Taro leaf area (Y) of each leaf can be determined by the equation Y = 0.9462 P x L for ratio of P/L less than 1.10, Y = 0.9109 P x L for ratio of P/L between 1.10-1.19, and Y = 0.8860 P x L for ratio of P/L equal or greater than 1.20. Keywords: model estimation, leaf area, taro

Ria RP, Lakitan B, Negara ZP. 2020. Effects of water table, seedling density and transplanting time on vegetative growth of black sticky rice at floating seedbed. Jurnal Lahan Suboptimal : Journal of Suboptimal Lands 9(2): 167-174.Study on black sticky rice cultivation in South Sumatera is seldom carry out. The objective of this study was to evaluate the effect of water table and population density on the growth of rice during seedling preparation at floating seedbed; furthermore, this study aimed to evaluate the effect of transplanting time on vegetative growth of black sticky rice. The research was started in May 2018 in Palembang. Black sticky variety used in this research was Toraja variety. The raft used is made from 1,5 l plastic bottles which are arranged to reach 2x1 meters in size. This study was conducted by two stages. The first stage was for water table and population density treatments laid on split plot design. The second stage was for transplanting time utilizing completely randomized factorial design. Statistically, results showed water table and population density significantly influensced root length of black sticky rice and transplanting time 14 DAS haad an effect on the leaf length , leaf width and leaf area.

In order to maintain soil fertility, NPK fertilizer applications that have been carried out by farmer need to be combined with non chemical fertilizer such as bokashi. Research on vegetative growth of kale land due to NPK and bokashi fertilizer has been carried out in Bajur Village, West Lombok Regency. The purpose of this research was to detemine: (1) vegetative growth of kale land due to different doses of NPK fertilizer, (2) vegetative growth of kale land due to different doses of bokashi, (3) the effect of interaction of NPK and bokashi fertilizer on growth of kale land, (4) Optimum dose of NPK fertilizer and bokashi for kale land. This research used 2 factors design. The first factor is the dose of NPK fertilizer and the second factors is the dose of bokashi. The growth parameters measured were stem height, leaf length, leaf width and number of kale land leaf. Reseach data analyzed using analysis of variance. The results showed that: (1) NPK fertilizer treatment significantly affected stem height, leaf length and kale leaf width, but have no significant effect on the number of kale land leaves, (2) bokashi aplication significantly affected stem heght, leaf length and kale land leaf width but did not significantly affect the number of kale land leaves, (3) the interaction of NPK fertilizer and bokashi did not significantly affect all growth parameters measured, (4) the optimun dose of bokashi for kale land is 1,2 kg for 8 kg of soil and the optimum dose of NPK fertilizer is 1,5 g per plant. It is recommended that kale land famers use 1,2 kg bokashi for 8 kg of soil and 1,5 g NPK fertilizer per plant.

This research aims to know the effect of dosing cacao rind bokashi fertilizer to the growth and the increase of chilli plants yield and also to know the optimum dose of bokashi which can provide the optimum growth and yield. The design used in this experiment is Randomized Block Design (RBD). The treatment used are P0 (without cacao rind fertilizer), P1 (cacao rind fertilizer 10 tons ha-1 = 5.6 kg/ptk), P2 (cacao rind fertilizer 20 tons ha-1 = 11.2 kg/ptk), P3 (cacao rind fertilizer 30 tons ha-1 = 16.8 kg/ptk), P4 (cacao rind fertilizer 40 tons ha?1= 22.4 kg/ptk). The variable of the observation in this research is the height of the plants, the number of leaves, the leaf width, the fruit weight tan?1, the fruit weight ha?1. The result of this research indicates that the dosing of cacao rind bokashi fertilizer can influence the plant's height with the total average of 24.52%, the average number of leaves with a total of 14.56%, and the average leaf width with a total of 29.55 %, and the total of fruits tan?1 31,46%, the fruit weight tan?1 29.17%, the fruit weight ha?1 28.67%. The optimum dose of cocoa rind bokashi 40 tons ha?1 can promote the optimum growth and yield of chilli plants.

This research aims at investigating the effect of some organic fertilizers on the growth and yield of green onion plants. The kind of organic fertilizers which can give optimum growth and yield of green onion plants is Bokashi fertilizer. The design used in this experiment is Randomized Block Design (RBD). The treatment used is P0 = without fertilizer or 0 kg swath?1, P1= chicken manure 15 tons ha?1 or 2.4 kg swath?1, P2= cow manure 15 tons ha?1 or 2.4 kg swath?1, P3= vermicompost fertilizer 15 tons ha?1 or 2.4 kg swath -1, P4= bokashi fertilizer 15 tons ha?1 or 2.4 kg swath?1. The observed variables are the height of the plants, the number of leaves, the leaf width, the number of seedlings, fresh residue tan?1, the weight of fresh clump leaves tan?1, the weight of fresh clump leaves ha?1, the number of clump stem?1, and the weight of clump stem?1. Bokashi fertilizer application gives a very real effect to the variable of plants height growth with a total of 37.91%, the number of leaves amounted to 34.81%, the leaves width amounted to 51.35%, the number of seedlings amounted to 48.47%, the fresh residue tan?1 amounted to 44.81%, the weight of fresh clump leaves tan?1 amounted to 19.27%, the weight of fresh clump leaves ha?1 amounted to 50.84%, the number of clump stem?1 amounted to 39.60.%, and the weight of clump stem?1 amounted to 51.98%. Kind of organic fertilizers which can provide the optimum growth and yield of green onion plants is Bokashi fertilizer 15 tons ha?1.

Chili high yield is the target of plant breeding. High yielding chili selection can be done through direct selection of yield characters and indirectly through other characters. Indirect selection is more efficient than the selection of one character. This research aims to study the relationship between quantitative characters with yield as well as obtaining the selection criteria. Correlation analysis results showed that the fruit weight, fruit diameter, pericarp thickness, leaf width, and leaf length were positively correlated and were very significant on yield. Based on the path analysis, characters that have a positive direct effect on yield are fruit weight, fruit diameter, leaf width, and leaf length, while pericarp thickness had a negative direct effect but had a large indirect effect on yield.

