Maturity Date Research Articles

Evaluation of Convolutional Neural Networks’ Hyperparameters with Transfer Learning to Determine Sorting of Ripe Medjool Dates

Convolutional neural networks (CNNs) have proven their efficiency in various applications in agriculture. In crops such as date, they have been mainly used in the identification and sorting of ripe fruits. The aim of this study was the performance evaluation of eight different CNNs, considering transfer learning for their training, as well as five hyperparameters. The CNN architectures evaluated were VGG-16, VGG-19, ResNet-50, ResNet-101, ResNet-152, AlexNet, Inception V3, and CNN from scratch. Likewise, the hyperparameters analyzed were the number of layers, the number of epochs, the batch size, optimizer, and learning rate. The accuracy and processing time were considered to determine the performance of CNN architectures, in the classification of mature dates’ cultivar Medjool. The model obtained from VGG-19 architecture with a batch of 128 and Adam optimizer with a learning rate of 0.01 presented the best performance with an accuracy of 99.32%. We concluded that the VGG-19 model can be used to build computer vision systems that help producers improve their sorting process to detect the Tamar stage of a Medjool date.

Screening of a molecular marker for association to maturity date in peach fruit

Screening of a molecular marker for association to maturity date in peach fruit

Valuasi One Period Coupon Bond dengan Aset Mengikuti Model Geometric Brownian Motion with Jump Diffusion

<p>One period coupon bond gives coupon once a bond life together with the principal debt. If the firm’s asset value on maturity date is insufficient to meet the debtholder’s claim, then the firm is stated as default. The well-known model for predicting default probability is KMV-Merton model. Under this model, it is assumed that the return on the firm’s assets is distributed normally and their behaviour can be described with the Geometric Brownian Motion (GBM) formula. In practice, most of the financial data tend to have heavy-tailed distribution. It indicates that the data contain some extreme values. GBM with Jump is a popular model to capture the extreme values. In this paper, we evaluate a corporate bond which has some extreme condition in their asset value and predicts the default probability in the maturity date. Empirical studies were carried out on bond that is issued by CIMB Niaga Bank that has a payment due in November 2020. The result shows that modelling the asset value is more appropriate by using GBM with Jump rather than GBM modelling. Estimation to CIMB Niaga Bank equity in November 2020 is IDR 246,533,573,844,229.00. The liability of this company is IDR 4,205,751,155,771.00. The prediction of CIMB Niaga Bank default probability is 1.065812 ´ 10<sup>-8</sup> at the bond maturity. It indicates that the company is considered capable of fulfilling the obligations at the maturity date.</p><p><strong>Keywords: </strong>jump diffusion, extreme value, probability default, equity, liability</p>

Potential agro-thermal resources dynamic for double-season rice cultivation across China under greenhouse gas emission scenarios

Maintaining the current levels of rice production in the face of future climate changes is an enormous challenge for agriculture. The use of high-resolution projections derived from statistical downscaled global climate models and dynamic downscaled regional climate models can assist in maximizing yield for double-season rice. The thermal indices of secure sowing date (SSd), secure maturation date (SMd), potential growing season (PGS), and growing accumulated temperature ≥ 10 °C (GAT10) were explored in future sub-periods under two greenhouse gas emission scenarios (RCP4.5 and RCP8.5). The trends predicted were advancements in SSd and delays in SMd across major areas of China. A comparison of RCP4.5 and RCP8.5 scenarios indicated that SSd advanced by 1–39 and 1–49 days in 2081–2095 relative to the baseline period of 2001–2015 while SMd was postponed by 11–60 and 11–70 days, respectively. Under RCP4.5, PGS was prolonged by 1–50, 1–60, 21–90, and 31–90 days in 2021–2035, 2041–2055, 2061–2075, and 2081–2095 relative to baseline, respectively. Within these same periods using RCP8.5, PGS advanced 1–50, 31–90, 41–90, and 51–90 days, respectively. A comparison of the relative contributions of SSd and SMd to PGS indicated that higher levels of SMd contributed prominently in the PGS increase. In addition, as the climate continued to warm, GAT10 levels would likely continue in an upward trend and were predicted for 2081–2095 to reach 500–2500 °C·day under RCP4.5 and 1500–3000 °C·day under RCP8.5. Regionally, earlier SSd, later SMd, longer PGS, and larger GAT10 values were projected for southern regions in Guangdong, Guangxi, and Hainan. This type of information is also a potential resource available to farmers to make informed decisions on timely cultivation adjustments and variety selections for specific climatological areas.

