Maturity Date Research Articles

Phenological Changes of Soybean in Response to Climate Conditions in Frigid Region in China over the Past Decades

Plant phenology becoming a focus of current research worldwide is a sensitive indicator of global climate change. To understand observed soybean phenology and explore its climatic determinants in frigid region (Northeast China and northeast in Inner Mongolia), we studied the phenological changes of soybean [Glycine max (L.) Merr.] for the frigid region during 1981–2017, then analyzed the contribution of major causal climate factors to phenology based on multiple stepwise regression. Altogether, the average temperature from sowing to maturity (WGP) was significant increasing, accumulated precipitation and sunshine hours were decreasing. More than 50% of observations showed delays in sowing, emergence and maturity stage and short durations of sowing to flowering (VGP), flowering to maturity (RGP) and sowing to maturity (WGP). The late sowing was getting the following phenological timing backward, but the flowering and maturity delaying trends were much less than that of sowing timing due to the warming accelerated growth of soybean. Detailed analysis indicated mean temperature and accumulated precipitation of the 1–3 months immediately preceding the mean emergence, flowering and maturity dates influenced the phenological timing in higher latitude areas (HLJ and FL), while in JL and LN, accumulated precipitation and sunshine hours(replacing mean temperature) were the climatic determinants. These results brought light the importance of research and policy to support strategies for adaptation to local condition under the climate change.

Sequential Monte Carlo Filters with Parameters Learning for Commodity Pricing Models

In this article, an estimation methodology based on the sequential Monte Carlo algorithm is proposed, thatjointly estimate the states and parameters, the relationship between the prices of futures contracts and the spot prices of primary products is determined, the evolution of prices and the volatility of the historical data of the primary market (Gold and Soybean) are analyzed. Two stochastic models for an estimate the states and parameters are considered, the parameters and states describe physical measure (associated with the price) and risk-neutral measure (associated with the markets to futures), the price dynamics in the short-term through the reversion to the mean and volatility are determined, while that in the long term through markets to futures. Other characteristics such as seasonal patterns, price spikes, market dependent volatilities, and non-seasonality can also be observed. In the methodology, a parameter learning algorithm is used, specifically, three algorithms are proposed, that is the sequential Monte Carlo estimation (SMC) for state space modelswith unknown parameters: the first method is considered a particle filter that is based on the sampling algorithm of sequential importance with resampling (SISR). The second implemented method is the Storvik algorithm [19], the states and parameters of the posterior distribution are estimated that have supported in low-dimensional spaces, a sufficient statistics from the sample of the filtered distribution is considered. The third method is (PLS) Carvalho’s Particle Learning and Smoothing algorithm [31]. The cash prices of the contracts with future delivery dates are analyzed. The results indicate postponement of payment, the future prices on different maturity dates with the spot price are highly correlated. Likewise, the contracts with a delivery date for the last periods of the year 2017, the spot price lower than the prices of the contracts with expiration date for 12 and 24 months is found, opposite occurs in the contracts with expiration date for 1 and 6 months.

Variation of Morphological, Agronomic and Chemical Composition Traits of Local Hazelnuts Collected in Northern Spain.

Hazelnut is a traditional crop in northern Spain, where it grows wild as well as being cultivated. A field collection of 41 local and 17 non-local accessions, including 15 well-known cultivars, was established at SERIDA in Villaviciosa, Spain. Here, phenotypic variation was documented for phenological and morphological traits and chemical composition. A large degree of variation for most morphological and phenological traits, except nut maturity date, was revealed. Estimates of broad-sense heritability were high (>0.75) for most of the assessed characters, except for the first male bloom date (0.65), male and female flowering periods (0.40, 0.31), kernel weight (0.69), and kernel percentage (0.33). Local accessions produced smaller nuts and kernels than well-known cultivars but with higher kernel percentage. Limited overlapping between the male and female flowering periods (dychogamy) was observed, except for ‘Forcinas 1’, ‘Forcinas 2’, and ‘Morell’. The local accessions generally exhibited significantly later male and female flowering compared with the reference cultivars. The local materials showed similar nutritional values to those reported previously for hazelnut. Moreover, the local accessions presented average values similar to the non-local accessions for total fat, ash and carbohydrate contents, as well as energy value, but their protein contents were lower. Their oils were rich in functional compounds, such as unsaturated fatty acids (average: 90.1%), tocopherols (514 mg/kg) and squalene (294.3 mg/kg). A hierarchical clustering on principal components analysis grouped the accessions and differentiated eight local accessions from the rest, including the landrace ‘Casina’. This finding provides potential new cultivars, as well as sources of desirable traits, for European hazelnut breeding programs.