Leaf shape is closely related to economics of leaf support and leaf functions, including light interception, water use, and CO2 uptake, so correct quantification of leaf shape is helpful for studies of leaf structure/function relationships. There are some extant indices for quantifying leaf shape, including the leaf width/length ratio (W/L), leaf shape fractal dimension (FD), leaf dissection index, leaf roundness index, standardized bilateral symmetrical index, etc. W/L ratio is the simplest to calculate, and recent studies have shown the importance of the W/L ratio in explaining the scaling exponent of leaf dry mass vs. leaf surface area and that of leaf surface area vs. leaf length. Nevertheless, whether the W/L ratio could reflect sufficient geometrical information of leaf shape has been not tested. The FD might be the most accurate measure for the complexity of leaf shape because it can characterize the extent of the self-similarity and other planar geometrical features of leaf shape. However, it is unknown how strongly different indices of leaf shape complexity correlate with each other, especially whether W/L ratio and FD are highly correlated. In this study, the leaves of nine Magnoliaceae species (&gt, 140 leaves for each species) were chosen for the study. We calculated the FD value for each leaf using the box-counting approach, and measured leaf fresh mass, surface area, perimeter, length, and width. We found that FD is significantly correlated to the W/L ratio and leaf length. However, the correlation between FD and the W/L ratio was far stronger than that between FD and leaf length for each of the nine species. There were no strong correlations between FD and other leaf characteristics, including leaf area, ratio of leaf perimeter to area, fresh mass, ratio of leaf fresh mass to area, and leaf roundness index. Given the strong correlation between FD and W/L, we suggest that the simpler index, W/L ratio, can provide sufficient information of leaf shape for similarly-shaped leaves. Future studies are needed to characterize the relationships among FD and W/L in leaves with strongly varying shape, e.g., in highly dissected leaves.

Leaf shape is a key plant trait that varies enormously. The range of applications for data on this trait requires frequent methodological development so that researchers have an up-to-date toolkit with which to quantify leaf shape. We generated a dataset of 468 leaves produced by Ginkgo biloba , and 24 fossil leaves produced by evolutionary relatives of extant Ginkgo . We quantified the shape of each leaf by developing a geometric method based on elastic curves and a topological method based on persistent homology. Our geometric method indicates that shape variation in modern leaves is dominated by leaf size, furrow depth and the angle of the two lobes at the leaf base that is also related to leaf width. Our topological method indicates that shape variation in modern leaves is dominated by leaf size and furrow depth. We have applied both methods to modern and fossil material: the methods are complementary, identifying similar primary patterns of variation, but also revealing different aspects of morphological variation. Our topological approach distinguishes long-shoot leaves from short-shoot leaves, both methods indicate that leaf shape influences or is at least related to leaf area, and both could be applied in palaeoclimatic and evolutionary studies of leaf shape.

Specific leaf area (SLA) is a good predictor of aboveground net primary productivity. However, the SLA of bamboo species is generally estimated on the basis of destructive measurements rather than the cost-effective and recyclable nondestructive measurements using easily accessible leaf traits such as leaf length (L) and width (W). Considering the strong empirical relationships between leaf area (LA) and leaf structural parameters of bamboo species that were developed by previous studies, this study explores the feasibility of estimating the leaf dry mass (LDM) and SLA of 50 bamboo species using L and W. The results show that the Montgomery equation and its similar forms precisely estimated LA of the 50 bamboo species at both leaf scale (R2 &gt, 0.96 and MAE% &lt, 4.67%) and the canopy scale (R2 &gt, 0.99 and RMSE &lt, 0.09), the LDM of the 50 bamboo species could also be estimated using L and W at both leaf scale (R2 &gt, 0.52 and MAE% &lt, 26.35%) and the canopy scale (R2 &gt, 0.003), and the estimated mean SLA of each of the 50 bamboo species had good agreement with the measured values (R2 &gt, 1.88) because of the precisely estimated mean LA and mean LDM at the canopy scale, indicating the feasibility of estimating SLA of the 50 bamboo species at the canopy scale based on nondestructive measurements. However, the empirical relationships used for mean SLA estimations are not suitable for SLA estimations at the leaf scale because of the uncertainties in the estimated LDM at the leaf scale.

Pak Choy plant is a vegetable plant that can grow with soil and hydroponic media. Plant growth can be monitored by knowing the width of the plant's leaves. This research creates a tool to accurately detect plant leaf width through plant growth monitored by the people-research implementation in the form of a mobile application that can detect the width of plant leaves. Using the canny edge detection method, the results obtained system accuracy of 95.06%, the light intensity of 18.75 lux, angle of 90°, and distance of 30 cm. Pak Choy plant growth was seen for 4 weeks, the best accuracy was obtained at 2nd week with an average accuracy of 99% and an average light intensity value of 22 lux.

The cultivation of carambola produced some waste that can be used as organic fertilizer. Organic fertilizer is useful to improve soil conditions and enrich the nutrient content contained therein so that it is easily absorbed by cultivated plants such as pakcoy (Brassica rapa L.). The optimum pakcoy production is supported by good land management in order to meet the availability of nutrients needed by the addition of inorganic fertilizers and starfruit organic fertilizer. The study was conducted at Attaqie Farm, Tuban in November 2018 to May 2019. The experimental design used was randomized completely block design with two factors carambla derivated organic fertilizer 10 tons ha -1 , 20 tons ha -1 , 30 tons ha -1 and inorganic fertilizer 0 kg ha -1 ; 50 kg ha -1 ; 100 kg ha -1 . The results showed that carambola derivated organic fertilizer contained N, P, K, S, Ca, and Mg about 6.19%, 0.94%, 75.04%, 0.02%, 20.13%, and 47.23%, respectively. The dosage of 50% inorganic fertilizer and 10 tons of carambola organic fertilizer gave optimum results for the growth of plant height, number of leaves, leaf width, stem diameter, canopy weight, root length and root weight of pakcoy plants. Fertilization using a dose of organic fertilizer 10 tons ha-1 could reduce 50% of the need of inorganic fertilizer. Keywords : fertilizer efficiency, organic fertilizer, pakcoy, starfruit waste, verticulture

This study aims to determine the response given by the red lettuce plant to the provision of nutrients in the form of nutrient solution (AB Mix) on the horizontal installation of the hydroponic system. The study was conducted on December 20, 2017 until February 16, 2018 at the PKK Gardens Education Center in Bengkulu province. Seeding process of Red Lettuce Seedlings is carried out for 14 days then transferred to a net pot at the installation in the Greenhouse. Fertilizers with the Fiora A and B Brands are dissolved to be mixed in a nutrient bath with a capacity of 3000 L with a nutrient density of 500 ppm in the Greenhouse to be distributed to the horizontal installation of the hydroponic system inside the Greenhouse. Then growth observations were carried out on 10 plant samples with parameters of leaf length, leaf width, number of leaves, stem height, andstem diameter for 30 days. The results obtained by sample 1-10 have an average growth and development that is not much different. The maximum leaf length and leaf width parameters are in samples 2 and 3. While the highest number of leaf strands in sample 3 is 22 strands with an average of 18 strands and sample 4 has the highest stem height parameter of 3.5 cm with an average height 2.7 cm. The largest stem diameter in sample 4 is 4.1 cm with an average of 3.38 cm. The response of red lettuce after the last week showed symptoms of leaves that are less red with relatively more withered body.

