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

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.

CART model to classify the drought status of diverse tomato genotypes by VPD, air temperature, and leaf-air temperature difference.

Regular water management is crucial for the cultivation of tomato (Solanum lycopersicum L.). Inadequate irrigation leads to water stress and a reduction in tomato yield and quality. Therefore, it is important to develop an efficient classification method of the drought status of tomato for the timely application of irrigation. In this study, a simple classification and regression tree (CART) model that includes air temperature, vapor pressure deficit, and leaf-air temperature difference was established to classify the drought status of three tomato genotypes (i.e., cherry type 'Tainan ASVEG No. 19', large fruits breeding line '108290', and wild accession 'LA2093'). The results indicate that the proposed CART model exhibited a higher predictive sensitivity, specificity, geometric mean, and accuracy performance compared to the logistic model. In addition, the CART model was applicable not only to three tomato genotypes but across vegetative and reproductive stages. Furthermore, while the drought status was divided into low, medium, and high, the CART model provided a higher predictive performance than that of the logistic model. The results suggest that the drought status of tomato can be accurately classified by the proposed CART model. These results will provide a useful tool of the regular water management for tomato cultivation.

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.

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.

Effectiveness of different sampling schemes in predicting adventitious genetically modified maize content in a smallholder farming system.

When genetically modified (GM) maize is planted in an open field, it may cross-pollinate with the nearby non-GM maize under certain airflow conditions. Suitable sampling methods are crucial for tracing adventitious GM content. By using field data and bootstrap simulation, we evaluated the performance of common sampling schemes to determine the adventitious GM content in small maize fields in Taiwan. A pollen dispersal model that considered the effect of field borders, which are common in Asian agricultural landscapes, was used to predict the cross-pollination (CP) rate. For the 2009-1 field data, the six-transect (Tsix), JM method for low expected flow (JM[L]), JM method for high expected flow (JM[H]), and V-shaped transect (TV) methods performed comparably to simple random sampling (SRS). Tsix, TV, JM(L), and JM(H) required only 13% or less of the sample size required by SRS. After the simulation and verification of the 2009-2 and 2010-1 field data, we concluded that Tsix, TV, JM(L), and systematic random sampling methods performed equally as well as SRS in CP rate predictions. Our findings can serve as a reference for monitoring the pollen dispersal tendencies of maize in countries with smallholder farming systems.

Using a zero-inflated model to assess gene flow risk and coexistence of Brassica napus L. and Brassica rapa L. on a field scale in Taiwan.

BACKGROUND: The cropping area of genetically modified (GM) crops has constantly increased since 1996. However, currently, cultivating GM crops is associated with many concerns. Transgenes are transferred to non-GM crops through pollen-mediated gene flow, which causes environmental problems such as superweeds and introgressive hybridization. Rapeseed (Brassica napus L.), which has many GM varieties, is one of the most crucial oil crops in the world. Hybridization between Brassica species occurs spontaneously. B. rapa grows in fields as a weed and is cultivated as a crop for various purposes. Both B. rapa weeds and crops participate in gene flow among rapeseed. Therefore, gene flow risk and the coexistence of these two species should be studied. RESULTS: In this study, field experiments were conducted at two sites for 4 years to evaluate gene flow risk. In addition, zero-inflated models were used to address the problem of excess zero values and data overdispersion. The difference in the number of cross-pollination (CP) events was nonsignificant between upwind and downwind plots. The CP rate decreased as the distance increased. The average CP rates at distances of 0.35 and 12.95 m were 2.78% and 0.028%, respectively. In our results, zero-inflated negative binomial models were comprehensively superior to zero-inflated Poisson models. The models predicted isolation distances of approximately 1.36 and 0.43 m for the 0.9% and 3% threshold labeling levels, respectively. CONCLUSIONS: Cultivating GM crops is prohibited in Taiwan; however, the study results can provide a reference for the assessment of gene flow risk and the coexistence of these two species in Asian countries establishing policies for GM crops.

Morphological and genetic characteristics of F1 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 F1 hybrids, 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 F1 hybrids and B. rapa varieties. Furthermore, we identified a specific 1100-bp band (LOC106302894) in F1 hybrids 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.

The effect of flowering time and distance between pollen source and recipient on maize.

Field experiments were conducted in Central Taiwan for 2 crop seasons to examine the effect of non-coincidence flowering on the cross-pollination (CP) rate of maize at various distances. Four local maize hybrid varieties with different flowering dates and one local maize variety were sown as the pollen sources and recipient, respectively. All varieties were sown on the same day to simulate the real situation of coexistence in which adjacent fields are sown with different genetically modified (GM) and non-GM varieties of maize. The CP rate was <0.2% at a distance of 3 m for the first crop season when the flowering time for the recipient was 5 d later than that of the pollen source variety. The CP rate was <0.02% at all distances for the second season when the flowering time for the recipient was 7 d later than that of the pollen source variety. The CP rate was <1% at a distance of 0.75 m when the flowering time was 3 d later. However, varieties with closer synchrony may result in a CP rate of >1% at a distance of 1.5 m and <1% at 2.25 m. Temporal separation and isolation distances can work together in Taiwan with fragmented landscapes to minimize the adventitious presence of one crop with another.

Development and psychometric testing of the Cancer Knowledge Scale for Elders.

AIM: To develop the Cancer Knowledge Scale for Elders and test its validity and reliability. BACKGROUND: The number of elders suffering from cancer is increasing. To facilitate cancer prevention behaviours among elders, they shall be educated about cancer-related knowledge. Prior to designing a programme that would respond to the special needs of elders, understanding the cancer-related knowledge within this population was necessary. However, extensive review of the literature revealed a lack of appropriate instruments for measuring cancer-related knowledge. A valid and reliable cancer knowledge scale for elders is necessary. DESIGN: A non-experimental methodological design was used to test the psychometric properties of the Cancer Knowledge Scale for Elders. METHODS: Item analysis was first performed to screen out items that had low corrected item-total correlation coefficients. Construct validity was examined with a principle component method of exploratory factor analysis. Cancer-related health behaviour was used as the criterion variable to evaluate criterion-related validity. Internal consistency reliability was assessed by the KR-20. Stability was determined by two-week test-retest reliability. RESULTS: The factor analysis yielded a four-factor solution accounting for 49.5% of the variance. For criterion-related validity, cancer knowledge was positively correlated with cancer-related health behaviour (r = 0.78, p < 0.001). The KR-20 coefficients of each factor were 0.85, 0.76, 0.79 and 0.67 and 0.87 for the total scale. Test-retest reliability over a two-week period was 0.83 (p < 0.001). CONCLUSION: This study provides evidence for content validity, construct validity, criterion-related validity, internal consistency and stability of the Cancer Knowledge Scale for Elders. The results show that this scale is an easy-to-use instrument for elders and has adequate validity and reliability. RELEVANCE TO CLINICAL PRACTICE: The scale can be used as an assessment instrument when implementing cancer education programmes for elders. It can also be used to evaluate the effects of education programmes.