Molecular genetic diversity and population structure analyses of rutabaga accessions from Nordic countries as revealed by single nucleotide polymorphism markers

BackgroundRutabaga or swede (Brassica napus ssp. napobrassica (L.) Hanelt) varies in root and leaf shape and colour, flesh colour, foliage growth habits, maturity date, seed quality parameters, disease resistance and other traits. Despite these morphological differences, no in-depth molecular analyses of genetic diversity have been conducted in this crop. Understanding this diversity is important for conservation and broadening the use of this resource.ResultsThis study investigated the genetic diversity within and among 124 rutabaga accessions from five Nordic countries (Norway, Sweden, Finland, Denmark and Iceland) using a 15 K single nucleotide polymorphism (SNP) Brassica array. After excluding markers that did not amplify genomic DNA, monomorphic and low coverage site markers, the accessions were analyzedwith 6861 SNP markers. Allelic frequency statistics, including polymorphism information content (PIC), minor allele frequency (MAF) and mean expected heterozygosity ( overline{H} e) and population differentiation statistics such as Wright’s F-statistics (FST) and analysis of molecular variance (AMOVA) indicated that the rutabaga accessions from Norway, Sweden, Finland and Denmark were not genetically different from each other. In contrast, accessions from these countries were significantly different from the accessions from Iceland (P < 0.05). Bayesian analysis with the software STRUCTURE placed 66.9% of the rutabaga accessions into three to four clusters, while the remaining 33.1% constituted admixtures. Three multivariate analyses: principal coordinate analysis (PCoA), the unweighted pair group method with arithmetic mean (UPGMA) and neighbour-joining (NJ) clustering methods grouped the 124 accessions into four to six subgroups.ConclusionOverall, the correlation of the accessions with their geographic origin was very low, except for the accessions from Iceland. Thus, Icelandic rutabaga accessions can offer valuable germplasm for crop improvement.

Asian rainbow option pricing formulas of uncertain stock model.

Asian rainbow option is option on the minimum or the maximum of several average prices. In modern financial market, Asian rainbow option is an effective instrument for asset allocation and risk management. The investor with Asian rainbow option enjoys an entitlement to select a max or min from multiple assets with an exercise price at maturity date. The investor has to defray fee to acquire this right, which raises the option pricing issue. This paper mainly explores the pricing of Asian rainbow option in the uncertain financial environment, in which the underlying assets prices are treated as uncertain processes. Here, the pricing formulas of Asian rainbow option are derived under the condition that stock prices obey uncertain differential equations driven by independent Liu processes. Furthermore, some numerical examples are designed to compute the prices of these options.

Producing a superior genotype from agria potato cultivar using somaclonal variation

This study was performed to produce a superior genotype from Agria potato cultivar using somaclonal variation. Two leaf and meristem explants in combination with four doses of 2,4-D (0, 2, 3 and 4 mg / l) were used for callus induction in a factorial model based on a completely randomized design with 3 replications. Results showed that the meristem explant, along with 3 mg 2,4-D produced the most suitable calluses. In the mentioned regeneration media, the best calluses were regenerated and one of the regenerated genotypes, which was very different from the parent cultivar was selected. The regenerated genotype, was compared with the maternal genotype (Agria) and a control cultivar (Sante), in a field experiment based on a randomized complete block design with 3 replications. The results showed that in terms of most of the studied traits such as tuber weight per plant, stolon length, percentage of dry matter and percentage of starch, the new genotype was superior, compared to the parent cultivar and in terms of peel percentage and maturity date, the parental cultivar was superior. The results of the molecular comparison also showed that based on CBDP marker, both in terms of band number and band size, there were differences between the new genotype and the parental cultivar. In general, results showed that somaclonal variation can be an effective method to generate new genotypes with superior characteristics.