Expanding the range of vegetable crops, including green ones, through the introduction of new varieties into production is an important task. The study and evaluation of the original material of the salad, the features of cultivation in different periods, will allow to identify samples of a complex of economically valuable traits for the selection of culture, which is relevant for the creation of varieties in Belarus. Research was carried out on the experimental field of the Department of horticulture of the Belarusian state agricultural Academy in 2013-2015. The article assesses the relationship between the main economically valuable features of varieties of lettuce when grown in the spring (seedling method) and spring and summer sowing in the open ground. In lettuce plants of the headed variety, the sign “the mass of the vegetative part of the plant” strongly depends on the sign “diameter of the head” (r=0.640 - with the seedling method and r=0.809 - with the spring sowing period), “leaf width” (r=0.685 and r=0.790, respectively). A high connection is also established between the signs "leaf length" and "leaf width" (r=0.702 - with the spring sowing period and r=0.749 - with the seedling method). In leaf lettuce plants, a strong correlation was noted between the signs “leaf length” and “plant height” (r=0.706 for summer and r=0.810 for spring planting), diameter of the rosette of leaves (r=0.564 for summer and r=0.810 - at the spring sowing time). The average feedback for leaf lettuce varieties is revealed between the signs “leaf width” and “number of leaves” (r=-0.444 - for spring and r=-0.458 - for summer sowing time). The majority of morphological signs, depending on the time of cultivation, are related to each other by average correlation links (the correlation coefficient ranged from 0.458 to 0.531).

Boiler ash is a solid waste from biomass combustion from palm oil mills. The boiler ash can be used as fertilizer because it has a high content in the samples of N, P, K and Mg and is safe for the environment. This study aims to determine the effect of boiler ash fertilizer on the growth of cocoa seedlings and get the optimal fertilizer dose when applied. This research was conducted in Jayapura – Papua for 3 months (September – November). This study used a completely randomized design that was repeated as many as 6 replications. The treatments given include: A0 (control), A1 (300 g.polybag–1), A2 (350 g.polybag–1), A3 (400 g.polybag–1) and A4 (450 g.polybag–1). Parameters measured were plant height, leaf number, leaf width, leaf length and plant wet weight. Based on statistical tests, the results showed that the use of boiler ash fertilizer on the growth of cocoa seedlings which was seen from all parameters had no significant effect. However, A4 treatment using 450 g of boiler ash fertilizer per polybag gives significant results for all parameters measured.

The aims are (1) to present a clinical brain case where the dose distribution calculated at 2.5-mm grid resolution was significantly different from that of 1.0 mm with Varian HD120 multileaf collimator (MLC; 2.5-mm central leaf width), and (2) to present our analysis results to better understand the influence of dose calculation grid resolution and its spatial alignment with MLC. A simulation using a static MLC pattern with 10 open strips was conducted to demonstrate the possibility that the characteristics of MLC dose profiles can be completely hidden. The effects of the spatial MLC alignment with the dose grid were investigated for grid resolutions from 1.0 mm to 5.0 mm. In the end, 20 recent stereotactic radiotherapy plans (5 brain, 5 lung, 5 spine, and 5 other) were retrospectively selected, and their dose distributions were recalculated at 1.0 mm, 1.5 mm, and 2.5 mm resolutions for comparisons. Film dosimetry results were used as references. At 2.5-mm grid resolution, the MLC open-strip patterns were not visible in the dose distribution when the MLC leaf interspaces were at exact alignment with the dose grid. The effects were smaller at 1.0-mm grid resolution. The dose error at the centers of the open strips varied significantly (7% to 39%) depending on the alignments. Overall, the planning target volume mean dose of 1.5-mm plans was higher than 1.0-mm plans by 1.3 ± 0.3% (mean ± 1SD) with a maximum of 2.6%, while the mean dose of 2.5-mm plans was lower by −0.5 ± 0.5% with a maximum mean dose of −3.7%. In conclusion, the choice of dose calculation grid resolution can affect the plan dose distribution significantly. The dose grid resolution must be smaller than the width of MLC leaf at a minimum. A finder resolution is expected to produce less uncertainty in the calculated dose and influenced less by the MLC-grid spatial alignment.

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. RESUMO Objetivou-se neste estudo obter equações para estimar a área foliar a partir de dimensões lineares da folha e estabelecer a relação alométrica entre a área foliar e o número de folhas da haste principal de chia (Salvia hispanica L.) em diferentes épocas de semeadura. O experimento foi conduzido no ano agrícola 2016/2017 em cinco épocas de semeadura em Santa Maria, RS, Brasil, em delineamento de blocos ao acaso com quatro repetições. Em cada parcela, dez plantas ao acaso foram marcadas para determinação semanal do número de folhas (NF) na haste principal durante a fase vegetativa, e três para determinação da área foliar (AF). Um total de 70 folhas de diferentes tamanhos foram usadas para calibrar o modelo e outras 106 folhas foram usadas para testar a capacidade preditiva das equações por vários índices estatísticos, nas quais foram medidos o comprimento (C) e a maior largura da folha (L). A coleta de folhas foi realizada durante o ciclo de desenvolvimento de todas as épocas de semeadura para ter representação de todos os tamanhos de folhas. Os modelos linear, quadrático, exponencial e potencial foram ajustados. O método não destrutivo, através das dimensões lineares da folha, é adequado para estimar a área foliar em chia. A equação geral AF = 0.642 (L x W) pode ser usada para estimar a área foliar das plantas de chia sem perda de precisão. O modelo potencial é adequado para caracterizar a relação alométrica entre a evolução da área foliar e o número de folhas acumuladas na haste principal de chia em diferentes épocas de semeadura.

Many vision-based techniques have been proposed and handheld devices have been commercially available for leaf area measurement. However, they are not cost-effective nor simple enough for use. As an effort to tackle this problem, this study proposed an easy vision-based approach toward measuring the leaf dimensions and area using a smartphone, a cost-effective and available device. Acceptable measurement accuracies were achieved from experiments with different leaf shapes and sizes in terms of both error and error percentage. The leaf area had the largest error percentage of 2.3%; however, its largest mean error percentage was only 0.6 ± 0.5%. The smallest error was associated with the leaf width with the largest mean error and mear error percentage of 0.61 ± 0.35 mm and 1.5 ± 1.0%, respectively. It is thus promising to apply this simple approach for screening the dimensions and area of many leaves with different shapes and sizes.

