Classifying cultivars of rice (Oryza sativa L.) based on corrected canopy reflectance spectra data using the orthogonal projections to latent structures (O-PLS) method

To improve the accuracy in discriminating plant species or genotypes in the field with canopy spectral data, a number of statistical methods incorporating measurement techniques have been developed. This study analyzed canopy reflectance spectra collected at the booting stage by using partial least square regression in combination with discriminant analysis (PLS-DA) to establish a classification model for the discrimination of three mega rice cultivars. To improve the model's capability to interpret and sharpen the separation between cultivars, PLS-DA was combined with orthogonal projection to the latent structure (O-PLS) to derive the OPLS-DA models by removing noise and the Y-orthogonal variation. The ground-based high-resolution reflectance spectra (330–1030 nm) were acquired from paddy field experiments during the growing periods, and were recalculated at intervals of 10 nm. With the PLS-DA approach, the total accuracy for discriminating three cultivars in the calibration datasets was 90% and was above 80% for individual cultivars. In the validation datasets, a similar capability for cultivar discrimination was obtained for both pooled and individual cultivars. However, the Y-orthogonal variation might be embedded within the PLS-DA model. Using the OPLS-DA approach, the large variation within rice cultivars (the intra variation) was effectively removed to improve the performance of both group separation and model establishment. The overall accuracy reached 100% in the calibration datasets and had superior discrimination than the PLS-DA model in the validation datasets. Therefore, the OPLS-DA method is recommended for establishing a classification model for the cultivar discrimination of rice in the vegetative phase using remotely sensed canopy reflectance spectra

The Relationship between the Amylographic Characteristics and Eating Quality of Japonica Rice in Taiwan

Eighteen local varieties of japonica rice and two japonica rice varieties introduced from Japan were studied to collect the basic information on the relationship between the amylographic characteristics and eating quality. The materials were planted in the first and second crop seasons of 1998 in central Taiwan. The pasting behaviors including peak viscosity, hot-paste viscosity, cool-paste viscosity, breakdown viscosity, setback viscosity, consistency viscosity, pasting temperature and the time to reach peak viscosity were measured. The eating quality of rice was evaluated by trained panelists in terms of overall palatability score. All amylographic characteristics except for hot-paste viscosity and overall palatability score varied significantly between the first and the second crops and the interactions between crops and varieties were also significant for all characteristics. Teikeng 2, Teikeng 3, Teikeng 4, and Teikeng 9 showed higher overall palatability scores than the other varieties in the first crop, and Koshihikari and Teikeng 6 showed the best overall palatability in the second crop, respectively. The coefficient of variation was higher in the second crop than in the first crop except the time to reach peak viscosity. Setback viscosity showed the highest variation in all amylographic characteristics. The heritability estimate was also higher in the second crop than in the first crop with the exception of consistency viscosity. The highest heritability values were given for consistency and breakdown viscositites in the first and second crops, respectively. However, the lowest heritability value was given for the time to reach peak viscosity in both crop seasons. The close relationship among peak, hot paste, and cool paste viscosities was found for both crops. The highest correlation coefficient was found between peak and breakdown viscosities in both crops. A significant negative correlation between breakdown viscosity and setback viscosity was observed in both crop seasons. Likewise, peak viscosity had a significant correlation with setback viscosity in both crops. In the first crop, the palatability score was negatively correlated with pasting temperature (r=-0.43**) but positively correlated with the time to reach peak viscosity (r=0.36*). There was a positive correlation between palatability score and peak viscosity (r=0.33**) and a negative correlation between palatability score and setback viscosity (r=0.34**) in the second crop

County-scale dataset indicating the effects of disasters on crops in Taiwan from 2003 to 2022

Abstract A lack of crop disaster datasets has limited the exploration of the influence of small-scale disasters on crops. Because disasters are often defined on the basis of human impact, disaster databases may underestimate the effect of disasters on crop production. Additionally, the resolution of such databases is insufficient for evaluating the effects of disasters on small areas. In this study, crop disaster and daily weather datasets covering the period from 2003 to 2022 in Taiwan were developed. Total 9,245 damage records from 233 observations of crop disasters were mined from the Report on Crop Production Loss Caused by Disasters of Taiwan. Daily weather data were collected from weather stations. Entire crop disaster information including multiple disasters, crops, and affected regions was stored in crop disaster dataset. All datasets were cleaned up and refined to enhance their quality, and characteristics such as disaster and crop classification were added to enhance the applicability of these datasets. These datasets can be used to determine the relationship between disaster type and crop production losses

Incorporating the field border effect to reduce the predicted uncertainty of pollen dispersal model in Asia

The presence of the field border (FB), such as roadways or unplanted areas, between two fields is common in Asian farming system. This study evaluated the effect of the FB on the cross-pollination (CP) and predicted the CP rate in the field considering and not considering FB. Three experiments including 0, 6.75, and 7.5 m width of the FB respectively were conducted to investigate the effect of distance and the FB on the CP rate. The dispersal models combined kernel and observation model by calculating the parameter of observation model from the output of kernel. These models were employed to predict the CP rate at different distances. The Bayesian method was used to estimate parameters and provided a good prediction with uncertainty. The highest average CP rates in the field with and without FB were 74.29% and 36.12%, respectively. It was found that two dispersal models with the FB effect displayed a higher ability to predict average CP rates. The correlation coefficients between actual CP rates and CP rates predicted by the dispersal model combined zero-inflated Poisson observation model with compound exponential kernel and modified Cauchy kernel were 0.834 and 0.833, respectively. Furthermore, the predictive uncertainty was reducing using the dispersal models with the FB effect

