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Separating cassava storage root from its stem, known as cassava storage root cutting, represents a pivotal stage in cassava harvesting. It has become increasingly challenging due to a shortage of skilled labor. This research introduces an innovative solution: a cassava storage root-cutting robot (CSRCR) utilizing computer vision technology. The Mask-RCNN model is employed for precise cutting alignment detection. The moving mechanism utilizes a Stewart platform, and the cutting action is performed by a cylinder saw integrated into the robot. The specifications of these components, including dimensions, load capacity, and speed, were meticulously defined and calculated based on a physical survey of cassava plants. The robot's performance was evaluated through a three-step process. First, motion performance was assessed, and the results demonstrated acceptable levels of accuracy, repeatability, and workspace. Second, the optimal moving speed and the cutter's speed were determined. In the third step, the robot was integrated with computer vision technology. The integration achieved a remarkable success rate of 100 %. The average loss and trash were minimized to 1.44 % and 0.66 %, respectively, and the cycle time was 32.43 s. This successful integration not only demonstrates the robot's ability to cut cassava stems accurately in various orientations but also significantly improves efficiency by reducing loss and trash. The research findings pave the way for enhanced traditional cassava harvesting practices.

In a tropical savanna climate like Thailand, cassava can be planted all year round and harvested at 8 to 12 months after planting (MAP). However, it is not clear how water limitation during the dry season without rain affects carbon assimilation, partitioning, and yield. In this field investigation, six cassava genotypes were planted in the rainy season (August 2021) under continuous irrigation (control) or subjected to drought for 60 days from 3MAP to 5MAP during the dry season (November 2021 to January 2022) with no irrigation and rainfall. After that, the plants were rewatered and continued growing until harvest at 12MAP. After 60 days of stress, there were significant reductions in the mean net photosynthesis rate (Pn), petiole, and root dry weight (DW), and slight reductions in leaf, stem, and tuber DW. The mean starch concentrations were reduced by 42% and 16% in leaves and tubers, respectively, but increased by 12% in stems. At 6MAP after 30 days of rewatering, Pn fully recovered, and stem starch was remobilized resulting in a dramatic increase in the DW of all the organs. Although the mean tuber DW of the drought plants at 6MAP was significantly lower than that of the control, it was significantly higher at 12MAP. Moreover, the mean tuber starch concentration at 12MAP of the drought plants (18.81%) was also significantly higher than that of the controls (16.46%). In the drought treatment, the high-yielding varieties, RY9, RY72, KU50, and CMR38-125-77 were similarly productive in terms of tuber DW and starch concentration while the breeding line CM523-7 produced the lowest tuber biomass and significantly lower starch content. Therefore, for cassava planted in the rainy season in the tropical savanna climate, the exposure to drought during the early growth stage was more beneficial than the continuous irrigation.

Background: The phenomenon of global warming results in a significant rise in temperature which adversely affects the growth, physiology, and yield of rice. In order to gain insight into the impacts of booting heat stress (at 42 °C, 3 h for 7 days), we investigated its effect in three rice genotypes, namely, N22, KDML105 and IR64. Results: Booting heat stress caused an extended phenology and a lower photosynthesis and plant growth rate but an increase in chalkiness. Although, the prolonged phenology from dough to physiological maturity resulted in a longer duration of grain filling, the adverse effects of this were a significantly lower yield component, yield and harvest index across all varieties of rice. Among cultivars, N22 demonstrated an adapted ability to maintain leaf gas exchange and compensated for the vegetative part by an increase in tiller numbers resulting in a less affected growth rate. It caused extended grain filling by prolonging the phenology. Consequence, N22 had the lowest reduction in number of seed panicle−1, number of filled seeds hill−1, yield, harvest index, and percentage chalkiness. KDML105 was adapted to booting heat stress by maintaining leaf gas exchange, increasing specific leaf area and prolonging phenology. The longest extended phenology and high photosynthesis during dough grain were associated with moderate yield reduction and chalkiness. Nonetheless, IR64 demonstrated significant reductions in photosynthesis, growth rate, and yield but the highest percentage of grain chalkiness. Conclusion: Therefore, the response of N22, KDML105 and IR64 to booting heat stress could be indicated as being heat tolerant, moderately heat sensitive, and heat sensitive, respectively. This approach can be applied to crop modeling and rice heat tolerance in breeding programs.