CO2 capture and storage (CCS) is an important technical strategy to reduce global CO2 emission from heavy industries. However, the risk of CO2 leakage in CCS-related projects cannot be ignored and it is crucial to identify and monitor CO2 leakage in CCS project areas in a timely and effective manner. So here we investigate the biological characteristics (plant height, leaf length, leaf width and SPAD value) and leaf spectral characteristics of maize under soil CO2 concentration of 10, 30, and 50%, with normal soil condition as control (CK). By analysing the original spectrum and first derivative spectrum of maize leaves, spectral parameters relatively sensitive to soil CO2 stress were extracted. Further, eight composite spectral characteristic indexes that are expected to identify CO2 leakages were constructed and analyzed. Besides, the normalized pigment chlorophyll index (NPCI) and modified chlorophyll absorption in reflectance index (MCARI) were also investigated for the indication role in CO2 leakage. The results showed that maize morphological traits had a significant hysteresis effect for the indication of CO2 leakage; the SPAD value was difficult to indicate the lower concentration of soil CO2 early. But it was found that three spectral characteristic indexes REP-BEP, RGP/RRV and RGP-RRV/RGP+RRV can effectively identify CO2 leakage, and three spectral characteristic indexes (RVP-GPP, REP-BEP and MCARI) can be used for quantitative inversion of soil CO2 concentration. Especially, REP-BEP index could both indicate CO2 leakage and quantitatively inverse soil CO2 concentration. In sum, the spectral characteristic indexes of maize leaves can be used as effective indicators to quickly and effectively identify CO2 leakage and quantitatively invert the CO2 concentration in soil.

Prostrate growth 1 (PROG1) gene is vital in controlling the prostrate growth habit of rice. Studying the effect of PROG1 gene on rice canopy structure is crucial in elucidating the molecular mechanism of rice plant type evolution. Herein, the morphological characteristics of different rice genotypes were collected at different growth stages and leaf nodes using image processing techniques. The morphological characteristics included leaf length, leaf width, and leaf area. The image processing techniques involved boundary mean oscillation (BMO) filtering and minimum bounding rectangle extraction of the target image. On this basis, the effect of the PROG1 gene on rice leaf morphology was quantitatively assessed. Also, the feasibility of image processing techniques in detecting the morphological characteristics of rice leaves was discussed. Under the influence of the PROG1 gene, the length, width, and area of rice leaves decreased by 45.1%, 12.7%, and 44.8%, respectively, at the booting stage. Similarly, the length, width, and area of flag leaves decreased by 15.8%, 32.0%, and 33.7% at the heading stage and by 25.4%, 16.2%, and 19.7% at the filling stage, respectively, and that of secondary leaf reduced by 23.2%, 13.6%, and 54.2% at heading stage and by 24.1%, 17.3%, and 37.0% at filling stage, respectively. Furthermore, the length, width, and area of other leaves reduced by 32.3%, 9.8%, and 51.6% at the heading stage and by 28.6%, 7.3%, and 36.7% at the filling stage, respectively. The leaves in the rice canopy were shorter, narrower, and smaller in leaf area. Notably, no significant differences were found between image processing technology and manual measurement methods regarding the values of leaf morphological characteristics obtained ( P < 0.05 ). Thus, these results show that image processing technology is effective in studying the morphological characteristics of rice leaves. This study provides a reliable foundation for molecular breeding studies and will guide the application of the PROG1 gene in molecular breeding.

Objetivo: Describir la variedad de nochebuena Ximena en base a directrices de la UPOV y evaluar su comportamiento con un productor cooperante en el estado de Morelos.Diseño/metodología/aproximación: La variedad se generó mediante los métodos genotécnicos de hibridación, selección recurrente y uso de la técnica de injerto. La descripción varietal se realizó en base al documento de la Unión para la Protección de las Obtenciones Vegetales (UPOV). El diseño experimental utilizado fue un completamente al azar con 10 repeticiones. Se registraron caracteres vegetativos y de bráctea de la planta. La información se estudió mediante análisis de varianza y prueba de comparación de medias Tukey (P? 0.05).Resultados: Ximena presenta porte alto, de amplitud grande con ramificación intermedia. La hoja de forma oval, larga y ancha con peciolo de longitud media. Brácteas de forma elíptica, color rojo, sin torsión y rugosidad entre los nervios. La anchura de la cima es media, glándulas del ciatio de color amarillo de tamaño medio sin alguna deformación. La respuesta de Ximena fue estadísticamente similar a los dos testigos en diámetro del tallo, número de entrenudos, ancho de hoja, longitud de peciolo de hoja y bráctea. En cambio, fue superior estadísticamente en longitud de bráctea, amplitud de dosel de bráctea y diámetro de ciatio.Limitaciones del estudio/implicaciones: La variedad se mantiene como planta madre, a partir de la cual se van a establecer cultivos comerciales. Por lo que, requiere adecuada nutrición y condiciones que no permitan su diferenciación floral.Hallazgos/conclusiones: El comportamiento y arquetipo de Ximena fue comparable a la de variedades comerciales, posee características estéticas que demanda el mercado, puede ser competitiva y se considera candidata para diversificar la oferta de plantas de nochebuena en la temporada de navidad.

The present study used fractal analysis for soybean leaves characterization (Glycine max (L.) Merr), Caro and Onix genotypes. The box-counting method was used to find the fractal dimensions of leaf shape in the two genotypes. The fractal dimensions were D = 1.627 at the Caro genotype, and respectively D = 1.509 at the Onix genotype. In the case of Caro genotype, correlation analysis showed average correlations between fractal dimension (D) and leaf width (W), r = 0.728, respectively between D and scan leaf area (SLA), r = 0.778 and low intensity correlations between D and perimeter of the leaves (Per), r = 0.624, respectively between D and the leaf length (L), r = 0.484. In the case of Onix genotype, high correlations were found between D and SLA (r = 0.862), between D and W (r = 0.812); average correlations between D and Per (r = 0.766), and respectively low correlations between D and L (r = 0.685). Based on D values, SLA prediction was possible under conditions of R2 = 0.631, p << 0.001 for Caro genotype, and R2 = 0.812, p << 0.001 respectively for Onix genotype.

Key message A highly significant and positive scaling relationship between bamboo leaf dry mass and leaf surface area was observed; leaf shape (here, represented by the quotient of leaf width and length) had a significant influence on the scaling exponent of leaf dry mass vs. area. Context The scaling of leaf dry mass vs. leaf area is important for understanding how plants effectively intercept sunlight and invest carbon to do so. However, comparatively few, if any, studies have focused on whether leaf shape influences this scaling relationship. Aims In order to explore the effects of leaf shape on the scaling relationship between leaf dry mass and area, we examined 101 species, varieties, forms, and cultivars of bamboo growing in China and identified the relationship between the scaling exponent of leaf dry mass vs. area and leaf shape. This taxon was used because its leaf shape is conserved across species and, therefore, easily quantified. Methods Ten thousand and forty-five leaves from 101 bamboo species, varieties, forms, and cultivars growing in China were collected, and leaf dry mass, the quotient of leaf width and length, leaf area, and leaf dry mass per unit area were measured. The effect of leaf shape that can be easily quantified using the quotient of leaf width and length on the relevant and ecologically important scaling exponents was explored using this data base. Results Leaf dry mass and area differed significantly across bamboo genera, and even within the same genus. However, a statistically robust log-log linear and positive scaling relationship was observed for mass and area with a 1.115 scaling exponent (95% CI = 1.107, 1.122; r2 = 0.907). Leaf shape had a significant influence on the numerical values of the scaling exponent of leaf dry mass vs. area. When the median of the quotient of leaf width and length was below 0.125, the numerical value of the scaling exponent increased with increasing quotient of leaf width and length. When the median of the quotient of leaf width and length was above 0.125, the scaling exponent numerically decreased toward 1.0. Conclusion We show, for the first time, that a significant relationship exists between leaf shape and the numerical values of scaling exponents governing the scaling of leaf dry mass with respect to leaf area. In addition, we show that with the quotient of leaf width and length increasing mean LMA increases, which implies a negative correlation between mean LMA and the estimated exponent of leaf dry mass vs. area for the grouped data based on the sorted quotients of leaf width and length.

