Corn Leaf Aphid and Polysora Rust Resistance in Tropical Maze

This research includes two separate studies both of which incorporated generation mean analyses to interpret genetically the resistance to com leaf aphid and polysora rust in tropical maize. The first study focused on resistance to com leaf aphid in tropical sweet corn inbred Hi38-71. An inoculation technique using hair-pin clip cages and infestation quantification method using digital image analysis were developed for this study. During the study, a heavy natural infestation of com leaf aphids occurred in a seed production nursery. Yield loss by ranged from 38.9% to 98.8%, with an average loss of 71.7%. The clip-cage method was effective in distinguishing resistant and susceptible plants under field conditions. Resistance to com leaf aphid from Hi38-71 appeared to be monogenic and recessive. Aphid reproduction and population growth were measured on four different genotypes of varying aphid tolerance. Aphids on Hi38-71 had poorest performance over all aspects of growth and reproduction examined. Difference in number of progenies produced and days to 50% mortality appeared to account for most of the difference observed in the genetic study. The second study estimated genetic parameters for polysora rust resistance in Hi38-71. Hi38-71 exhibited moderately high resistance to polysora rust as well as resistance to com leaf aphid. Generation mean analysis showed that epistatic interactions of [aa] and [dd] along with simple dominance and additive gene effects were involved in controlling resistance in Hi38-71 to polysora mst. It is concluded that polysora resistance breeding cannot be based on selection of a single parent but a hybrid-breeding or reciprocal recurrent selection approach appears justified. The tropical sweet com inbred, Hi38-71 is a sib line of Hi38 which was bred from a bt-1 conversion of AA8sh2. AA8sh2 was studied for its resistance to com leaf aphid in 1970’s in Hawaii and was converted to common rust resistance, Rd1-D which broke down due to evolved racial variation of the pathogen. Hi38-71 is thus of particular value in sweet com breeding for tropical regions. This is due not only to its resistance to com leaf aphid and polysora, but to its high sweet com qualities and generally good combining abilities

Prediction of cultivar performance and heterogeneity of genotype variance, correlation and error variance in the Iowa Crop Performance Tests−Corn (Zea mays L.)

Multi-environment trials generally have highly unbalanced data structures in which a particular cultivar is only observed in a subset of all environments for which data are available. A very common approach to reporting data from such unbalanced data is to subset the data into balanced sets and restrict comparisons within balanced sets. Such an approach results in much information being ignored. In an attempt to make use of all available information, a likelihood-based mixed linear model approach can be chosen since unbalanced data can be analyzed in a straightforward manner. Two studies were undertaken to determine the complexity of heterogeneity of genotype variance, correlation and error variance and to investigate predictive ability of multivariate mixed linear models with varying levels of heterogeneity of those variance components for hybrid performance in unobserved environment in the data sets of the Iowa Crop Performance Tests-Corn. In the first study, a likelihood-based model selection approach identified evidence of heterogeneity of error variances among 58 of 65 singe-year and single-district balanced data sets for two model selection criteria, AIC and BIC. Heterogeneity of genotypic variances and correlations between pairs of environments was found in about half of the data sets analyzed. In the second study where two years of data within a district formed 51 highly unbalanced data sets, there was no substantial difference between the best and worst prediction models among all 24 models considered using cross validation, although the best models were generally simpler and parsimonious models. When there was a relatively large difference between the best and worst prediction model, the magnitude of the difference appeared to be highly positively associated with the difference in pooled GE interaction variance among models and to be negatively associated with number of common hybrids between two years in the data sets. There seemed to be a negative association between the difference in pooled GE interaction variance among models and the number of common hybrids in the data sets. A simulation study indicated that the cause of the deviation of pooled GE interaction variance that was obtained from heterogeneous models from that obtained from the homogeneous genotype variance covariance model was due mainly to poor estimation of some of the variance components by very small number of common hybrids across two years. Because the prediction ability based on an average BLUPs across environments are about the same for models with varying degrees of heterogeneity in genotype variance, correlation and error variance, we may still need to find a statistical model with the best fit of the observed data which would give the most appropriate shrinkage estimator for each environment