English

Greenhouse experiments were conducted to investigate the effects of various vermicompost amendments on growth responses and nutrient content of kale (Brassica oleracea Acephala group), radish (Raphanus sativus), and tomato (Solanum lycopersicum L), using a completely randomized design with three crop species, four vermicompost treatments and four replications. The twelve treatment combinations consisted of vermicompost levels of 0, 5, 10, and 15% (v/v) and three crop species, kale, radish and tomato. Plants were grown in pots containing soil in which the respective vermicompost levels were incorporated. Three seeds of each species were sown in each pot and seedlings were thinned to one per pot each, approximately two weeks after germination. Plants were supplied at regular intervals with 300 ml of water to maintain field capacity. Plant height, leaf chlorophyll, stem diameter, and leaf expansion rates were collected at weekly intervals beginning three weeks after planting. Plants were harvested at respective maturity dates, and fresh and dry weights as well as total yield were taken. Root, leaf and fruit samples were collected to determine phenolic and ascorbic acid content. Vermicompost soil amendment significantly increased plant height of kale and radish compared to the control but had no significant effect on the height of tomato plants. Leaf chlorophyll content was also greater among plants receiving vermicompost amendments except that of kale which declined at highest amendment level.&nbsp; Fresh and dry weight of kale increased with levels of vermicompost amendments with the magnitude of increase being greater between the control plants and those amended with 5%. Tap root yield of radish was highest among plants amended with 15% vermicompost but yield was similar among amended treatments. Regardless of the treatment, stem diameter was highest in the last few weeks of measurements. Total phenolic content tended to decrease regardless of species with increasing vermicompost levels and vitamin C increased initially up to 10% level for kale and declined thereafter, while there was a steady decline in radish. These results show that vermicompost amendments above 10% may adversely affect plant height and leaf chlorophyll content, while enhancing overall biomass production, and that phenolic and vitamin C responses varied based on vermicompost levels. Keywords: Compost, sustainability, soil, organic matter, chlorophyll.

Determination of Key Phenological Phases of Winter Wheat Based on the Time-Weighted Dynamic Time Warping Algorithm and MODIS Time-Series Data

Accurate determination of phenological information of crops is essential for field management and decision-making. Remote sensing time-series data are widely used for extracting phenological phases. Existing methods mainly extract phenological phases directly from individual remote sensing time-series, which are easily affected by clouds, noise, and mixed pixels. This paper proposes a novel method of phenological phase extraction based on the time-weighted dynamic time warping (TWDTW) algorithm using MODIS Normalized Difference Vegetation Index (NDVI) 5-day time-series data with a spatial resolution of 500 m. Firstly, based on the phenological differences between winter wheat and other land cover types, winter wheat distribution is extracted using the TWDTW classification method, and the results show that the overall classification accuracy and Kappa coefficient reach 94.74% and 0.90, respectively. Then, we extract the pure winter-wheat pixels using a method based on the coefficient of variation, and use these pixels to generate the average phenological curve. Next, the difference between each winter-wheat phenological curve and the average winter-wheat phenological curve is quantitatively calculated using the TWDTW algorithm. Finally, the key phenological phases of winter wheat in the study area, namely, the green-up date (GUD), heading date (HD), and maturity date (MD), are determined. The results show that the phenological phase extraction using the TWDTW algorithm has high accuracy. By verification using phenological station data from the Meteorological Data Sharing Service System of China, the root mean square errors (RMSEs) of the GUD, HD, and MD are found to be 9.76, 5.72, and 6.98 days, respectively. Additionally, the method proposed in this article is shown to have a better extraction performance compared with several other methods. Furthermore, it is shown that, in Hebei Province, the GUD, HD, and MD are mainly affected by latitude and accumulated temperature. As the latitude increases from south to north, the GUD, HD, and MD are delayed, and for each 1° increment in latitude, the GUD, HD, and MD are delayed by 4.84, 5.79, and 6.61 days, respectively. The higher the accumulated temperature, the earlier the phenological phases occur. However, latitude and accumulated temperature have little effect on the length of the phenological phases. Additionally, the lengths of time between GUD and HD, HD and MD, and GUD and MD are stable at 46, 41, and 87 days, respectively. Overall, the proposed TWDTW method can accurately determine the key phenological phases of winter wheat at a regional scale using remote sensing time-series data.