The study was conducted to determine the impacts of environmental variations on yield and yield related properties of tobacco. The experimental layout was in the randomized blocks with three replicates in four different locations (Erbaa-Evciler, Erbaa-Karayaka, Gümüşhacıköy, Bafra) using 21 lines and four standard varieties that stand out with their different characteristics. The variation in plant height, number of leaves, leaf width, leaf length and leaf yield of genotypes were investigated at different ecologies. All the parameters investigated of the genotypes have been significantly affected by changing environmental conditions. Plant height ranged from 49.33 cm to 177.32 cm, the number of leaves from 21.83 to 47.10 per plant, leaf width from 6.83 to 16.31 cm, leaf length from 13.01 to 28.93 cm, and yield ranged from 79.17 kg-1 to 238.98 kg da-1. The results for the performances of genotypes in all environments showed that 5 lines (ERB-11, ERB-14, ERB-16, ERB-21, ERB-35) for plant height, 6 lines (ERB-6, ERB-7, ERB-11, ERB-14, ERB-16, ERB-35) for the number of leaves, 10 lines (ERB-9, ERB-16, ERB-17, ERB-18, ERB-19, ERB-21, ERB-25, ERB-26, ERB-27, ERB-30) for leaf width, 1 line (ERB-16) in for leaf length and 13 lines (ERB-6, ERB-7, ERB-9, ERB-13, ERB-16, ERB-18, ERB-19, ERB-21, ERB-25, ERB-27, ERB-30, ERB-35, ERB-38) for yield come to the fore.

The characteristic traits of maize (Zea mays L.) leaves affect light interception and photosynthesis. Measurement or estimation of individual leaf area has been described using discontinuous equations or bell-shaped functions. However, new maize hybrids show different canopy architecture, such as leaf angle in modern maize which is more upright and ear leaf and adjacent leaves which are longer than older hybrids. The original equations and their parameters, which have been used for older maize hybrids and grown at low plant densities, will not accurately represent modern hybrids. Therefore, the aim of this paper was to develop a new empirical equation that captures vertical leaf distribution. To characterize the vertical leaf profile, we conducted a field experiment in Jilin province, Northeast China from 2015 to 2018. Our new equation for the vertical distribution of leaf profile describes leaf length, width or leaf area as a function of leaf rank, using parameters for the maximum value for leaf length, width or area, the leaf rank at which the maximum value is obtained, and the width of the curve. It thus involves one parameter less than the previously used equations. By analysing the characteristics of this new equation, we identified four key leaf ranks (4, 8, 14 and 20) for which leaf parameter values need to be quantified in order to have a good estimation of leaf length, width and area. Together, the method of leaf area estimation proposed here adds versatility for use in modern maize hybrids and simplifies the field measurements by using the four key leaf ranks to estimate vertical leaf distribution in maize canopy instead of all leaf ranks.

The purpose of this research is to know the relationship between vegetative growth with sweet corn produced in experimental garden of Faculty of Agriculture Unilak. The environmental design used was a complete randomized design with 20 replications. Data analysis using correlation analysis. The parameters observed were plant height, leaf number, leaf length, leaf width, weight of cob weighing, cob weight without cornhusk, length of cob weighing, length of cob without cornhusk. The results showed that plant height, leaf number, and leaf width were significantly correlated with unbalanced cob weight, and correlated significantly with the length of cobs weighing and length of cobs without cornhusk. Plant height, leaf number, and leaf width did not give a significant correlation to the weight of cobs weighing. Weight of cobs weighing with unobstructed weight of cobs without real correlated weight, and long cobs without weight with weightlessness showed no real correlation.

We aimed to propose a reliable and accurate model using non-destructive measurements of leaf length (L) and/or width (W) for estimating leaf area (LA) of Surinam cherry ( Eugenia uniflora L.). For model construction, 560 leaves were randomly sampled from different levels of the tree canopies and encompassed the full spectrum of measurable leaf sizes. Power models better fit E. uniflora leaf area than linear models; but, among of then, the best fit were made when product of the L and W (LW) were used. To validate these models, independent data set of 156 leaves were used. Thus, we developed a single power model (Yi = β0 xβ1) [LA = 0.685 (LW)0.989; standard errors: β0 = 0.014, β1 = 0.005; R2 a = 0.997] with high precision and accuracy, random dispersal pattern of residuals and unbiased. A simpler linear model [LA = 0.094 + (LW * 0.655); standard errors: β0 = 0.025, β 1 = 0.001; R2 a = 0.998] also described here to estimate leaf area of E. uniflora, which are as good as the first. The simplicity of the latter model may be relevant in field studies, as it does not demand high precision or expensive instruments.

Research conducted an experiment using a completely randomized design environment with four replications, and the design of treatment used is six varieties of sweet corn. Analysis of data using polynomial regression, the parameters measured were plant height, leaf number, leaf length, leaf width, and sugar beans, followed by analyzing the relationship between the growth of plants with a sugar content of sweet corn kernels. The results showed that leaf width gives a weak relationship to the sugar content of sweet corn seed, and leaf length, number of leaves and plant height had a close relationship to the sugar content of sweet corn kernels. Keywords: varieties, sweet corn, correlation, sugar content