Corn leaf aphid and polysora rust resistance in tropical maize

xiii, 86 leavesThis research includes two separate studies both of which incorporated generation mean analyses to interpret genetically the resistance to com leaf aphid and polysora rust in tropical maize. The first study focused on resistance to corn leaf aphid in tropical sweet corn inbred Hi38-71. An inoculation technique using hair-pin clip cages and infestation quantification method using digital image analysis were developed for this study. During the study, a heavy natural infestation of com leaf aphids occurred in a seed production nursery. Yield loss by ranged from 38.9% to 98.8%, with an average loss of 71.7%. The clip-cage method was effective in distinguishing resistant and susceptible plants under field conditions. Resistance to com leaf aphid from Hi38-71 appeared to be monogenic and recessive. Aphid reproduction and population growth were measured on four different genotypes of varying aphid tolerance. Aphids on Hi38-71 had poorest performance over all aspects of growth and reproduction examined. Difference in number of progenies produced and days to 50% mortality appeared to account for most of the difference observed in the genetic study. The second study estimated genetic parameters for polysora rust resistance in Hi38-71. Hi38-71 exhibited moderately high resistance to polysora rust as well as resistance to com leaf aphid. Generation mean analysis showed that epistatic interactions of [aa] and [dd] along with simple dominance and additive gene effects were involved in controlling resistance in Hi38-71 to polysora rust. It is concluded that polysora resistance breeding cannot be based on selection of a single parent but a hybrid-breeding or reciprocal recurrent selection approach appears justified. The tropical sweet corn inbred, Hi38-71 is a sib line of Hi38 which was bred from a bt-1 conversion of AA8sh2. AA8sh2 was studied for its resistance to corn leaf aphid in 1970's in Hawaii and was converted to common rust resistance, Rd1-D which broke down due to evolved racial variation of the pathogen. Hi38-71 is thus of particular value in sweet corn breeding for tropical regions. This is due not only to its resistance to corn leaf aphid and polysora, but to its high sweet corn qualities and generally good combining abilities

Prediction of cultivar performance and heterogeneity of genotype variance, correlation and error variance in the Iowa Crop Performance Tests−Corn (Zea mays L.)

Multi-environment trials generally have highly unbalanced data structures in which a particular cultivar is only observed in a subset of all environments for which data are available. A very common approach to reporting data from such unbalanced data is to subset the data into balanced sets and restrict comparisons within balanced sets. Such an approach results in much information being ignored. In an attempt to make use of all available information, a likelihood-based mixed linear model approach can be chosen since unbalanced data can be analyzed in a straightforward manner. Two studies were undertaken to determine the complexity of heterogeneity of genotype variance, correlation and error variance and to investigate predictive ability of multivariate mixed linear models with varying levels of heterogeneity of those variance components for hybrid performance in unobserved environment in the data sets of the Iowa Crop Performance Tests-Corn. In the first study, a likelihood-based model selection approach identified evidence of heterogeneity of error variances among 58 of 65 singe-year and single-district balanced data sets for two model selection criteria, AIC and BIC. Heterogeneity of genotypic variances and correlations between pairs of environments was found in about half of the data sets analyzed. In the second study where two years of data within a district formed 51 highly unbalanced data sets, there was no substantial difference between the best and worst prediction models among all 24 models considered using cross validation, although the best models were generally simpler and parsimonious models. When there was a relatively large difference between the best and worst prediction model, the magnitude of the difference appeared to be highly positively associated with the difference in pooled GE interaction variance among models and to be negatively associated with number of common hybrids between two years in the data sets. There seemed to be a negative association between the difference in pooled GE interaction variance among models and the number of common hybrids in the data sets. A simulation study indicated that the cause of the deviation of pooled GE interaction variance that was obtained from heterogeneous models from that obtained from the homogeneous genotype variance covariance model was due mainly to poor estimation of some of the variance components by very small number of common hybrids across two years. Because the prediction ability based on an average BLUPs across environments are about the same for models with varying degrees of heterogeneity in genotype variance, correlation and error variance, we may still need to find a statistical model with the best fit of the observed data which would give the most appropriate shrinkage estimator for each environment.</p

Nitrogen (N) use efficiency and yield in rice under varying types and rates of N source: chemical fertilizer, livestock manure compost and food waste-livestock manure compost

Abstract An optimal use of organic composts derived from animal and food wastes could provide an opportunity to achieve both sustainable crop production and soil quality, and a lot of research has provided the evidence. The nitrogen use efficiencies (NUEs) is a definition to evaluate the interaction between crop and nitrogen (N), and, due to this reason, widely used in agriculture. The current work tried to evaluate NUEs as an indicator of N acquisition capacity and physiological responses of rice grown under varying N levels. To do this, we employed different types and rates of nitrogen source, chemical fertilizer, livestock manure-based compost and food waste and livestock manure-containing compost. Despite of the enhanced rice growth and yield by fertilization, a difference by types and rates of fertilization was not observed. Net photosynthetic rate was significantly higher in the treatments of 90–317 N kg ha-1. The NUE (N uptake efficiency × N utilization efficiency) was the highest in lower N application groups, and sharply reduced with an increase in fertilization rates. In contrast, the nitrogen harvest index (NHI, grain N/total biomass N, kg kg-1) showed higher (0.71– 0.76 kg kg-1) in greater N application treatments (≤ 317 N kg ha-1). Accordingly, in terms of NUE, our result suggest that rice may be affordable of the application of less than 300 kg N ha-1 (combination with chemical fertilizer and organic compost). Nevertheless, it should be investigated how excess N application affects soil quality, and how long rice plant and soil can accept excess N without an environmental load

