Growth rates and yields of cassava at different planting dates in a tropical savanna climate

Phoncharoen, Phanupong; Banterng, Poramate; Vorasoot, Nimitr; Jogloy, Sanun; Theerakulpisut, Piyada; Hoogenboom, Gerrit

doi:10.1590/1678-992x-2017-0413

Cited by 30 publications

(45 citation statements)

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“…The results of the present study complement those of Phoncharoen et al (2019), who evaluated the performances of the same four genotypes in response to planting dates and a crop growth duration of 12 mo under well-watered conditions at one location. The results of the present study complement those of Phoncharoen et al (2019), who evaluated the performances of the same four genotypes in response to planting dates and a crop growth duration of 12 mo under well-watered conditions at one location.…”

Section: Discussionsupporting

confidence: 72%

“…This is the first study in Thailand that has been conducted on growth rates and stability of cassava genotypes Kasetsart 50, Rayong 9, Rayong 11, and CMR38-125-77 grown after rice in upper paddy field ecology and with a crop duration of 6 mo. The results of the present study complement those of Phoncharoen et al (2019), who evaluated the performances of the same four genotypes in response to planting dates and a crop growth duration of 12 mo under well-watered conditions at one location. The results from the present study provide valuable information on the desirable cassava genotype that can be cultivated in upper paddy field conditions during the off-season of rice or the dry season, thus increasing land use efficiency and providing extra income for the farmers.…”

Section: Discussionsupporting

confidence: 72%

“…The results revealed a significant contribution of leaf growth during 120 to 180 DAP (late growing period) to final biomass and pointed out that the cassava leaves during that time play an important role as a source of photosynthates for growth and yield formation. A study from Phoncharoen et al (2019) with the same four cassava genotypes but under ) using a graphical approach for analyzing the genotype main effect plus genotype ´ environment interaction (G + GE) or GGEbiplot software (PC 1 and PC 2 are the first and second principal components, respectively; SVP is singular value partitioning). Leaf growth rate (LGR), stem growth rate (SGR), and crop growth rate (CGR) during 120 to 180 d after planting (DAP) and storage root growth rate (SRGR) during 90 to 180 DAP for the four cassava genotypes grown at five environments.…”

Section: Discussionmentioning

confidence: 99%

“…De Tafur et al (1997) reported reasonable dry root yields in seasonally dry (?6.7 Mg ha −1 ) and semiarid (2.3 Mg ha −1 ) environments in northern Colombia where highly significant correlations between yield and leaf photosynthetic rates were observed across several cassava genotypes. A study from Phoncharoen et al (2019) with the same four cassava genotypes but under SVP is singular value partitioning). The genotype on the right side of double arrows line has higher performance than the average.…”

Section: Discussionmentioning

confidence: 99%

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Cassava Growth Analysis of Production during the Off‐Season of Paddy Rice

et al. 2019

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Cassava (Manihot esculenta Crantz) grown in upper paddy fields after rice (Oryza sativa L.) could increase cassava yield and improve land use efficiency. The objective of this study was to evaluate growth, yield, and starch content of four cassava genotypes grown after the harvest of rice in upper paddy fields in Thailand. Four cassava genotypes—cultivars Kasetsart 50, Rayong 9, and Rayong 11—and line CMR38‐125‐77 were evaluated during the 2015–2016 and 2016–2017 growing seasons for five environments. Each experiment had a randomized complete block design with four replications. Soil characteristics were assessed prior to planting, and crop growth and development and local weather conditions were recorded during the experiments. Environment affected all traits, but genotype and genotype × environment effects were nonsignificant for starch content at 180 d after planting (DAP) and for leaf growth rate (LGR) at 120 to 180 DAP. Average storage root dry weights across five environments were 4301, 3933, 3128, and 5824 kg ha−1 for Kasetsart 50, Rayong 9, Rayong 11, and CMR38‐125‐77, respectively. CMR38‐125‐77 was the most stable genotype for storage root fresh and dry weights, and total dry weight. Physiological determinants of both storage root yield and total biomass of cassava were crop growth rate (CGR) and net assimilation rate (NAR) for 30 to 90 DAP and LGR, stem growth rate (SGR), CGR, and NAR for 120 to 180 DAP, as well as storage root growth rate (SRGR) for 90 to 180 DAP. Leaf growth rate during 120 to 180 DAP is likely to be a new criterion for supporting cassava varietal selection. This investigation showed the feasibility of growing cassava between paddy rice seasons.