Background and purpose: Several studies have investigated multi leaf collimator (MLC) leaf design. We performed a systematic review and meta-analysis of those studies to compare the impact of MLC leaf width used for different radiotherapy techniques. Materials and methods: We decided to focus on 2.5, 3.0 and 5.0 mm leaf width MLCs as it appeared to be the most contentious area from literature. We adopted Cochrane and PRISMA guidelines and computed the association between MLC leaf width and conformity index (CI) across the selected studies as pooled mean difference (PMD) with 95% confidence interval. Results: A total of 43 papers were selected from the literature search, of which ten compare MLC leaf width of 2.5 mm or 3.0 mm (MLC2.5 mm) versus 5.0 mm (MLC5 mm) in terms of CI. There was a slight, but significant, difference between MLC2.5 mm and MLC5 mm in favor of the former (mean difference −0.036; 95% confidence interval: −0.068 to −0.005). A subgroup analysis was performed by comparing techniques (intensity modulated radiation therapy vs conformal). In the intensity modulated radiation therapy (IMRT) subgroup, the difference between MLC2.5 mm and MLC5 mm appeared to be negligible (mean difference: −0.006; 95% confidence interval: −0.013 to 0.001) and not significantly different from zero. In the subgroup of studies which used conformal techniques, there was a significant difference between MLC2.5 mm and MLC5 mm (mean difference: −0.054; 95% confidence interval: −0.096 to −0.012). Conclusions: Introduction of IMRT produced comparable target coverage (CI) between 2.5 or 5.0 mm leaf width MLCs. Keywords: Multi leaf collimators, Treatment planning system, Intensity modulated radiation therapy, Systematic review, Meta-analysis

We aimed to propose a reliable and accurate model using non-destructive measurements of leaf length (L) and/or width (W) for estimating leaf area (LA) of three genotypes of purging nut ( Jatropha curcas L.), i.e. Astrea and Barranca , both Colombian and a Mexican genotype. For model construction, ~500 healthy leaves were collected from at least 20 healthy plants naturally grown at each locations, and encompassed the full spectrum of measurable leaf sizes. Equations with L and/or W were generated; however, the best fit were made when product between L and W (LW). To validate these models, independent data set of 450 leaves were used. Thus, we developed a single model ( Y i = β 0 * LW β1 ) with high precision and accuracy, random dispersion pattern of residuals and unbiased. In spite of this, a single equation, joining all the studied genotypes, was developed [LA = 0.822 * (LW) 0.983 ; standard errors: β 0 = 0.020, β 1 = 0.004; R 2 a = 0.976], which greatly simplifies the process of measuring the leaf area of the genotypes, a fact that should be highlighted.

CO2 capture and storage (CCS) is an important technical strategy to reduce global CO2 emission from heavy industries. However, the risk of CO2 leakage in CCS-related projects cannot be ignored and it is crucial to identify and monitor CO2 leakage in CCS project areas in a timely and effective manner. So here we investigate the biological characteristics (plant height, leaf length, leaf width and SPAD value) and leaf spectral characteristics of maize under soil CO2 concentration of 10, 30, and 50%, with normal soil condition as control (CK). By analysing the original spectrum and first derivative spectrum of maize leaves, spectral parameters relatively sensitive to soil CO2 stress were extracted. Further, eight composite spectral characteristic indexes that are expected to identify CO2 leakages were constructed and analyzed. Besides, the normalized pigment chlorophyll index (NPCI) and modified chlorophyll absorption in reflectance index (MCARI) were also investigated for the indication role in CO2 leakage. The results showed that maize morphological traits had a significant hysteresis effect for the indication of CO2 leakage; the SPAD value was difficult to indicate the lower concentration of soil CO2 early. But it was found that three spectral characteristic indexes REP-BEP, RGP/RRV and RGP-RRV/RGP+RRV can effectively identify CO2 leakage, and three spectral characteristic indexes (RVP-GPP, REP-BEP and MCARI) can be used for quantitative inversion of soil CO2 concentration. Especially, REP-BEP index could both indicate CO2 leakage and quantitatively inverse soil CO2 concentration. In sum, the spectral characteristic indexes of maize leaves can be used as effective indicators to quickly and effectively identify CO2 leakage and quantitatively invert the CO2 concentration in soil.

O objetivo deste trabalho foi verificar a interação entre a calagem e a fosfatagem em diferentes profundidades no crescimento do Panicum maximum cv. Mombaça a fim de obter melhor manejo desses produtos de forma a ter uma recomendação adequada. O experimento foi conduzido no campo agrostológico situado na área experimental da Universidade Estadual de Mato Grosso do Sul - Unidade Universitária de Aquidauana. O delineamento foi inteiramente casualizado, com três repetições, disposto em esquema fatorial 4 x 5, com 4 saturações de base (sem calagem, V = 40 %, 50 % e 60 %) e 5 profundidades de fosfato natural de Bonito (sem fosfato, fosfato na superfície, 10cm, 20cm e 30 cm), totalizando 54 unidades experimentais. O solo utilizado para o experimento possuía 23,30 % de saturação de bases. Da parte aérea avaliou-se o comprimento das folhas, largura das folhas e número de perfilhos, além de produção de massa seca total (MST), massa de colmos (COL), massa de folhas (FOL), massa de material morto (MM) e a relação folha:colmo (F/C). Em relação às raízes foi observado comprimento de raiz (RAI) e massa seca total. A correção da saturação de bases para 40 % proporciona os melhores resultados de CF, LF e NP, independente da profundidade de aplicação de fósforo. A profundidade de aplicação de fósforo não altera as variáveis CR, MM, RAI, FOL, COL e F/C. A profundidade de aplicação de fósforo, na ausência de calagem, interferiu no CF, LF e NP. A adubação fosfatada é recomendada para independente da profundidade de aplicação.

Many plant species produce ovate leaves, but there is no general parametric model for describing this shape. Here, we used two empirical nonlinear equations, the beta and Lobry–Rosso–Flandrois (LRF) equations, and their modified forms (referred to as the Mbeta and MLRF equations for convenience), to generate bilaterally symmetrical curves along the x-axis to form ovate leaf shapes. In order to evaluate which of these four equations best describes the ovate leaf shape, we used 14 leaves from 7 Neocinnamomum species (Lauraceae) and 72 leaves from Chimonanthus praecox (Calycanthaceae). Using the AIC and adjusted root mean square error to compare the fitted results, the modified equations fitted the leaf shapes better than the unmodified equations. However, the MLRF equation provided the best overall fit. As the parameters of the MLRF equation represent leaf length, maximum leaf width, and the distance from leaf apex to the point associated with the maximum leaf width along the leaf length axis, these findings are potentially valuable for studying the influence of environmental factors on leaf shape, differences in leaf shape among closely related plant species with ovate leaf shapes, and the extent to which leaves are bilaterally symmetrical. This is the first work in which temperature-dependent developmental equations to describe the ovate leaf shape have been employed, as previous studies lacked similar leaf shape models. In addition, prior work seldom attempted to describe real ovate leaf shapes. Our work bridges the gap between theoretical leaf shape models and empirical leaf shape indices that cannot predict leaf shape profiles.