Lodging tolerance of rice is improved without decreasing productivity by mixing lines with different maturity dates

We hypothesised that mixing of rice lines with different maturity dates can improve the productivity per unit area while improving lodging resistance on account of the heterogeneous canopy. To test this hypothesis, we grew two lines, wild-type (WT) and early-maturing (EML), of each of two cultivars (Koshihikari and Hitomebore) in monoculture plantings and within-cultivar mixed plantings, with WT and EML plants alternating every one or two rows, over 2 years in northern Japan. The mixtures formed a canopy with different heading dates (5–7 days earlier than WT in Hitomebore and 14–19 days earlier in Koshihikari). For Koshihikari, the mixture increased grain yield per plant in the WT by 18–33%, but decreased it in the EML by 19–22%; however, for Hitomebore, there was no significant difference. Consequently, grain yield per unit area did not change relative to the mean of monocultures of WT and EML in either cultivar. Lodging tolerance improved significantly in the mixtures, especially for Koshihikari. Thus, mixing rice lines with different maturity dates improved lodging tolerance without decreasing productivity.

Optimization of temporal UAS‐based imagery analysis to estimate plant maturity date for soybean breeding

AbstractEstimating the date of maturity of soybean breeding field plots is necessary for breeding line characterization and for informing yield comparisons among varieties. The main drawback of visually dating soybean maturity is the sheer scale of note recording entailed and the frequency at which these notes need to be taken. The overall aim of this study was to build upon prior work in using low‐cost UAS‐based RGB cameras to estimate soybean maturity date by examining the effect of vegetation index, summary statistic of the pixel values from each region of interest (plot), statistical model, and flight frequency. Maturity dates collected from five environments with 53 experimental trials (4,415 plots) were both visually dated and imaged using a RGB camera carried by a UAS. Using the mean greenness leaf index on each plot combined with LOESS regression, we achieved high correlations between ground and UAS‐based estimates (r = 0.84–0.97). Precision, quantified by broad‐sense heritability estimates, was greater for UAS‐based dates in 29 of 53 field trials, and nearly equivalent in 11 more field trials. We found that 54% of the significant deviations between ground and UAS‐based estimates were caused by inaccurate UAS‐based estimates, while errors in the ground‐based estimates accounted for 46% of the deviations. Reasons for these inaccurate estimates were attributed to lodging, presence of weeds, low germination, and within‐line genetic heterogeneity in the plots. A detailed description of the analysis pipeline, a user‐friendly R script, and all of the images and ground data have been made publicly available to help other researchers and breeders test and adopt these methods.

Performances of Improved Lablab Varieties for Their Agronomic Characteristics and Chemical Compositions in Adola Sub-site of Bore Agricultural Research Center