Simulating upland rice yield at diverse temperatures using DSSAT4.7-CERES-Rice crop model under changing climatic conditions in southern Thailand

Declaration of climate emergency reminds that the main source of variations in worldwide food production sourced from developing countries and is of utmost concern. Process-based models use simplified functions to express the interactions between upland rice growth and the major environmental factors (i.e., climate, soils, and management) that affect crops yield. This research was conducted to investigate the DSSAT-CERES-Rice model for simulating the impact of different temperature (28˚C, 30˚C and 32˚C) on upland grain yield (Dawk Pa-yawm, Mai Tahk, Bow Leb Nahng, Dawk Kha 50 and Dawk Kahm). The results showed that the temperature significantly affected the grain yield, flowering, and maturity date. The highest grain yield bearing genotype was Bow leb Nahng (6235.80 kgha -1 ) with the highest variation between the genotypes. At maximum temperature 32˚C simulated grain yield varied from (3194-6669) kgha -1 , at high temperature 30˚C it varied from 3252-6667 kgha -1 while at moderate temperature 28˚C 3189-6711 kgha -1 was the observed range. However, results indicated that moderate temperature i.e., 28˚C gave the highest simulated grain yield. Thus, it was demonstrated that the CERES-Rice model was more useful as a tool for simulating grain yield under the changing different temperature conditions.

Optimal timing of investments modeled as perpetual American options in a Levy market

Using a real option approach, this paper models an arbitrary real life investment, which typically has a long maturity date, as a perpetual American call option in a Levy market. Expressions for the moments, characteristic function and infinitesimal generator of the associated jump-diffusion Levy process, defined by two independent compound Poisson processes and two correlated standard Brownian motions, are derived and these fundamental results are employed to determine the optimal time for investment. An application of the results to a Build Operate and Transfer investment is furnished.

EVALUATION OF YIELD AND RESISTANCE TO COTTON LEAF WORM FOR SOME NEW GENOTYPES OF SOYBEAN UNDER OLD LANDS AND NEWLY RECLAIMED LANDS CONDITIONS IN EL-BEHEIRA GOVERNORATE

A field traial allowed in completely randomized design with three replications were conducted in the research farm of the agricultural research station of Etay Al-Baroud (old land) and the research farm of the Faculty of Agriculture, Damanhur University, in El-Bostan region, El-Beheira Governorate (newly reclaimed lands) during 2018 and 2019 seasons to evaluate the performance of twelve new genotypes of soybean compared with the three commercial varieties Giza 111, Giza 22 and Crawford. The resistance of genotypes to cotton leaf worm was estimated in the laboratory by raising a fourth instar larvae of cotton leaf worm and leaving them for feeding on the middle leaflet of the third upper trifoliate leaf of the plant for 24 hours, after that the areas that the insect fed on were measured as a percentage of the total area of the leaf (leaf area consumed). The resistance to cotton leaf worm in the field was estimated by vision according to the Smith and Brim 1979 method (defoliation %). The results confirmed that mean square due to genotypes, locations and genotypes x location were highly significant for all studied traits except the locations mean square for number of hairs under binocular field area and branches number /plant in the first season and genotypes x location mean square of number of hairs under binocular field area, branches number /plant, maturity date and 100-seed weight in both seasons as well as number of pods/plant in the second season. All tested genotypes significantly differ in their performances in all studied traits across the two locations and the four genotypes Line 3, Line 105, Line 127 and Line 129 seemed to excellent genotypes for yield and resistance to cotton leaf worm across the two locations. The consumed leaf area caused by cotton leaf worm and oil percentage negatively associated with pubescence density while seed yield positively associated with pubescence density. Seed yield and oil percentage negatively associated with the defoliation value. In general, it can be said that the four soybean genotypes, Line 3, Line 105, Line 127 and Line 129 are promising genotypes that could be sowing in newly reclaimed lands to expand soybean cultivation in Egypt.