The experiment designed a completely randomized experimental design was carried out Adnan Menderes University, Agriculture Faculties greenhouse. Quinoa variety candidate named “Saponinsiz” is used experimental material. The seeds were sowed in plastic pots filled with soil and perlite (%50+%50) at the greenhouse with six replicates. Five different salt concentrations were determined as 0 (control), 4 ds m-1, 8 ds m-1, 16 ds m-1 and 30 ds m-1 and were applied with NaCl solution which was prepared before sowing. Leaf number, leaf length, leaf width, leaf thickness, stem thickness and green biomass weight values ​​were measured when the quinoa plant reached 6 leaf stage. As a result of the study, it was observed that the differences between the salt concentrations in leaf number, leaf length, leaf width and green biomass weight were significant. The maximum leaf length (11.53 mm) was measured with 8 ds m-1 salt concentration applied plants, whereas the maximum leaf width (4.99 mm) and green biomass (1019.5 mg) were measured with 4 ds m-1. The control plot only showed the highest values ​​for the leaf number value. These results confirmed that the quinoa plant was facultative halophytic species (salt-resistant). It was determined that 16 ds m-1 dose gave the lowest values in all measurements. And any plant wasn’t growing at the 30 ds m-1 applied pots. The values of the experiment measured of 4 ds m-1 pots and 8 ds m-1 pots, which is considered the limit values for the field crops, were approximately equal or greater than control pots. Moreover, there was a rapid decline of plant on the 16 ds m-1 values., Theexperiment designed a completely randomized experimental design was carried outAdnan Menderes University, Agriculture Faculties greenhouse. Quinoa variety candidatenamed “Saponinsiz” is used experimental material. The seeds were sowed in plasticpots filled with soil and perlite (%50+%50) at the greenhouse with six replicates.Five different salt concentrations were determined as 0 (control), 4 ds m-1,8 ds m-1, 16 ds m-1 and 30 ds m-1 and were appliedwith NaCl solution which was prepared before sowing. Leaf number, leaf length, leafwidth, leaf thickness, stem thickness and green biomass weight values ​​were measured when the quinoaplant reached 6 leaf stage. As a result of the study, it was observed that the differencesbetween the salt concentrations in leaf number, leaf length, leaf width and greenbiomass weight were significant. The maximum leaf length (11.53 mm) was measuredwith 8 ds m-1 salt concentration applied plants, whereas the maximumleaf width (4.99 mm) and green biomass (1019.5 mg) were measured with 4 ds m-1. The control plot only showed the highestvalues ​​for the leafnumber value. These results confirmed that the quinoa plant was facultative halophyticspecies (salt-resistant). It was determined that 16 ds m-1 dose gavethe lowest values in all measurements. And any plant wasn’t growing at the 30 dsm-1 applied pots. The values of the experiment measured of 4 ds m-1pots and 8 ds m-1 pots, which is considered the limit values for thefield crops, were approximately equal or greater than control pots. Moreover, therewas a rapid decline of plant on the 16 ds m-1 values.

Leaf Area (LA) is a key index of plant productivity and growth. A multiple linear regression technique is commonly applied to estimate LA as a non-destructive and quick method, but this technique is limited under the realistic situation. Thus, it is indispensable to elaborate new models for estimation. In this research, the performance of the Adaptive Neural-Based Fuzzy Inference System (ANFIS) in predicting the LA of 61 plant species (C) was investigated. Four parameters including leaf length (L), leaf width (W), C, and specific coefficient (K) for each plant were selected as input data to the ANFIS model and the LA as the output. Seven different ANFIS models including different combinations of input data were constructed to reveal the sensitivity analysis of the models. The normalized root mean square error (NRMSE), mean residual error (MRE), and linear regression were applied between observed LA and estimated LA by the models. The results indicated that ANFIS4-K2min which employed all input dat...

Non destructive estimation of leaf area is necessary for taking successive observations on the same leaf. Usually, a common method for developing leaf area estimation models was to execute regression analysis by taking leaf area as dependant variable and leaf parameters as independent variables. However, the regression analysis applicable only when there is a relation between dependent and independent variables. Therefore, the objective of this work was to develop an artificial neural network (ANN) model including leaf length and leaf width as inputs and to make comparison with regression models. Leaf area (LA) of Durain (Durio zibethinus) was estimated by ANN and regression models. Among the linear regression models (LRM), the equation LA = 0.888 (L*W) − 4.961 (R2 = 0.91, MSE = 5.17) was found to be the best fitting for durian. In ANN modelling best fitting results were obtained with two input nodes (leaf length and leaf width), one hidden layer, and one output layer (leaf area) as 2-1-1. Based on the values of root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and coefficient determination (R2), ANN model was found to be more accurate both in terms of training (R2 = 0.96, RMSE = 3.77, MAE = 2.41 and MAPE = 7.77) and testing phases (R2 = 0.94, RMSE = 4.81, MAE = 2.91 and MAPE = 0.05) than the best fitting regression model. Hence ANN method may be used as an alternative or supportive model in the estimation of leaf area of durian.

Artificial neural network (ANN) is applied for many subjects in agricultural science such as: crop yield and evapotranspiration prediction, soil parameters estimation, water demand forecasting, hydrological forecasting. Leaf area is one of parameters that is used to assess the plant vegetative growth. In this study, leaf areas of 61 plant species with different leaf shapes were estimated by ANNs and the effect of input data and pre-processing methods on ANNs performance was assessed. Results showed that the ANNs could provide good estimation of leaf area. ANNs input variable combination affected the ANNs performance to estimate the leaf area. With increase in number of hidden layers the epochs decreased and accuracy of the leaf area prediction and running speed increased. Results of test data set showed that MinMax pre-processing method resulted in more accurate prediction in comparison with the no pre-processed method and Norm STD method. The most conclusive result of this study is the application of ANNs for all of plant species, whereas, in application of other methods: specific equation should be prepared for each plant.

Introduction: This study explores the feasibility of SRS/SRT treatment with MLC leaves wider than 2.5 mm at isocenter by inter-comparing treatment plans produced with 2.5, 5.0, and 10.0 mm leaves for various target sizes and shapes. Materials and methods: Forty previously treated patients were re-planned using 2.5, 5.0, and 10.0 mm wide MLC leaves. For each patient, all three plans were evaluated and contrasted between them in terms of five metrics: target dose homogeneity, conformity index, organs at risk dose, dose fall off outside the target, and dose to normal tissues. A regularity index RI was introduced that quantified the degree of target shape irregularity. The effect of target size and shape irregularity on feasibility of 5.0 and 10.0 mm leaves was analyzed. Results: Consistent plan degradation was observed for 10.0 mm (sometimes for 5.0 mm) compared to 2.5 mm MLC in terms of the above five plan metrics, but this degradation was small to clinically insignificant. As an exception, when target (PTV) size was smaller than about 1 cm diameter, clinically significant differences were found between 2.5, 5.0, and 10.0 mm MLC. Conclusion: 5.0 and 10.0 mm MLC can be used in SRS/SRT for targets (PTV) diameter larger than 1 cm. For smaller targets, 2.5 mm MLC is clinically superior, 5.0 is acceptable and 10.0 mm MLC is discouraged in terms of PTV dose conformity.