The Cropping System Model (CSM)-MANIHOT-Cassava provides the opportunity to determine target environments for cassava (Manihot esculenta Crantz) yield trials by simulating growth and yield data for various environments. The aim of this research was to investigate whether cassava production on paddy fields in Northeast, Thailand could be grouped into mega-environments using the model. Simulations for four different cassava genotypes grown on paddy field following rice harvest was conducted for various soil types and the weather data from 1988 to 2017. The genotype main effect plus genotype by environment interaction (GGE biplot) technique was used to group the mega-environments. The analyses of yearly data showed inconsistent results across years for environment grouping and for the winning genotypes of the individual environment group. An analysis using GGE biplot with the average value of the simulated storage root dry weight (SDW) for 30 years indicated that all 41 environments were grouped into two different mega-environments. This study demonstrated the ability of the CSM-MANIHOT-Cassava to help identify the mega-environments for cassava yield trials on paddy field during off-season of rice that could help reduce both time and resources.

The yield potential of cassava might be increased by enhancing light interception and the ability to convert energy into biomass and yield, which is described as radiation use efficiency (RUE). The objective of this study was to determine light interception, extinction coefficient (k), and RUE of three cassava genotypes (Kasetsart 50 (KU50), Rayong 11 (RY11), and CMR38-125-77) under seasonal variations. The field experiments were conducted in a randomized complete block design with four replications, using two planting dates for 2 years at Khon Kaen, Thailand. Data were recorded for weather conditions, light interception, leaf area index (LAI), and biomass. Solar radiation interception, RUE, and k were calculated. Light interception of the crop planted in May sharply increased in the early growth stage, whereas the crop planted in November slowly increased and could maintain higher light interception from the mid–late growth stages. Light interception and LAI had a moderate to high coefficient of determination (R2 = 0.61–0.89) for three cassava genotypes and all planting dates. The k values ranged from 0.59 to 0.94, varying by genotypes and planting dates, indicating that the leaf orientation of the three cassava genotypes was horizontally oriented. The relationship between biomass accumulation and cumulative solar radiation produced a high value of R2 (0.86–0.99). The RUE for biomass (RUEbi) varied by genotype and planting date, ranging from 0.66 g MJ−1 to 0.97 g MJ−1. However, the RUE for storage root dry weight (RUEsr) ranged from 0.29 g MJ−1 to 0.66 g MJ−1. The RUEbi and RUEsr in each genotype on each planting date were significantly different. The highest RUEbi and RUEsr were found at 4–6 and 7–9 MAP for almost all genotypes and planting dates, except for the crop planted in November 2015, when both RY11 and CMR38-125-77 had the highest RUEbi at 10–12 MAP. RY11 had a lower LAI compared to other genotypes, which contributed to lower light disruption and lower RUEbi and RUEsr. KU50 and CMR38-125-77 could maintain canopy light interception during canopy development and storage root accumulation stages and had high RUEbi and RUEsr, resulting in high biomass and crop yield.

The evaluation of leaf area provides valuable information for decision-making for the cassava yield trail. The objectives of this study were (1) to determine the relationship between the leaf area and yield of the segregating populations and (2) to investigate the suitable mathematical model for calculating cassava leaf area. The single-row trial for 60 segregating progenies of Kasetsart 50 × CMR38–125–77 was conducted from 2021 to 2022. The trial for eighteen progenies and the Kasetsart 50 and CMR38–125–77 was carried out in 2022. The sampled leaves for each genotype were collected to measure the leaf area. The length (L) and width of the central lobe (W), number of lobes (N), the product of the length and width (L × W; K), and the product of the length and number of lobes (L × N; J) were recorded for developing the mathematical models. The result showed that there were statistically significant correlations between the maximum individual leaf area and the total crop fresh weight and storage root fresh weight. The mathematical model LA = −3.39L + 2.04K + 1.01J − 15.10 is appropriate to estimate the maximum individual leaf area and leaf area index (LAI). This mathematical model also provided the estimated individual maximum leaf area that had the highest correlation with actual biomass at the final harvest as compared to the other three functions. The results showed statistical significance for the estimated LAI and biomass correlation.