Shortened key growth periods of soybean observed in China under climate change

Phenology is an important indicator of global climate change. Revealing the spatiotemporal characteristics of crop phenology is vital for ameliorating the adverse effects of climate change and guiding regional agricultural production. This study evaluated the spatiotemporal variability of soybean’s phenological stages and key growth periods, and assessed their sensitivity to key climatic factors, utilizing a long-term dataset (1992–2018) of soybean phenology and associated meteorological data collected at 51 stations across China. The results showed that (1) during the soybean growing seasons from 1992 to 2018, the average temperature (0.34 ± 0.09 ℃ decade−1) and cumulative precipitation (6.66 ± 0.93 mm decade−1) increased, but cumulative sunshine hours (− 33.98 ± 1.05 h decade−1) decreased. (2) On a national scale, dates of sowing, emergence, trifoliate, anthesis, and podding of soybean were delayed, while the maturity date showed an advancing trend. The vegetative growth period (− 0.52 ± 0.24 days decade−1) and whole growth period (− 1.32 ± 0.30 days decade−1) of soybean were shortened, but the reproductive growth period (0.05 ± 0.26 days decade−1) was slightly extended. Trends in soybean phenological stages and key growth periods diverged in regions. Soybean phenological stages were delayed in Huang-Huai-Hai soybean zone, whereas advanced in southern soybean zone. Moreover, the key growth periods were greatly shortened in northern soybean zone. (3) In general, the sensitivity of soybean key growth periods to temperature was negative, whereas those to precipitation and sunshine hours differed among regions. In particular, most phenological stages were negatively sensitive to sunshine hours. Our results will provide scientific support for decision-making in agricultural production practices.

Modeling growth, development and yield of cassava: A review.

Cassava is an important crop in the developing world. The goal of this study was to review published cassava models (18) for their capability to simulate storage root biomass and to categorize them into static and dynamic models. The majority (14) are dynamic and capture within season growth dynamics. Most (13) of the dynamic models consider environmental factors such as temperature, solar radiation, soil water and nutrient restrictions. More than half (10) have been calibrated for a distinct genotype. Only one of the four static models includes environmental variables. While the static regression models are useful to estimate final yield, their application is limited to the locations or varieties used for their development unless recalibrated for distinct conditions. Dynamic models simulate growth process and provide estimates of yield over time with, in most cases, no fixed maturity date. The dynamic models that simulate the detailed development of nodal units tend to be less accurate in determining final yield compared to the simpler dynamic and statistic models. However, they can be more safely applied to novel environmental conditions that can be explored in silico. Deficiencies in the current models are highlighted including suggestions on how they can be improved. None of the current dynamic cassava models adequately simulates the starch content of fresh cassava roots with almost all models based on dry biomass simulations. Further studies are necessary to develop a new module for existing cassava models to simulate cassava quality.

