• Proceedings of the Korean Society of Crop Science Conference
• /
• 2021.10a
• /
• pp.151-151
• /
• 2021

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2021.10a
• /
• pp.150-150
• /
• 2021

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2022.10a
• /
• pp.48-48
• /
• 2022

In recent, a demand for sweetpotato cultivation technology to expand the cultivated area of field crops in paddy fields is increasing. This research was carried out to establish suitable varieties and cultivation techniques for mass production of sweetpotato for processing raw materials. For the selection of varieties suitable for cultivation in rice fields for each processing purpose, 12 varieties in 2018 (8 varieties for starch, 4 as dried, chips and beverages), and 6 varieties in 2019 (4 varieties for starch including 'Daeyumi'; chips, semi-dried 'Pungwonmi'; beverage and coloring 'Shinjami') were used. Sweetpotato stems were planted in mid-May and harvested after 120 days to investigate the yield. Results revealed that the yield of sweetpotato (2019) for starch production, varied with variety as 'Gogeonmi' 3,926 > 'Jinhongmi' 3,428 > 'Daeyumi' 2,873 > 'Singeonmi' 2,752 kg/10a. The starch content was 20.2% in 'Daeyumi', 18.2 in 'Gogeonmi', 21.2 in 'Singeonmi', and 20.6% in 'Jinghongmi'. The total amount of starch was higher in 'Daeyumi' (730 kg/10a) and 'Gogeonmi' (731 kg/lOa). The yield of chips and edible varieties 'Pungwonmi' was 4,688 kg/10a. The yield of 'Shinjami' of purple variety such as beverages and powder was 3,139 kg/10a. Aaa result of evaluation sweetpotato yield by waterlogging treatments on different growing stages in paddy fields, the yields of 'Daeyumi' and 'Jinhongmi' varieties treated with waterlogging at the storage root formation stage decreased by 11.8% and 11.7%, respectively, compared to the control. In the case of waterlogging treatment at storage root swelling stage, Both varieties showed the lowest yield reduction at 7.0% and 4.8%, respectively. Based on these results, stable production and substitution effect of processing raw materials can be expected by cultivating sweetpotato varieties suitable for paddy cultivation.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 1989.02a
• /
• pp.42-43
• /
• 1989

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.45 no.4
• /
• pp.245-250
• /
• 2000

This study was conducted to analyze the responses of some agronomic traits to the different cultural environments and relations among the agronomic traits for selecting sesame varieties with higher cultural stabilities. The indexes for stability parameters measured were coefficient of variability, heritabilities, genetic correlations and path coefficients of agronomic traits according to locations and years in Korea. The heritabilities of agronomic traits showed different by locations and years. Number of seeds per capsule and 1000 seeds weight showed higher heritabilities, but stem length and seed weight per plant showed relatively lower heritabilities. Average heritabilities of some agronomic traits in 1998 were comparatively higher than those of 1999. Of six areas, Jinju area showed biggest coefficient of yield variability in 1998-1999. Iksan and Taegu areas showed higher heritabilities in 1998, but Iksan and Jinju areas showed lower heritabilities in 1999. Genetic correlations were slightly higher than corresponding phenotypic correlations. Stem length showed positive genetic correlation with the number of capsules per plant, and seed weight per plant and the number of capsule per plant showed positive genetic correlation with seed weight per plant. On the analysis of path coefficients, stem length and number of capsules effected highly on grain yield. Great regional variations were observed on the effects of agronomic traits on grain yield. Higher direct effects of stem length on grain yield were observed at Suwon, Chungwon, Taegu, Jinju and Naju areas, but in Iksan area was observed higher direct effect of the number of capsules per plant on grain yield in 1998. In 1999, higher direct effect of stem length on grain yield was observed at Chungwon and Suwon areas. Iksan and Taegu areas were also observed higher direct effect of the number of capsule per plant on grain yield.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.46 no.2
• /
• pp.130-133
• /
• 2001