A study was conducted with the objective to identify adaptable and chemical composition of Lablab varieties. Three Lablab Beresa-17, Gabis-55 and Local variety +were tested in randomized complete block design (RCBD) with three replications. The result revealed that date of maturity was significantly (p 0.05) differ among the tested varieties. The analyzed chemical compositions indicated, Beresa-17 variety had the highest in Organic matter (OM), crude protein (CP), neutral detergent fiber (NDF) and dry matter (DM) and less in acid detergent fiber (ADF), acid detergent lignin (ADL), and total ash content (TASH) content while, Gabis-55 was highest in acid detergent lignin (ADL) and acid detergent fiber (ADF) and less in crude protein (CP) content. The local variety had the highest in neutral detergent fiber (NDF) and total ash content (TASH) and less in dry matter (DM) content than the rest varieties. The result of this study implied that Gabis-55 variety was adapted and being productive regarding the plant height, biomass yield and seed yield of each variety, which is hopeful to fill the gap of low quantity feed. In addition to the nutritional values were promising particularly the crude protein (CP), Dry matter (DM) and Organic Matter (OM) content in Beresa-17 variety. Based on its adaptability, high biomass yield, high seed yield, good CP, DM and OM of Gais -55 is recommended for further promotion in the midland of East Guji zone.

Correlation and Path Coefficient Studies on Advanced Bread Wheat Lines in Ethiopia

Grain yield is a complex quantitative trait which is influenced by a number of yield contributing traits. To improve grain yield in wheat, selection of genotypes should not only be based on grain yield alone, and the other grain yield components should also be considered. Twenty-three advanced bread wheat genotypes from the national wheat research breeding program; two released bread wheat varieties in Ethiopia; a total of twenty-five genotypes used in this study. The experiment was conducted in square lattice design with three replication over five locations for two consecutive years, in 2018 and 2019 main cropping seasons. The total experimental unit was 2.5m x 1.2m = 3m². Overall results from correlations showed a higher genotypic correlation than the corresponding phenotypic correlation for most of the traits. The genotypic correlation between Grain yield and Plant height (r_g=0.51**); between grain yield and thousand kernel weight (rg=0.73**); and between grain yield and hectoliter weight (r_g= 0.52**) are highly significant at (P<0.01) (table 3). The highest phenotypic correlation found between thousand kernel weight and grain yield (r_p=0.68**) followed by the phenotypic correlation between hectoliter weight and grain yield (r_p=0.57**) (Table 5). The date of maturity, Plant height, Thousand Kernel Weight, and HectoLiter Weight had a positive direct effect on Grain yield (table 4). In conclusion, to generate a new technology, a variety with improved grain yield, a breeder needs to apply indirect selection for yield components from an early stage, nurseries to sets of advanced yield trials in the breeding program.

EFFECT OF SOWING DATE AND INTERCROPPING SYSTEM OF SUNFLOWER WITH SUGAR BEET ON THE PRODUCTIVITY OF BOTH CROPS.

A field study was conducted during 2018/2019 and 2019/2020 seasonsinItay EL-Baroud Agric. Res. Station,Beheira Governorate, Egypt, to study the effect of three sowing dates of sunflower (simultaneously with sugar beet (T1), twenty one days after sowing sugar beet (T2) andthirty five days after sowing sugar beet(T3)) and three intercropping systems(25% (S1),33.3% (S2)and 50% (S3)of sunflower plant density + 100% sugar beet)on yield and yield components of both crops.A split plot design with four replications was used. Results showed that all studied characters of sugar beet were significantlyaffected by sowing dates and intercropping systems of sunflower. Intercropping system (S1)significantly increasedall characters of sugar beet at T3over the other treatments. Early sowing date(T1)significantly accelerated days to 50% of flowering and maturity date and recorded the highest values for each of growing degree days (GDD) andseed yield and its componentsof sunflower. Significant differences were recorded for sunflower studied traits as affected by the intercropping systems. The highest seed and oil yields/fad., were achieved with sole sunflower followed byS3system at T1 compared with the other treatments. The highest land equivalent ratio (LER)value 1.46 was recorded at T2 with S3, followed by 1.44 with T2 x S1, as average of both seasons.While T2 x S1 had the highest relative crowding coefficient (RCC) and net return. It can be concluded that T2 x S1 had the highest sugar yield valued 4.74 ton/fad.,increased net return by 28.30% and produced 26.10 ton sugar beet plus 444.63kg seed of sunflower compared to sole sugar beet which had 26.91 ton sugar beet.

Determination of Upland Rice Cultivar Coefficient Specific Parameters for DSSAT (Version 4.7)-CERES-Rice Crop Simulation Model and Evaluation of the Crop Model under Different Temperature Treatments conditions

To develop basis for strategic or arranged decision making towards crop yield improvement in Thailand, a new method in which crop models could be used is essential. Therefore, the objective of this study was to measure cultivar specific parameters by using DSSAT (v4.7) Cropping Simulation Model (CSM) with five upland rice genotypes namely Dawk Pa-yawm, Mai Tahk, Bow Leb Nahng, Dawk Kha 50 and Dawk Kahm. Experiment was laid out in a Completely Randomized Design (CRD) with split plot design. Results showed that five upland rice genotypes had significantly affected each other by different temperature treatments (28°C, 30°C, 32°C) with grain yield, tops weight, harvest index, flowering, and maturity date. At the same time, all the phenological traits had highly significant variation with the genotypes. The cultivar specific parameters obtained by using a temperature tolerant cultivar (Basmati 385) with five upland genotypes involved in the DSSAT4.7-CSM. Model evaluation results indicated that utilizing the estimated cultivar coefficient parameters, model simulated well with varying temperature treatments as indicated by the agreement index (d-statistic) closer to unity. Hence, it was estimated that model calibration and evaluation was realistic in the limits of test cropping seasons and that CSM fitted with cultivar specific parameters can be used in simulation studies for investigation, farm managing or decision making. This electronic document is a “live” template. The various components of your paper [title, text, heads, etc.] are already defined on the style sheet, as illustrated by the portions given in this document.

The Effect of Nano Fertilizer on Teff Yield and Yield Components in Ethiopia

Nano technology increases the nutrient use efficiency. The experiment to test nano fertilizers on tef was conducted at the teff crop producing areas of Adet, Meray, and Meshenti areas. A total of sixteen fertilizer combinations of urea, DAP (Di Amonium phosphate) and Nano fertilizers including without fertilizer and without nano checks were tested on 2m X 1.5m plot size. The materials were planted in RCBD (Randomized Complete Block Design) with three replications. Spacing between replications and plots were 1 meter and 0.5 meter respectively. The seed and fertilizer rates were used as per recommendation rate per hectare bases. The nano fertilizer was tested as early as seed dressing and field spray during tillering stage. The performances of nano fertilizer over all locations have shown consistence results at all locations. Analysis of variance showed that there is a significant difference between the treatments for all parameters including grain yield. The highest grain yield (38 Q/ha) was recorded at the treatment combination of 2gm/ha nano seed dressing, 39g DAP and 10.8g urea. And the least grain yield (2.5 Q/ha) was recorded at treatment combination of no nano and no fertilizer treatments. Here all nano treatment combinations without DAP and urea fertilizers gave grain yield less than 7Q/ha. Which implies that Nano fertilizers cannot act solely without DAP and Urea. The least maturity date (119 dates) and the highest plant height (132.4 cm) was also recorded at a treatment combination of 2gm/ha nano seed dressing, 39g DAP and 10.8g urea. This implies that the crop at these treatments was vigor and was able to mature early.

Evaluation of Newly Released Rice Varieties (&amp;lt;i&amp;gt;Oryza Sativa L.&amp;lt;/i&amp;gt;) Under Smallholder Farmers’ Condition Through On-Farm Demonstration in Western Ethiopia