Joint Influence Mechanism of Phenology and Climate on the Dynamics of Gross Primary Productivity: Insights From Temperate Deciduous Broadleaf Forests in North America

AbstractUnderstanding the influence mechanism of biotic and abiotic factors on the dynamics of gross primary productivity (GPP) is crucial to accurately simulate the terrestrial carbon cycle. Based on the carbon flux data, meteorological data (i.e., temperature, precipitation, vapor pressure deficit, and radiation) and phenological metrics (i.e., the date of greenup, maturity, senescence, and dormancy) collected from six North America temperate deciduous broadleaf forests (NAT‐DBF) sites, this study investigated the joint influence mechanism of phenology and climate on the dynamics of GPP by using commonality analysis and structural equation modeling. The results showed that precipitation, the date of maturity and senescence jointly dominated the dynamics of annual GPP in NAT‐DBF. The date of maturity and senescence rather than the date of greenup and dormancy were crucial phenological metrics that directly influenced the dynamics of annual GPP. There existed an important indirect influence path of temperature on the dynamics of annual GPP through regulating the date of maturity, while the direct influence of temperature on the dynamics of annual GPP was negligible. Precipitation not only directly influenced the dynamics of annual GPP, but also indirectly influenced the dynamics of annual GPP through regulating the date of senescence. Our study provides a process‐based understanding for the joint influence mechanism of meteorological factors and phenology on the dynamics of annual GPP, which is helpful for understanding the vegetation responses to climate change and improving the process‐based ecosystem models.

Optimum Sowing Window and Yield Forecasting for Maize in Northern and Western Bangladesh Using CERES Maize Model

Determination of the optimum sowing window not only can improve maize yield significantly but also can fit maize in the existing cropping pattern. To get the advantages of sowing maize at the optimum time, a study was designed and carried out at the research field of Bangladesh Agricultural Research Institute, Rangpur, Bangladesh during 2015–2017. Another aim of the study was to forecast the yield of maize for the northern and western regions of Bangladesh using the CERES-Maize model. The study considered 5 November, 20 November, 5 December, 20 December, and 5 January as sowing dates for maize to identify the optimum sowing window. Three hybrid maize varieties, viz., BARI Hybrid Maize-9 (BHM-9), NK-40, and Pioneer30V92 were used. The study was laid out in a split-plot design, assigning the sowing dates in the main plot and the varieties in the sub-plot. To forecast the yield, the daily weather data of 2017 were subjected to run the model along with thirty years (1986–2015) of weather data. The genetic coefficients of the tested maize varieties were obtained through calibration of the model by using the observed field data of 2015–2016 and through validation by using the data of 2016–2017. The seasonal analysis was done using the DSSAT CERES-Maize model to confirm the experimental findings for optimizing the sowing window for maize at the northern region (Rangpur) of the country and subsequently adjusted the model for the western region (Jashore). The model performances were satisfactory for crop phenology, biomass, and grain yield. The NRMSE for anthesis was 0.66% to 1.39%, 0.67% to 0.89% for maturity date, 1.78% to 3.89% for grain yield, and 1.73% to 3.17% for biomass yield. The optimum sowing window for maize at the Rangpur region was 5 November to 5 December and 5 to 20 November for the Jashore region. The CERES-Maize model was promising for yield forecasting of the tested maize varieties. It gave a realistic yield forecast at approximately 45 days prior to the harvest of all the tested varieties. The study results are expected to be useful for both the farmers and the policy planners to meet up the future maize demands.

Impact of climate change and crop management on cotton phenology based on statistical analysis in the main-cotton-planting areas of China