The purpose of this study was to investigate the decreased ratio of growth and yield by delayed seeding and flowering because drought of spring season often cause to delay seeding and sprout emergence. Equation of linear regression, y=-11.914x＋818.61 ($R^2$=0.916) and y=-16.96lx＋913.98 ($R^2$=-0.885) were derived from relationship between sowing date and yield of leading variety, Yangbaeckkae in 1999 and 2000, respectively. Yield was decreased by 7, 24, 40, 57, 74%, respectively, according as sowing date was delayed more 5, 15, 26, 36, 46 days than May 15, standard sowing date under the culture mulched with black P.E. film. Number of capsules per plant and length of stem bearing capsule were greatly decreased, while plant height, stem diameter, and day to flowering were affected little by delayed seeding date. Equation of linear regression, y=-0.7081x＋41.04 ($R^2$=0.861) was derived from relationship between flowering date and yield of 33 accessions. Yield was decreased by 7.7, 8.3, 9.2, 10.1, 11.2%, respectively, according as flowering date was delayed more 1, 2, 3, 4, 5 days than July 3, normal flowering date of Yangbaeckkae when it was sown on May 15, and the more flowering date was delayed, the more yield was decreased. Number of capsules per plant and length of stem bearing capsules were greatly decreased, but plant height and harvest index were decreased little by delay of flowering date

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.21 no.2
• /
• pp.75-84
• /
• 2019

In this study, the random forest approach was used to predict the national mean rice yield of South Korea by using mean climatic factors at a national scale. A random forest model that used monthly climate variable and year as an important predictor in predicting crop yield. Annual yield change would be affected by technical improvement for crop management as well as climate. Year as prediction factor represent technical improvement. Thus, it is likely that the variables of importance identified for the random forest model could result in a large error in prediction of rice yield in practice. It was also found that elimination of the trend of yield data resulted in reasonable accuracy in prediction of yield using the random forest model. For example, yield prediction using the training set (data obtained from 1991 to 2005) had a relatively high degree of agreement statistics. Although the degree of agreement statistics for yield prediction for the test set (2006-2015) was not as good as those for the training set, the value of relative root mean square error (RRMSE) was less than 5%. In the variable importance plot, significant difference was noted in the importance of climate factors between the training and test sets. This difference could be attributed to the shifting of the transplanting date, which might have affected the growing season. This suggested that acceptable yield prediction could be achieved using random forest, when the data set included consistent planting or transplanting dates in the predicted area.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2017.06a
• /
• pp.96-96
• /
• 2017

Rice is a staple food for nearly half of the world's population, with more than 10,000 rice varieties providing almost one-quarter of the global per capita dietary energy supply. Grain size, panicle size and branch number, grain number in a panicle are directly associated with rice productivity. Recently several genes which increase grain yield were identified through map-based cloning. Gn1a, Cytokinin oxidase, is a major grain number QTL and regulates grain number per panicle. Dep1 increases panicle branching and reduced rachis length. SCM2 (APO1) was identified by a QTL for culm strength and increased spikelet number. OsSPL16 (GW8) controls grain size and shape and then increases 1000-weight of seed. In here, to identify genotype of genes related to yield in 400 of rice germplasms possessed in National Institute of Crop Science, we had first chosen 4 of well-known genes related to yield; Gn1a, Dep1, SCM2, and OsSPL16. Among these germplasms, 195, 382, 165, and 353 of germplasms harbored the dominant type of Gn1a, Dep1, SCM2, and OsSPL16, respectively. We grouped these germplasms into a total of 10 groups using genotypes of Gn1a, Dep1, SCM2 and OsSPL16. Most rice germplasms belong to group 1, harbored Gn1a, dep1, gw8 and APO1, and group 10, harbored gn1a, Dep1, GW8 and apo1. Hanareum2 is the highest productive cultivar in Korea but do not have dominant type OsSPL16, so belong to group 1. On the other hand, in the case of Unkwang, belongs to group 10, which has dominant type of OsSPL16 but do not have the remaining genes. We can grasp the differences in rice germplasms through the Profiling of genes related to these grain yield, which will be useful for cross-breeding to integrate grain yield genes. We are continuously observing the genotype and phenotype of rice that possesses grain yield genes.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2017.06a
• /
• pp.234-234
• /
• 2017

Recent abnormal weather, especially continued rainfall during sowing season causes difficulty in proper sowing of wheat and delayed sowing after November 15 is concerned about freezing damage during winter, resulting in reduction of wheat yield. To correspond government policy of crop sufficiency improvement and produce and supply raw wheat and barley steadily, expansion of cultivation area is necessary and spring sowing of wheat is required. To obtain basic information on the improvement of spring sown wheat and barley production, comparison and path coefficients analysis was conducted for yield and yield related components from autumn and spring sown wheat and barley. Path analyses were known as very useful in clarifying the effects of yield components on grain yield formation, which were not accurately reflected in simple correlation anaylses. Most cultivated 5 wheat and 9 barley cultivars were sown on October and February at Cheon-ju province according to standard sowing method. For the spring sowing of wheat and barley, the varieties having vernalization degree I~III are seeded in the mid of February and seeding rate is 200~250kg/ha which is increased by 25% than autumn sowing. N-fertilizer of 95 kg/ha and the same amount of P, K dressed in autumn are applied at once as basal fertilizer. The magnitude of direct effect in each yield components on yield was in sequence as follows. In autumn wheat, grain number per $spike{\geq}$ the number of spike per $m^2$>1000-grain weight and in spring wheat, grain number per $ spike{\geq}the$ number of spike per $m^2$> 1000-grain weight. In autumn naked barley, 1000-grain weight> the number of spike per $m^2$, grain number per spike and in spring barely, the number of spike per $m^2$> grain number per spike > 1000-grain weight. In autumn covered barley, grain number per spike>the number of spike per $m^2$ and in spring coverd barley, the number of spike per $m^2$> grain number per spike, 1000-grain weight. In autumn malt barley, the number of spike per $m^2$>1000-grain weight and in spring malt barley, the direct effects of three yield components were similar. According to the path analysis of yield components for spring sown wheat and barley, it was suggested that adequate number of spike per $m^2$ was most important factor for yield increase.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.53 no.3
• /
• pp.297-302
• /
• 2008

Application of genotype by environment ($G\;{\times}\;E$) interaction would be used for identifying optimum test condition of the varietal adaptation in the establishment of breeding purpose. Yield and yield components were used to perform additive main effect and multiplicative interaction (AMMI) analysis. Significant difference for $G\;{\times}\;E$ interaction were observed for all variable examined. For yield, 0.18 of total sum of squares corresponded to $G\;{\times}\;E$ interaction. Correlation analysis was carried out between genotypic scores of the first interaction principal component axis (IPCA 1) for agronomic characters. Significant correlations were observed between IPCA 1 for yield and capsule bearing stem length (CBSL), number of capsule per plant (NOC). The biplot of grain yield means for IPCA1 which accounted for 34% of the variation in total treatment sums of squares showed different reaction according to $G\;{\times}\;E$ interaction, genotypes and environments. Taegu showed relatively lower positive IPCA1 scores, and it also showed smaller coefficient variation of yield mean where it is recommendable as a optimal site for the sesame cultivar adaptation and evaluation trial. In case of variables, Yangbaek and M1 showed relatively lower IPCA1 scores, but the score direction showed opposite each other on the graph. Ansan, Miryang1, Miryang4, and Miryang6 seemed to be similar group in view of yield response against IPCA1 scores. These results will be helpful to select experimental site for sesame in Korea to minimize $G\;{\times}\;E$ interaction for the selection of promising genotype with higher stability.