In this research, seven different models to predict leaf area (LA) of loquat (Eriobotrya japonica Lindl) were tested and evaluated. This species was chosen due to the relevant importance of its fruit as an appreciated early summer product and of its leaves and flower as a source of additional income within the nutraceutical and functional food markets. The analysis (calibration and validation) was made using a large dataset (2190) of leaf width (W), leaf length (L), and single LA collected in ten common loquat cultivars. During the analysis, the results obtained using one- and two-regressor models were also evaluated to assess the need for fast measurements against different levels of accuracy achieved during the final estimate. The analysis permitted to finally select two different models: 1) a model based on a single measurement and quadratic relationship between the single LA and W (R2 = 0.894, root mean squared error [RMSE] = 12.98) and another model 2) based, instead, on two measurements (L and W), and on the linear relationship between single LA and the product of L &times, W (R2 = 0.980, RMSE = 5.61). Both models were finally validated with an independent dataset (cultivar &lsquo, Tanaka&rsquo, ) confirming the quality of fitting and accuracy already observed during the calibration phase. The analysis permitted to select two different models to be used according to the aims and accuracy required by the analysis. One, based on a single-regressor quadratic model and W (rather than L) as a proxy variable, is capable of obtaining a good quality of fitting of the single LA of loquat cultivars (R2 = 0.894, RMSE = 12.98), whereas, the other, a linear two-regressor (i.e., W and L) model, permitted to achieve the highest prediction (R2 = 0.980, RMSE = 5.61) of the observed variable, but double the time required for leaf measurement.

The simplified Gielis equation (SGE) can approximately describe the leaf shapes of many different broad-leaved plant species by replacing two parameters of the SGE with leaf width and leaf length with a floating ratio (c–value) to adjust for leaf length. In this study, we tested the validity of the SGE in predicting leaf area using 20 bamboo species, 12 species of Rosaceae, 5 species of Lauraceae, and 5 species of Oleaceae. We find that c–values in leaf length for 20 bamboo species are all smaller than zero, whereas, for most tree species, c–values are larger than zero. Using c–values, there was a strong correlation (>0.99 for most of the species investigated) between actual and predicted leaf area. Also, using the SGE to fit the leaf profile data, the predicted leaf width approaches its actual value, whereas the predicted length is larger than or smaller than its actual value (for bamboo species and most tree species, respectively). Although c–values ranged from −15% to zero for bamboo species and from zero to 17% for tree species, the mean percent error in leaf area for most species did not exceed 5%. These findings indicate that leaves exhibit more variation in length than in width, i.e., leaf area is fairly conservative despite considerable variation in leaf shape. Given that the SGE adequately describes the areas of leaves with complex forms (e.g., several species of Rosaceae), our data indicate that the SGE is a useful tool for describing leaf morphometrics and may open a door for the study of leaf shape evolution. Keywords: Gielis equation, Floating ratio, Lamina area, Lamina length, Lamina width, Percent error

According to Thompson’s principle of similarity, the area of an object should be proportional to its length squared. However, leaf area–length data of some plants have been demonstrated not to follow the principle of similarity. We explore the reasons why the leaf area–length allometry deviates from the principle of similarity and examine whether there is a general model describing the relationship among leaf area, width and length. We sampled more than 11,800 leaves from six classes of woody and herbaceous plants and tested the leaf area–length allometry. We compared six mathematical models based on root-mean-square error as the measure of goodness-of-fit. The best supported model described a proportional relationship between leaf area and the product of leaf width and length (i.e., the Montgomery model). We found that the extent to which the leaf area–length allometry deviates from the principle of similarity depends upon the extent of variation of the ratio of leaf width to length. Estimates of the parameter of the Montgomery model ranged between 1/2, which corresponds to a triangular leaf with leaf length as its height and leaf width as its base, and π/4, which corresponds to an elliptical leaf with leaf length as its major axis and leaf width as its minor axis, for the six classes of plants. The narrow range in practice of the Montgomery parameter implies an evolutionary stability for the leaf area of large-leaved plants despite the fact that leaf shapes of these plants are rather different.

Tobacco is an important trade commodity in Indonesia because it supports the country’s economy through taxes and excise. The path analysis is used to measure the direct and indirect effects of agronomic character parameters that are strongly correlated with the results. The path analysis in this study aims to find the agronomic characteristics of tobacco that can be used as selection criteria to get high krosok production. The number of samples used was 50 plants. Observation parameters included plant height, stem diameter, number of leaves per plant, foot leaf length, foot leaf width, middle leaf length, middle leaf width, shoot leaf length, shoot leaf width, leaf wet weight, yield, heavyweight. The results showed the wet weight of the leaves can be used as direct selection criteria. The fresh weight of the leaves has a high positive correlation (Rx10y = 0.812), a high positive direct effect (Px10y = 0.924), and a contribution value of 75.007%.

A model for estimating the area of individual leaves (LA) by employing their dimensions was developed for chrysanthemum. Further hypotheses were tested: (a) LA estimation is improved by considering blade length (Lb) rather than leaf length (L), and (b) a reasonable LA estimation can be attainable by considering L in conjunction to a shape trait, which is cultivar dependent. For the model development, six cultivars were employed (1500 leaves in total), while for model validation, an independent set of nine cultivars was utilized (1125 leaves in total). Several characteristics were digitally assessed in fully expanded leaves which included petiole length, leaf L, width (W), perimeter, shape traits (aspect ratio, circularity, roundness, solidity), together with LA. LA estimation was more accurate by considering both L and W, as compared to a single dimension. A linear model, employing the product of L by W as independent variable, provided the most accurate LA estimation (R2 = 0.84). The model validation indicated a highly significant correlation between computed and measured LA (R2 = 0.88). Replacing L by Lb reasonably predicted LA (R2 = 0.832) but at some expense of accuracy. Contrary to expectation, considering L (or W) and a cultivar-specific shape trait generally led to poor LA estimations.

The growth of maize is a complex phenomenon which involves certain parameters including the number of leaves, the length of the leaves, the width of the leaves, the height and the circumference of the plant. A study of these growth parameters was carried out in the region of Daloa (Cote d’Ivoire). These measurements could show a complexity of the growth of maize. To this end, mathematical models have been developed to predict this growth from artificial neural networks for the number of leaves, the length of the leaves, the width of the leaves, the height of the plant and the circumference of the trunk of the maize plant. The coefficients of determination between the experimental measurements and the measurements predicted by artificial neural networks are respectively 0.9914; 0.9965; 0.9872; 0.9995 and 0.9976 for plant height; the number of leaves; the circumference of the plant; leaf length and leaf width. Satisfactory results have been obtained insofar as all the coefficients of determination are greater than 0.98. These coefficients close to 1 show a good interpolation between the experimental values and those predicted by the model. Because of this, we can say that the values predicted by the artificial neural network are reliable enough to predict the growth of maize.