Phenology is one of the prominent indicators for studying the impact of climate change on crop production. Based on cotton phenology and meteorological data from 79 agricultural weather stations in China between 1981 and 2017, the Pearson correlation, multi-variate linear regression and path analysis are applied to investigate the spatial and temporal changes of cotton phenological indices and climate variables (precipitation (Pre), sunshine duration (Sun), average (Tave), minimum (Tmin) and maximum temperatures (Tmax), influence degrees of Pre, Sun, and Tave on phenology, and isolated effects of climate change and crop management on cotton phenology. The results showed that: (1) Emergence (Eme), squaring (Squ), flowering (Flo), and boll opening (Bol) dates of cotton advanced by 0.026–0.351 days year−1, respectively. The cotton sowing (Sow) and maturity (Mat) dates were delayed by 0.170 and 0.337 days year−1. The average phenological stages from Sow-Eme, Squ-Flo, and Flo-Bol were shortened about 0.19–0.30 days year−1, Eme-Squ, Bol-Mat and the Sow-Mat were delayed by 0.11, 0.77, and 0.082 days year−1, respectively. (2) Pre had a positive effect on most of the lengths phenological stages of cotton except during Bol-Mat. The effect of Sun on the length of the various phenological stages of cotton was the opposite of that of Pre. Tave, Tmin, and Tmax on the general negative effects on the length of the cotton phenological stages. (3) Pre, Sun, and Tave had different influence degrees on the cotton phenological stages because of different regional climate characteristics. (4) The impact of climate change on cotton phenology was weaker than crop management or combined effects of climate change and crop management. Under the combined impacts, and isolated impact of crop management, the lengths of the stages from Sow-Eme and Squ-Flo were shortened while other phenological stages were extended. The isolated impact of climate change shortened the lengths of stages from Sow-Eme, Eme-Squ, and Flo-Bol, extended Squ-Flo, Bol-Mat, and Sow-Mat, implying that the longer-duration cotton varieties in a changing climate might be a better choice for planting. This could be a viable strategy for adapting to climate change. In addition, the study found that Seed cotton yield (Scy) decreased with the delay of Sow, Eme, Squ, Flo and Bol dates, increased with the increase of the lengths of Sow-Eme, Flo-Bol, Bol-Mat and Sow-Mat. And the change trend of Scy affected by climate change was less than that affected by crop management or combined effects.

Pomological and Phenological Identification of Some Walnut (Juglans regia L.) Genotypes and Cultivars

The Persian walnut (Juglans regia L.) is one of the most valuable crops in Iran. The present study was conducted in The rabor agriculture research station (RARS) in Kerman province to investigate 21 important pomological and phenological variables among 37 walnut native genotypes and commercial cultivars in the year 2020. In general, results showed that walnuts from RARS were phenotypically diverse with the significant variation found across most traits examined. The highest and lowest coefficient of variation (CV) was for kernel percentage (CV= 29.48%), and time of male flowering (CV= 14.77%), respectively. Results also showed a strong positive correlation between nut weight and kernel weight (r= 0.727). The date of nut maturity had the lowest correlation with kernel intensity of the ground color (r= -0.476). Principal component analysis of variables revealed that the first eight principal components (PCs) accounted for 79.43% of the total variation. Cluster analysis based on variables produced a dendrogram with five main clusters. The grouping of genotypes was not following their geographical origin. This study revealed the presence of high phenotypic diversity in the walnut genotypes of Rabor Agricultural Research Station (RARS), supporting their breeding value for possible use in the future.

GENETIC BEHAVIOR OF SOME SOYBEAN GENOTYPES UNDER NORMAL AND STRESS IRRIGATION CONDITIONS

The present study was carried out during 2017 and 2018 seasons at the experimental farm of Agricultural Station of Etay El-Barood, EL-Behira overnorate, Egypt. Six soybeans parental genotypes and their 15 F1 were evaluated for seed yield and some of its attributes under normal irrigationconditions (irrigate every 15 days) and stress irrigation conditions (irrigate every 30 days) to select the best genotypes (parents and crosses) had high yield under water stress conditions. Also, to determine the type of gene action involving seed yield and yield components traits and the method of selection for the best crosses in segregation generations under normal and stress irrigations conditions. The results indicated that mean square for genotypes, parents, crosses, parents vs. crosses, genotypes x irrigation, parents x irrigation, F1 x irrigation and parents x F1 x irrigation were significant for all studied traits under both irrigation treatments and the combined analysis except parents vs. crosses for maturity date under normal irrigation. The two parents D89-8940 and Line162 and the two crosses D89-8940 x Line162 and Dr101 x Line162 recorded the highest seed yield/plant (g) in both irrigation treatments and the combined analysis. Our results indicated that mean square associated with general combining ability (GCA) and specific combining ability (SCA) were significant for all studied traits under normal, stress conditions and combined analysis except SCA for main root length cm under normal irrigation condition. The highly GCA/SCA ratio more than the unity was observed for all studied traits which may indicate that the largest part of the total genetic variability associated with these traits a result of additive and additive x additive. The parental genotypes D89-8940, Dr101 andLine162 seemed to be excellent combiners for seed yield/plant and most other traits under normal, stress and the combined analysis. The most desirable Ŝij effects for seed yield/plant were recorded by the cross Dr101 x Line162 flowed by Lkota x Dr101 and Dr101 x Giza21. It could be recommended to use the pedigree method to select the superior crosses for high yield in the segregation generation under both normal and drought conditions.