Typical and Atypical Imaging Features of Malignant Lymphoma in the Abdomen and Mimicking Diseases

Malignant lymphoma typically presents with homogeneous enhancement of enlarged lymph nodes without internal necrotic or cystic changes on multiphasic CT, which can be suspected without invasive diagnostic methods. However, some subtypes of malignant lymphoma show atypical imaging features, which makes diagnosis challenging for radiologists. Moreover, there are several lymphomamimicking diseases in current clinical practice, including leukemia, viral infections in immunocompromised patients, and primary or metastatic cancer. The ability of diagnostic processes to distinguish malignant lymphoma from mimicking diseases is necessary to establish effective management strategies for initial radiological examinations. Therefore, this study aimed to discuss the typical and atypical imaging features of malignant lymphoma as well as mimicking diseases and discuss important diagnostic clues that can help narrow down the differential diagnosis

Digital Image Analysis of Low-Temperature Responses in Sweet Corn Hybrid Seedlings

Breeding for stress-tolerant hybrids begins with screening germplasm for tolerant genotypes. We employed a non-destructive and objective method to evaluate the low-temperature response of sweet corns at the seedling stage, using a digital image analysis. It was estimated using summed leaf area, a new parameter defined as the sum of the leaf area measured from images taken at different angles. The summed leaf area, SPAD, shoot and root fresh weight, and total root length were significantly different among hybrids. The group mean of sugary endosperm type was significantly higher than that of shrunken type for all traits but SPAD. For the summed leaf area, the top three ranked hybrids were from the sugary type, but the area for the following three hybrids from the shrunken type did not differ from that for the first three hybrids. The summed leaf area was correlated with SPAD (r = 0.49 **), shoot (r = 0.99 **) and root (r = 0.93 **) fresh weight, and total root length (r = 0.76 **). Phytoglycogen in seeds only had a significant correlation (r = 0.46 **) with the area. The summed leaf area of only one hybrid differed between normal- and low-temperature conditions. The low-temperature response based on the summed leaf area was reflected in the field condition, with a few exceptions. The results suggest that the summed leaf area via digital image analysis can be used to evaluate low-temperature response in sweet corns

Prohexadione-Calcium Mitigates the Overgrowth of Corn Seedlings

In the temperate climate of South Korea, specific corn varieties are cultivated using plug trays. The cultivation process is initiated from February to March within greenhouse facilities, maintaining a temperature below 10 degrees Celsius. Following this, in April, seedlings are transplanted to enable an exceptionally early harvest for increased profitability. However, the subsequent elevation in indoor temperatures leads to seedling overgrowth. This study explores the effectiveness of three plant growth regulators—paclobutrazol, prohexadione-calcium, and diniconazole–on super sweet corn seedlings. Significantly, the application of prohexadione-calcium at 2 ppm during the first leaf stage substantially reduces seedling height and impedes the growth of both the first and second internodes. This impact extends to leaf-related traits, manifesting reductions in the area, length, and width of the third leaf. Furthermore, prohexadione-calcium induces a significant decrease in both fresh and dried shoot weight, while simultaneously augmenting root weight. This alteration results in a noteworthy shift in the root–shoot ratio, particularly at 2 ppm. Subsequent experiments have identified the optimal concentration of prohexadione-calcium at 15 ppm, effectively mitigating overgrowth in both hybrid and inbred corn varieties. These findings provide essential insights for practitioners seeking to efficiently manage corn seedling overgrowth. The study contributes to understanding the retardant effect of prohexadione-calcium on various morphological traits, offering practical applications for optimizing plant growth regulator concentrations in corn cultivation strategies

A novel double mutation in cis in MFN2 causes Charcot-Marie-Tooth neuropathy type 2A

Mutations in mitofusin-2 (MFN2) are the most common cause of axonal Charcot-Marie-Tooth (CMT) neuropathy. Herein, we report a novel double mutation in cis (c.[474+4A > G; 668T > A]) in a Korean family with late-onset autosomal dominant mild axonal CMT. Transcriptional analysis demonstrated aberrant splicing with exon 5 skipping and premature termination of translation before the missense mutation in exon 7. Interestingly, the aberrant splicing was incomplete, with some of the primary transcripts being spliced correctly and expressing the downstream missense mutation. The pathogenic relevance of the missense mutation would not be appreciated without the leaky aberrant splicing and the insensitivity of MFN2 to haploinsufficiency.OAIID:oai:osos.snu.ac.kr:snu2012-01/102/2008000967/1SEQ:1PERF_CD:SNU2012-01EVAL_ITEM_CD:102USER_ID:2008000967ADJUST_YN:YEMP_ID:A077101DEPT_CD:801CITE_RATE:3.354FILENAME:MFN2_neurogenetics.pdfDEPT_NM:의학과EMAIL:[email protected]_YN:YCONFIRM: