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All Journal AGRIVITA, Journal of Agricultural Science
Prakit Somta
Kasetsart University
Agriculture, Biological Sciences & Forestry

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Journal : AGRIVITA, Journal of Agricultural Science

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DISSECTING QUANTITATIVE TRAIT LOCI FOR AGRONOMIC TRAITS RESPONDING TO IRON DEFICEINCY IN MUNGBEAN [Vigna radiata (L.) Wilczek] Somta, Prakit; Prathet, Prayoon; Kongjaimun, Alisa; Srinives, Peerasak
AGRIVITA, Journal of Agricultural Science Vol 36, No 2 (2014)
Publisher : Faculty of Agriculture University of Brawijaya and Indonesian Agronomic Assossiation

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Abstract

Calcareous soil is prevalent in many areas of the world agricultural land causing substantial yield loss of crops. We previously identified two quantitative trait locus (QTL) qIDC3.1 and qIDC2.1 controlling leaf chlorosis in mungbean grown in calcareous soil in two years (2010 and 2011) using visual score and SPAD measurement in a RIL population derived from KPS2 (susceptible) and NM10-12-1 (resistant). The two QTLs together accounted for 50% of the total leaf chlorosis variation and only qIDC3.1 was confirmed, although heritability estimated for the traits was as high as 91.96%. In this study, we detected QTLs associated with days to flowering , plant height, number of pods per plants, number of seeds per pods, and seed yield per plants in the same population grown under the same environment with the aim to identify additional QTLs controlling resistance to calcareous soil in mungbean. Single marker analysis revealed 18 simple sequence repeat markers, while composite interval mapping identified 33 QTLs on six linkage groups (1A, 2, 3, 4, 5 and 9) controlling the five agronomic traits. QTL cluster on LG 3 coincided with the position of qIDC3.1, while QTL cluster on LG 2 was not far from qIDC2.1. The results confirmed the importance of qIDC3.1 and qIDC2.1 and revealed four new QTLs for the resistance to calcareous soil. 
Evaluating Genetic Coefficients of KUML4 Mung Bean Variety for a Crop Simulation Model Inboonchuay, Tawatchai; Wongmaneeroj, Audthasit; Phankamolsil, Napaporn; Chungopast, Sirinapa; Kongthon, Sahaschai; Somta, Prakit
AGRIVITA Journal of Agricultural Science Vol 46, No 3 (2024)
Publisher : Faculty of Agriculture University of Brawijaya in collaboration with PERAGI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17503/agrivita.v46i3.4324

Abstract

The Decision Support System for Agrotechnology Transfer (DSSAT) cropping system model is a part of the management module that processes user inputs describing crop management. The precision and accuracy of cropping models require recent research to calibrate and validate models according to climate changes and new cultivars. This study aims to determine the genetic coefficient (GC) of the mung bean variety KUML4 for the CSM-CROPGRO Model and compare predicted data from the model with observed data in the phenology, growth, yield and yield component used in DSSAT. Mung bean is planted in two seasons (dry and rainy seasons) at two locations. Plant growth is monitored at V4, R3, R6 and R7. DSSAT CROPGRO-cowpea model is used to calibrate the GC with the generalized likelihood uncertainty estimation (GLUE). Results show that the GC evaluation of mung bean by using the second planting date in the highest growth and yield plot, then the genetic coefficient of KUML4 was calibrated by GLUE until predicted values of plant growth and development were close to observed values. The GC of KUML4 mung bean could estimate growth, such as shoot weight, leaf area index, and plant height. The prediction of mung bean yield is acceptable.
Co-Authors Alisa Kongjaimun Chungopast, Sirinapa Inboonchuay, Tawatchai Kongthon, Sahaschai Peerasak Srinives Phankamolsil, Napaporn Prayoon Prathet Wongmaneeroj, Audthasit