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Section: Discussionsupporting

confidence: 72%

Section: Discussionsupporting

confidence: 72%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Cassava Growth Analysis of Production during the Off‐Season of Paddy Rice

et al. 2019

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“…Kasetsart 50 is also one of interesting genotypes as it had high storage root dry weights at 360 DAP for both 2018/2019 and 2019/2020 (p < 0.01). The preferable performance of a CMR38-125-77 genotype based on biomass and yield in Thailand was recorded for planting under well water management [26], and under rainfed upper paddy field conditions during off-season of rice [14,27]. In addition to CMR38-125-77, the genotypes Rayong 7 and Rayong 9 also showed better performances of storage root and total dry weights at 180 DAP (at rainfall season) than at 270 and 360 DAP (during late rainy season and dry season) for both 2018/2019 and 2019/2020 (Table 1 and Figure 3), indicating a good response of these genotypes to well water conditions, and they would be recommended as the genetic resources for planting under irrigated condition.…”

Section: Performances Of Cassava Genotypesmentioning

confidence: 99%

Physiology, Growth and Yield of Different Cassava Genotypes Planted in Upland with Dry Environment during High Storage Root Accumulation Stage

et al. 2020

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Additional information on the physiological performances for different cassava genotypes would support better decision-making about desirable genetic resources for water-limited conditions. The objective of this study was to evaluate the physiological expression and yield of eight different cassava genotypes grown under a dry environment during high storage root accumulation. The eight cassava genotypes, i.e., Kasetsart 50, Huay Bong 80, Rayong 5, Rayong 7, Rayong 9, Rayong 11, Rayong 90, and CMR38-125-77 were evaluated under rain-fed upland conditions at Khon Kaen University, Thailand, during 2018 to 2020. A randomized complete block design (RCBD) with three replications was used. Soil moisture contents, chlorophyll fluorescence (Fv/Fm and Fv′/Fm′), net photosynthesis (Pn), stomatal conductance, water use efficiency (WUE), relative water content (RWC) for leaf, leaf area index (LAI), specific leaf area (SLA), starch content, crop dry weight, and starch yield were observed at 180, 270, and 360 days after planting (DAP), and weather data during the experimental period were also recorded. The results from both 2018/2019 and 2019/2020 indicated that Pn was positively and significantly correlated with stomatal conductance and Fv/Fm during the high storage root accumulation stage (270 and 360 DAP) with soil moisture content lower than field capacity. CMR38-125-77 had satisfactory performances in Pn, RWC, Fv/Fm, Fv′/Fm′, stomatal conductance, LAI, SLA, WUE, biomass, starch content, and starch yield at a last growth stage with soil moisture content lower than permanent wilting point. Significant association between crop dry weight and WUE at 360 DAP was recorded, and CMR38-125-77 and Kasetsart 50 were classified as favorable genotypes with high WUE and biomass.

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Performance of a model in simulating growth and stability for cassava grown after rice

et al. 2021

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Selecting the appropriate genotype for growing cassava (Manihot esculenta Crantz) after rice (Oryza sativa L.) can help increase the supply of cassava and improve land use efficiency. However, conducting the selection requires data from many years of multi-environment yield trials. A systems analysis approach using crop models can support this process. This study aimed to evaluate a potential application of the Cropping System Model (CSM)-MANIHOT-Cassava in determining genotype stability across different upper paddy field conditions when planted following rice. Four cassava genotypes, that is, Kasetsart 50, Rayong 9, Rayong 11, and CMR38-125-77, were evaluated for the six different environments in Thailand from the 2015 through 2018 growing seasons. The data required for the model were recorded, including biomass and yield. The cultivar coefficients of the CSM-MANIHOT-Cassava model for the four genotypes were calibrated and evaluated with the experimental data. The model was then run for historical weather data from 1988 to 2018 for the six environments for production under rain-fed conditions in upper paddy fields following rice. The overall results showed that the model was able to simulate biomass and yield of the four cassava genotypes quite well when compared to the experimental data. The model identified the same stable genotypes as presented in the actual trials. The genotype CMR38-125-77 was found to be a stable genotype and had the highest mean performance for both the actual yield trials and the simulation study.Therefore, the CSM-MANIHOT-Cassava model could be used to help identify the favorable genotype for planting in various paddy field conditions after rice harvest. INTRODUCTIONCassava (Manihot esculenta Crantz) is recognized as one of the most important food, feed, and energy crops across the Abbreviations: ASEAN, Association of the Southeast Asian Nations; CSM, Cropping System Model; DAP, days after planting; DSSAT, Decision Support System for Agrotechnology Transfer; MSD, mean square deviation; NODWT, node weight of the first stem of the shoot before forking; RCBD, randomized complete block design.

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Growth rates and yields of cassava at different planting dates in a tropical savanna climate

Cited by 30 publications

References 30 publications

Cassava Growth Analysis of Production during the Off‐Season of Paddy Rice

Cassava Growth Analysis of Production during the Off‐Season of Paddy Rice

Physiology, Growth and Yield of Different Cassava Genotypes Planted in Upland with Dry Environment during High Storage Root Accumulation Stage

Performance of a model in simulating growth and stability for cassava grown after rice

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