Evaluation of morphophysiological traits and essential oil production in Iranian genotypes and foreign varieties of Chamomile (Matricaria chamomilla L.) through multivariate analyses

Morphology, physiology and essential oil characteristics of six wild chamomile (Matricaria chamomilla) genotypes of Iran districts were evaluated in this research. These genotypes were collected from different natural habitats. Two European varieties were used as control group. All genotypes were planted according to the randomized controlled block design in Karaj province (Iran). In order to determine the best harvest time in terms of flower yield and essential oil, the traits of flower yield, percentage and yield of essential oil, number of flowers per plant and height were investigated for two harvests. The results showed that genotypes, harvest time and their interaction had significant effect on these parameters. Based on the results, the highest quantitative and qualitative yield of chamomile were attained in the second harvest. Result also showed that genotypes originated from warm part of south western of Iran (Andimeshk, Dashtestan and Ramhormoz) had early maturity, smaller flower, higher flower number, shorter plants, and high essential oil percentage. The foreign varieties had late maturity date, taller plants, long flowering times, but lower flower and essential oil yield. Finally, three local genotypes (Karaj, Shadegan and Taft) had mid maturity date, medium height plants, and medium essential oil yield. It was concluded that genotypes of Andimeshk, Dashtestan and Ramhormoz are capable to breeding improved new cultivars and should be focused on selection higher flower yield and percentage of essential oil, coupled with early flowering date.

Temperature-based prediction of harvest date in winter and spring cereals as a basis for assessing viability for growing cover crops

• The growth and viability of cover crops depends on autumn growth duration. • The viability of growing cover crops was assessed with a phenology model. • The phenology model predicts harvest time of spring and winter cereals. • The harvest time varies more spatially across Denmark than between years. • Simulations show that cover crops can be reliably established in southern Denmark. Cover crops are an important component of sustainable cereal cropping systems by providing nutrient retention and improving soil quality. However, the successful establishment and growth of cover crops depend on a timely harvest of the preceding annual crops. To assess the viability of growing cover crops in Denmark, a phenology model was developed, calibrated, cross-validated and applied to predict the harvest date of spring barley and winter wheat in Denmark using data from field experiments in Denmark during 1991 to 2018. A simple phenology model was used for the period from sowing to maturity, and this was extended to simulate the duration from maturity to harvest. This extended model was used to predict the harvest date in the ongoing season, and it provides the capability for assessing the performance of cover crops as a basis for improved cover crop management. The model uses temperature sums and day length to calculate the developmental rate of spring barley from sowing to harvest and for winter wheat from 1st January to harvest. The standard deviation of the estimated harvest date based on the uncertainty of the model parameters was 10-14 days and 1-4 days for spring barley and winter wheat, respectively. The model was evaluated using historically recorded temperature data (20 years, 1999–2018) to simulate harvest date, which was within the range of observed harvest dates. The interannual range of estimated harvest dates is 7–10 days for spring barley and 5–10 days for winter wheat. This interannual variation of harvest date was lower than the spatial variation across the country. The model can be used for forecasting cereal harvest time and thus readiness for autumn field operations, including the establishment of cover crops. Simulations of growing degree days from date of harvest to 1 November shows that cover crops can be reliably established in southern parts of Denmark to ensure low nitrate leaching. Advancing the harvest date to the date of physiological maturity of the cereals would allow the establishment of efficient cover crops in all years in the entire country.