Rice is one of the main important food crops in the world. It is the promising and strategic commodity set under Ethiopian food security strategy program. Although consumers’ preference of rice is increasing rapidly, the current production status is unable to meet the existing consumption needs. The evaluation was conducted at Jawe and Pawe districts of Western Ethiopia focusing on the newly released rice varieties under smallholder farmers’ condition. A total of 31 hosted farmers were selected purposively based on their experience and willingness to implement the on-farm demonstration under five rice potential kebeles. Four improved varieties of rice (Pawe-1, Nerica-3, Hidasie and Nerica-12) were the materials used for the demonstration under farmers’ management practices. The evaluation was done on farmers’ field with plot size of 25*25m (625 m²) for each variety. Both qualitative and quantitative data were collected from 51 farmers (20 control group). The collected data were analysed through descriptive and inferential statistics. Farmers’ preference ranking also done to choose the best performed variety based on their own selection criteria. The results of the evaluation revealed that all the demonstrated varieties have a significant yield advantage over the control variety and higher than the national average productivity. The highest mean grain yield (3763..08 kg ha^-1) was recorded from Pawe-1 variety with yield advantage of 1027.38 kg and the lowest yield (2735.70 kg ha^-1) recorded from the local control variety. Marketability, grain yield, seed color, seed size, tillering capacity and maturity date were the major preference traits for farmers. Pawe-1 was the best preferred and promising variety based on farmers’ preference criteria followed by Nerica-12 variety. The highest technology gap (1136.85 kg) observed from Nerica-3 variety. Results of the overall evaluation indicated that all the evaluated improved rice varieties performed very well in all testing sites. Therefore, the newly released rice varieties with full recommended packages have to be promoted accordingly for large-scale production to enhance its contribution in the national food security strategy program.

The COVID-19 Pandemic and the Degree of Persistence of US Stock Prices and Bond Yields

This paper analyses the possible effects of the Covid-19 pandemic on the degree of persistence of US monthly stock prices and bond yields using fractional integration techniques. The model is estimated first over the period January 1966-December 2020 and then a recursive approach is taken to examine whether or not persistence has changed during the following pandemic period. We find that the unit root hypothesis cannot be rejected for stock prices while for bond yields the results differ depending on the maturity date and the specification of the error term. In general, bond yields appear to be more persistent, although there is evidence of mean reversion in case of 1-year yields under the assumption of autocorrelated errors. The recursive analysis shows no impact of the Covid-19 pandemic on the persistence of stock prices, whilst there is an increase in the case of both 10- and 1- year bond yields but not of their spread.

Agro-morphological Characterization of Eight (08) Cowpea Accessions [(&lt;i&gt;Vigna unguiculata&lt;/i&gt; (L.) Walp.)] from Benin and Ghana Introduced in Center-Benin

The present study allowed to characterize at agro-morphological level, eight (08) traditional cowpea accessions from Benin and Ghana in order to identify the best performing ones. The test was installed in a Randomized Complete Block (RCB) design with four (04) repetitions in a station in Savè in Center-Benin. The parameters studied are the date of flowering and maturation, the numbers of stems and leaflets per plant, the height of plants, the port of the stem, the lengths of pods and petiole, the weights of pods, tops, seeds and of 100 seeds, the seed yield, the colors of flowers, pods and seeds, the shapes of leaflets and of seeds, the size and the appearance of seeds. Xlsat version 2018.6 software was used for multi-component analysis to categorize accessions by their significant variables. SAS 9.2 software was used for the analysis of variance and the comparison of the means of variables. The number of branches, the length of the petiole, the height of the plants, the number of leaves, the length of the pods, the weights of the pods and of the tops had a positive influence on the cowpea seeds yield. The accessions were classified into three groups. The first group is made up of three (03) high-performance accessions, Nketewade, Mung bean lens and Songotra, with a short cycle of 61 to 62 days and a high yield of between 1050 kg/ha and 1300 kg/ha. The second group is that of the Djetoko and black eye bean accessions of long-cycle from 80 to 88 days, with a yield of between 620 kg/ha and 800 kg/ha. The third group is made up of false Cassoulet, Ennepa and Nsroma accessions with a short cycle of 62 to 65 days and a low yield of between 175 kg/ha and 230 kg/ha. Multilocal tests and genetic molecular characterization must be considered for a good valuation of these cowpea accessions.

Stoptions: Representations and Applications

We introduce a new derivative security called a stoption. After paying an upfront premium, the owner of a stoption accrues realized price changes in some underlying security until the exposure is stopped by the owner. Upon stopping, the reward is the sum of all of the previous price changes plus a deterministic amount which can vary with the stopping time. Stoptions are finite-lived and hence must be stopped at or before a fixed maturity date. We propose a particular discrete-time probabilistic model for the underlying's price changes and then determine the optimal stopping strategy and stoption premium for that model in closed-form. We also present an application to DVA (debit valuation adjustment) under full collateralization.

Performance and Adaptability Evaluation of Improved Onion Varieties (&amp;lt;i&amp;gt;Allium cepa&amp;lt;/i&amp;gt; L.) for Bulb Yield and Some Agronomic Traits

Onion is one of the most important vegetable crops in the world including Ethiopia. The field experiment was conducted in Arsi zone at Kulumsa Agriculture Research Center and Ziway Dugda districts under irrigation condition. A total of five improved onion varieties were evaluated in Randomized Complete Block Design with three replications with the objectives of studying the performance and adaptability of improved onion varieties for bulb yield and yield related traits in 2017 during off season. The combined Analysis of variance (variety by location) revealed that significant difference between improved onion varieties for maturity date, marketable and unmarketable bulb yield tons per hectare, bulb length in centimeter, and bulb weight in gram was observed. But non-significant difference for plant height in centimeter, total bulb yield tons per hectare and average bulb diameter in centimeter were observed between improved onion varieties. Except variety Adama Red all the tested improved onion varieties (Melkam, Nafis, Nasik Red and Bombay Red) was well performed and adapted. These varieties were gave more than 40 marketable bulb yield t ha^-1. So those improved onion varieties were recommended for the study area and areas of similar agro- ecological zones under off season growing condition.

Future climate change impacts on grain yield and groundwater use under different cropping systems in the North China Plain

Crop production in the North China Plain (NCP) is heavily influenced by the unfolding climate change and water shortage. Groundwater overdraft for irrigation in this region has caused serious ecological and environmental problems. Cropping systems adjustment offers an effective approach for the sustainable use of groundwater. However, the assessment of the impacts of future climate change on crop production and water consumption under different cropping systems with/without straw mulching has not been reported in the NCP. In this study, we applied the well validated APSIM model to explore the implementation of five cropping systems (i.e., two maturities per year, 1Y2MS0; three maturities per two year without (with) straw mulching during the fallow period, 2Y3MS0 (2Y3MS1); and one maturity per year without (with) straw mulching during the fallow period, 1Y1MS0 (1Y1MS1)). Statistical downscaled daily climate data based on 33 global climate models (GCMs) were used to drive APSIM to simulate crop phenology, yield and water use under future climate change. We found that cropping system adjustment significantly reduced the amount of water required for irrigation, thereby decreasing groundwater overdraft to a certain extent. Straw mulching could have mitigating effect on groundwater overdraft. Multi-GCMs ensemble means show an increase in temperature, precipitation and solar radiation in the future. Under future climate change scenarios, the phenological date (e.g. flower and maturity dates) of maize and wheat were advanced due to climate warming. Our simulated results indicated that future climate change would have negative impact on maize yield across all cropping systems but have positive impact on wheat yield under most climate change scenarios. Both irrigation and groundwater overdraft reduced in the future due to decreased evapotranspiration and increased precipitation. We concluded that 2Y3MS1 would be the optimum cropping system to balance crop yield and groundwater overdraft. This knowledge can inform the development of improved regional impact assessments of the sustainability of multi-crop rotation systems.

Impacts of Climate and Phenology on the Yields of Early Mature Rice in China

Phenological variables are closely correlated with rice (Oryza sativa L.) yields as they play important roles in influencing and controlling the carbon allocations between plant organs, but their impacts on rice yields and their relative importance compared with climatic variables are not yet well investigated. In this study, the impacts and the relative importance of climatic and phenological variables on the yields of early mature rice were assessed using the trial data from 75 agricultural stations across China, spanning from 1981–2010. We found that both daily maximum (Tmax) and daily minimum (Tmin) temperatures during the growing season (from transplanting to maturity) increased significantly, while sunshine duration (SD) and precipitation (Prep) did not change significantly. The average transplanting date was advanced by 3.18 days/decade, and the heading (maturity) dates were delayed by 2.47 (4.55) days/decade, with yields significantly increased by 9.65 g/m3 per decade across all sites. Partial correlation coefficients between most phenological variables and rice yields were negative, whereas most of the climatic variables were positively correlated with rice yields. The average of partial correlation coefficients between transplanting, heading, and maturity dates and rice yields were −0.10, −0.15, and −0.01, respectively, and the average of coefficients between Tmax, Tmin, SD, and Prep and rice yields were 0.08, 0.02, 0.12, and −0.05, respectively. Interestingly enough, phenological variables were the dominating influencing factors on rice yields at 63% of the sites, suggesting that the relative importance of phenology to rice yields may be even higher than that of climate. The climatic variables were closely correlated with rice yields as they are fundamental growth materials for crops, and phenological variables strongly influenced the growth and development of rice. Our results highlight that phenology should be precisely evaluated in crop models to improve the accuracy of simulating their response to climate change. Furthermore, due to limited understanding of phenological processes, manipulative experiments are urgently needed to comprehensively improve our understanding of rice phenology and rice yield response to ongoing climate change.

Analysis of the effects of climate, host resistance, maturity and sowing date on wheat stem rust epidemics

Under appropriate environmental conditions, stem rust (caused by Puccinia graminis Pers.:Pers. f. sp. tritici) is a destructive disease of wheat crops worldwide. Although fungicide application and host genotype resistance are the most commonly used methods to control wheat stem rust, efficient agronomic methods are needed to lower disease management expenses and improve sustainability of wheat production. However, an understanding of highly effective agronomic practices to control stem rust is still lacking. From 2013 to 2017, 282 wheat-stem-rust progress curves were studied using three agronomic, three climatic, and two disease variables at plot scale in Kermanshah province, Iran. Cultivar, sowing date, and disease-assessment time significantly affected stem rust severity. From principal component analysis (PCA), three principal components explained 79% of data variance. According to PCA and multiple regression model, AUDPC corresponded with disease-onset and maturity date, mean minimum temperature and number of rainy days over designated spring months, number of days with minimum temperature within 5–20 °C and maximum relative humidity above 60%, resistance index, and sowing date. These new findings suggested improvement of current predicting models by involving dates of maturation and sowing, and wheat resistance besides rainfall-temperature-wetness variables for more effective, economic and sustainable management of stem rust epidemics.

Does the Nature of Index and Liquidity Influence the Mispricing in Future Contracts in India?

In this study, we investigate the variations in the mispricing of futures in Nifty (benchmark index), Bank Nifty and Nifty IT. Using a regression model on 1230 observations for the period of 1 January 2014 to 31 December 2018, we find no significant mispricing exists in the last week to the expiry of the contract in all three indices. This finding supports the existing literature that as the contract moves towards the maturity date, its value converges the market value. However, the main highlight of the paper is to reveal the difference in the life of mispricing in different indices. This difference in mispricing can be allocated to the liquidity in that indices. We report that being the most liquid, Bank Nifty is having mispricing only in 1 week (first week) of the contract, after that no significant mispricing exists in mispricing, Nifty shows significant mispricing for the first two weeks and Nifty IT shows mispricing for all weeks except last week. This is the pioneering work which considers the sectoral differences while evaluating futures mispricing. The findings of this study will provide a useful insight to the regulator and investors.