ABSTRACT: Details on growth and yield for cassava planted on different dates are useful for determining suitable genotypes for particular growing seasons. Our aim was to study growth and yield of cassava planted on different dates. Four cassava genotypes (Kasetsart 50, Rayong 9, Rayong 11 and CMR38-125-77) were evaluated using a randomized complete block design (RCBD) with four replications in six growing periods (20 Apr, 25 May, 30 June, 5 Oct, 10 Nov and 15 Dec 2015-2016) at Khon Kaen, Thailand. Soil properties were determined prior to planting, and crop traits and weather data were recorded. The six planting dates had a statistically significant effect on all crop traits. Low temperatures and solar radiation related to low biomass accumulation rates and short periods of linear phases for total crop and storage root dry weights with the 30 June planting date. CMR38-125-77 is likely to be a good genotype with respect to total crop and storage root dry weights at final harvest for almost all growing dates, except for the 20 Apr. Leaf area index (LAI) at 120, 240 and 300 days after planting (DAP), specific leaf area (SLA) at 120 DAP, storage root growth rate (SRGR) during 300-360 DAP and leaf growth rate (LGR) during 60-120 and 300-360 DAP were the components for the physiological determinants of total crop and storage root dry weight. The relationship between these physiological traits and storage root could be useful for cassava breeding.

Temperature is one of the most critical factors affecting cassava metabolism and growth. This research was conducted to investigate the effects of short-term exposure to extreme cool (15 °C) and hot (45 °C) temperature on photosynthesis, biochemical and proteomics changes in potted plants of two cassava cultivars, namely Rayong 9 and Kasetsart 50. One-month-old plants were exposed to 15, 30, and 45 °C for 60 min in a temperature chamber under light intensity of 700 μmol m−2 s−1. Compared to the optimum temperature (30 °C), exposure to 15 °C resulted in 28% reduction in stomatal conductance (gs) and 62% reduction in net photosynthesis rate (Pn). In contrast, gs under 45 °C increased 2.61 folds, while Pn was reduced by 50%. The lower Pn but higher electron transport rate (ETR) of the cold-stressed plants indicated that a greater proportion of electrons was transported via alternative pathways to protect chloroplast from being damaged by reactive oxygen species (ROS). Moreover, malondialdehyde (MDA) contents, a marker related to the amount of ROS, were significantly higher at low temperature. Proteomics analysis revealed some interesting differentially expressed proteins (DEPs) including annexin, a multi-functional protein functioning in early events of heat stress signaling. In response to low-temperature stress, AP2/ERF domain-containing protein (a cold-related transcription factor) and glutaredoxin domain-containing protein (a component of redox signaling network under cold stress) were detected. Taken together, both cultivars were more sensitive to low than high temperature. Moreover, Rayong 9 displayed higher Pn under both temperature stresses, and was more efficient in controlling ROS under cold stress than Kasetsart 50.

Determining the effect of irrigated and rainfed conditions on light interception, light extinction coefficient (k), radiation use efficiency (RUE), biomass, and storage root accumulation of cassava was the objective of this study. The field experiment was arranged in a randomized complete block design (RCBD) with four replications. The effect of irrigated and rainfed water conditions in cassava were evaluated under two planting dates for two years. Light interception depended on k and LAI which affected solar radiation accumulation and thus biomass production for cassava. The k values ranged from 0.49 to 0.93 a nd 0.46 to 0.86 for irrigated and rainfed crops, respectively. The RUEbi and RUEsr depended on water conditions and crop growth stages and seasons, whereas rainfed crops in the May planting were slightly lower in RUEbi than irrigated crops. RUEbi of the crop planted in November was not significantly different for irrigated and rainfed crops. Irrigation at the late growth stage could maintain higher LAI, light interception, and RUE for the crop planted in May, whereas those in November planting were not significantly different.

