Browsing by Person "Khongdee, Nuttapon"

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Adaption to rainfall and temperature variability through integration of mungbean in maize cropping
(2021) Khongdee, Nuttapon; Cadisch, Georg
Climate change has threatened global agricultural activities, particularly in tropical and subtropical regions. Rainfed cropping regions have become under more intense risk of crop yield loss and crop failure, especially in upland areas which are also prone to soil erosion. In Thailand, maize is one of the important economic crops and mostly grown in upland areas of northern regions. Maize yield productivity largely depends on the onset of seasonal rainfall. Uncertainty of seasonal rainfall adversely affects maize yield productivity. Therefore, coping strategies are urgently needed to stabilize maize yields under climate variability. In order to identify suitable coping strategies, early maize sowing and maize and mungbean relay cropping were tested on upland fields of northern Thailand. The specific aims of this thesis were (i) monitoring growth and yield performance of maize and mungbean under relay cropping, (ii) testing early maize sowing and maize – mungbean relay cropping as coping strategies under rainfall variations (Chapter 2), (iii) testing effects of relay cropping on growth and yield of mungbean under weather variability (Chapter 4), (iv) determining suitable sowing dates under erratic rainfall patterns by using a modelling approach (Chapter 3), and (v) developing a technique for diagnosis of crop water stress in maize by thermal imaging technique (Chapter 5). Specifically, in Chapter 2 early maize planting or relay cropping strategies were assessed for growth and yield performance of maize under heat and drought conditions. Maize planted in July showed, regardless of sole or relay cropping, low grain formation as a consequence of adverse weather conditions during generative growth. However, July-planted maize relay cropping produced higher above ground biomass than July-planted maize sole cropping and early planting of maize in June. Despite unfavourable weather conditions, maize was, at least partly, able to compensate for such effects when relayed cropped, achieving a higher yield compared to maize sole cropping. June-planted maize sole cropping, however, was fully able to escape such a critical phase and achieved the highest grain yield (8.5 Mg ha-1); however, its associated risk with insufficient rain after early rain spells needs to be considered. Relay cropping showed to be an alternative coping strategy to cope with extreme weather as compared to maize sole cropping. However, relay cropping reduced maize growth due to light competition at young stages of maize before mungbean was harvested (Chapter 2). This negative impact of relay cropping is partly off-set by considering of land equivalent ratio (Chapter 4). Land equivalent ratio indicated a beneficial effect of relay cropping over maize and mungbean solecropping (LER = 2.26). During high precipitation, mungbean sole cropping produced higher yield (1.3 Mg ha-1) than mungbean relay cropping (0.7 Mg ha-1). In contrast to the period of low precipitation, mungbean relay cropping used available water more efficiently and was able to establish its plant, while mungbean sole cropping could not fully withstand severe drought and heat. Mulching effects of maize residues conserved soil water which was then available for mungbean to grow under extreme weather condition. WaNuLCAS modelling approaches can be used to support the decision of maize sowing date in northern Thailand to cope with climate change as indicated by goodness of fit of the model validation (R2 = 0.83, EF = -0.61, RMSE = 0.14, ME = 0.16, CRM = 0.02 and CD = 0.56) (Chapter 3) using forty-eight-year of historical rainfall patterns of Phitsanulok province. Only 27.1% of rainfall probability was classified as a normal rainfall condition. Consequently, maize in this region had faced with high rainfall variability. From long term simulation runs, the current maize sowing date led to strong maize yield variation depending on rainfall condition. Early maize sowing i.e. 15 and 30 days before farmers and staggered planting produced higher yield than current farmers’ practice (mid of July) in most conditions (91.7%). Simulations revealed that water was the most limiting factor affecting maize growth and yield while nutrients (N and P) had only limited impact. Results of the WaNuLCAS model could be used to identify optimal maize planting date in the area prone to soil erosion and climate variation of northern Thailand; however, the model cannot fully account for heat stress. Thermal imaging technique is a useful method for diagnose maize water status. As presented in chapter 5, the developed Crop Water Stress Index (CWSI) using a new approach of wet/dry references revealed a strong relationship between CWSI and stomatal conductance (R2 = 0.82). Our study results established a linear relationship to predict final maize grain yield and CWSI values at 55 DAS as follows “Yield = -16.05×CWSI55DAS + 9.646”. Both early planting of maize and/or relay cropping with legumes are suitable coping strategies for rainfall variability prone regions. The positive response of early planting and legume relay cropping offers the opportunity of having a short-duration crop as sequential crop, providing an additional source of protein for humans and fostering crop diversification on-site. This leads to a win-win situation for farmers, food security and the environment due to an enhanced sustainability of this cropping system.
Thermal imaging for assessment of maize water stress and yield prediction under drought conditions
(2022) Pradawet, Chukiat; Khongdee, Nuttapon; Pansak, Wanwisa; Spreer, Wolfram; Hilger, Thomas; Cadisch, Georg
Maize production in Thailand is increasingly suffering from drought periods along the cropping season. This creates the need for rapid and accurate methods to detect crop water stress to prevent yield loss. The study was, therefore, conducted to improve the efficacy of thermal imaging for assessing maize water stress and yield prediction. The experiment was carried out under controlled and field conditions in Phitsanulok, Thailand. Five treatments were applied, including (T1) fully irrigated treatment with 100% of crop water requirement (CWR) as control; (T2) early stress with 50% of CWR from 20 days after sowing (DAS) until anthesis and subsequent rewatering; (T3) sustained deficit at 50% of CWR from 20 DAS until harvest; (T4) late stress with 100% of CWR until anthesis and 50% of CWR after anthesis until harvest; (T5) late stress with 100% of CWR until anthesis and no irrigation after anthesis. Canopy temperature (FLIR), crop growth and soil moisture were measured at 5‐day‐intervals. Under controlled conditions, early water stress significantly reduced maize growth and yield. Water deficit after anthesis had no significant effect. A new combination of wet/dry sponge type reference surfaces was used for the determination of the Crop Water Stress Index (CWSI). There was a strong relationship between CWSI and stomatal conductance (R² = 0.90), with a CWSI of 0.35 being correlated to a 64%‐yield loss. Assessing CWSI at 55 DAS, that is, at tasseling, under greenhouse conditions corresponded best to the final maize yield. This linear regression model validated well in both maize lowland (R² = 0.94) and maize upland fields (R² = 0.97) under the prevailing variety, soil and climate conditions. The results demonstrate that, using improved standardized references and data acquisition protocols, thermal imaging CWSI monitoring according to critical phenological stages enables yield prediction under drought stress.