Morphological and genetic characteristics of F-1 hybrids introgressed from Brassica napus to B. rapa in Taiwan

Background: Unintentional introgression from genetically modified (GM) oilseed rape (Brassica napus) to a relative is inevitable in the open field. A feasible and practical strategy for restricting the spread of GM offspring is to set a reasonable isolated distance between GM B. napus and the relatives. To define the isolated distance, a pollen donor/recipient pair is a prerequisite to conducting the field trial of pollen flow. However, because the cultivation of GM B.napus is prohibited in Taiwan, it is difficult to obtain relevant information. Thus, this study explored the morphological and genetic characteristics of five varieties of B. napus (donor), three varieties of B. rapa (recipient), and the 15 corresponding F1hybrids, aiming to construct phenotypic data and genetic variation data and to select the most appropriate pollen donor/recipient for future field trials of pollen flow. Results: The genome size of all F1 hybrids estimated using flow cytometry showed intermediate DNA content between B. napus and B. rapa varieties. Most of the F1 hybrids had intermediate plant height and blooming period, and the rosette leaves type and colors resembled those of B. napus varieties. The results of sequence-related amplified polymorphism (SRAP) showed an average of 9.52 bands per primer combination and 67.87 polymorphic bands among the F1 hybrid population. Similarity and cluster analyses revealed higher similarity between F1 hybrids and B. napus varieties than between F1hybrids and B. rapa varieties. Furthermore, we identified a specific 1100-bp band(LOC106302894) in F1hybrids and B. napus varieties but not in B. rapa varieties. Conclusions: The rosette leaves and the DNA marker LOC106302894 observed in F1 hybrids are consistent phenotypic and genetic characteristics that can be used to identify the presence of unintentional hybridization from B.napus to B. rapa in Taiwan. Due to the prohibition of GM crop cultivation, the hybridization system of non-GM Brassica species in this study can be utilized as a mimic scheme to conduct pollen flow trials, thus facilitating the determination of the proper isolated distance

Using Sigmoid Growth Curves to Establish Growth Models of Tomato and Eggplant Stems Suitable for Grafting in Subtropical Countries

In subtropical regions, tomato (Solanum lycopersicum) is mainly produced in autumn and winter. To enhance the off-season production of tomato, summer cultivation has become a prime objective. Grafting tomato scions onto eggplant (Solanum melongena) rootstocks is a key method to overcome the difficulties of tomato cultivation in summer. In this study, we collected seedling growth data over six growing seasons in Taiwan and established growth models by employing three commonly used sigmoid growth curves, namely the Gompertz, Richards, and Logistic curves. Cumulative temperature was introduced as an independent variable and its relationship with plant stem diameter determined. The R2 values of the growth models were 0.74–0.85 and 0.72–0.80 in calibration and validation, respectively. Performance did not differ markedly among models in the same growing season, but notable differences were observed among models for different growing seasons. In addition, the estimates of several model parameters differed significantly among the seasons; hence, separate models should be established for different seasons. The results of this study can be used in prediction of tomato and eggplant seedling growth and arrangement of the grafting schedule to improve the efficiency of seedling production in subtropical countries

Using Sigmoid Growth Curves to Establish Growth Models of Tomato and Eggplant Stems Suitable for Grafting in Subtropical Countries

In subtropical regions, tomato (Solanum lycopersicum) is mainly produced in autumn and winter. To enhance the off-season production of tomato, summer cultivation has become a prime objective. Grafting tomato scions onto eggplant (Solanum melongena) rootstocks is a key method to overcome the difficulties of tomato cultivation in summer. In this study, we collected seedling growth data over six growing seasons in Taiwan and established growth models by employing three commonly used sigmoid growth curves, namely the Gompertz, Richards, and Logistic curves. Cumulative temperature was introduced as an independent variable and its relationship with plant stem diameter determined. The R2 values of the growth models were 0.74–0.85 and 0.72–0.80 in calibration and validation, respectively. Performance did not differ markedly among models in the same growing season, but notable differences were observed among models for different growing seasons. In addition, the estimates of several model parameters differed significantly among the seasons; hence, separate models should be established for different seasons. The results of this study can be used in prediction of tomato and eggplant seedling growth and arrangement of the grafting schedule to improve the efficiency of seedling production in subtropical countries

Bootstrap simulations for evaluating the model estimation of the extent of cross-pollination in maize at the field-scale level.

With the recent advent of genetic engineering, numerous genetically modified (GM) crops have been developed, and field planting has been initiated. In open-environment cultivation, the cross-pollination (CP) of GM crops with wild relatives, conventional crops, and organic crops can occur. This exchange of genetic material results in the gene flow phenomenon. Consequently, studies of gene flow among GM crops have primarily focused on the extent of CP between the pollen source plot and the adjacent recipient field. In the present study, Black Pearl Waxy Corn (a variety of purple glutinous maize) was used to simulate a GM-maize pollen source. The pollen recipient was Tainan No. 23 Corn (a variety of white glutinous maize). The CP rate (%) was calculated according to the xenia effect on kernel color. We assessed the suitability of common empirical models of pollen-mediated gene flow (PMGF) for GM maize, and the field border (FB) effect of the model was considered for small-scale farming systems in Asia. Field-scale data were used to construct an optimal model for maize PMGF in the maize-producing areas of Chiayi County, southern Taiwan (R.O.C). Moreover, each model was verified through simulation and by using the 95% percentile bootstrap confidence interval length. According to the results, a model incorporating both the distance from the source and the FB can have optimal fitting and predictive abilities