Matching fertilization with crop needs is important for maximizing yields and reducing fertilizer losses. Seasonal variation in nutrient uptake dynamics is poorly understood and thus, the ability to optimize fertilization strategies is limited. This study aims to investigate the effects of planting dates on macronutrient uptake dynamics in cassava genotypes with full irrigation. The performance of cassava genotypes, i.e., CMR38-125-77, Kasetsart 50 and Rayong 11, were evaluated in the early rainy (ERS) and post rainy seasons (PRS) for two years using a randomized complete block design with four replicates. The plants were harvested at 1, 3, 6, 9 and 12 months. Planting dates had significant effects on the accumulation of dry matter and storage roots as well as nutrient uptakes and partitioning. On average, the total nutrient uptake per plant to produce 2831–3279 g of biomass with 1244–1810 g of storage roots in the ERS varied among cassava genotypes, ranging from 21.1–24.3 g N, 5.1–5.9 g P, 26.5–29.5 g K, 14.1–22.2 g Ca, 6.1–7.6 g Mg and 2.0–2.3 g S. The total nutrient uptake per plant to produce 3353–3824 g of biomass with 1604–2253 g of storage roots in the PRS ranged from 27.1–32.4 g N, 5.2–6.0 g P, 29.1–31.3 g K, 11.9–20.3 g Ca, 7.3–9.9 g Mg and 1.2–1.5 g S. In the ERS, the majority of the total nutrient uptake occurred at the early growth stages, whereas in the PRS, this occurred at the mid- to late growth stages. At final harvest, the percentages of nutrient removal by the storage roots for ERS were 24.7–36.0% N, 26.0–32.3% P, 43.4–51.5% K, 12.4–17.6% Ca, 22.2–31.5% Mg and 27.2–31.5% S, whereas in the PRS the percentages were 30.4–44.4% N, 33.3–41.6% P, 44.7–57.3% K, 12.0–15.1% Ca, 20.2–28.1% Mg and 12.0–25.4% S. CMR38-125-77 exhibited satisfactory performance in nutrient uptake, nutrient use efficiency and storage roots yield across the planting dates. The evidence obtained from this study would greatly facilitate more efficient adoption of precision agriculture in cassava production by applying recommended fertilizers, e.g., rates, kinds and timings, according to crop demand in each growing season in Thailand and for choosing superior cassava genotypes.

Crop simulation models can be used to identify appropriate genotypes and growing environments for improving cassava yield. The aim of this study was to determine the best genotypes for different cassava production environments using the cropping system model (CSM)–MANIHOT–Cassava. Data from cassava experiments that were conducted from 2009–2011 and 2014–2015 at Khon Kaen, Thailand, were used to evaluate the model. Simulations were then conducted for different scenarios using four cassava genotypes (Kasetsart 50, Rayong 9, Rayong 11, and CMR38–125–77), twelve planting dates (at monthly intervals starting in January and ending in December), and ten locations in Thailand under fully irrigated and rainfed conditions using 30 years of historical weather data. Model evaluation with the experimental data for total biomass and storage root yield indicated that the model classified well for relative productivity among different planting dates. The model indicated that growing cassava under irrigated conditions generally produced higher biomass and storage root yield than under rainfed conditions. The cassava genotype CMR38–125–77 was identified for high biomass, while the genotype Rayong 9 was identified as a good genetic resource for high yield. The December planting date resulted in the highest biomass for all locations, while the February planting date produced the highest storage root yield for almost all locations. The results from this study suggest that the CSM–MANIHOT–Cassava model can assist in determining suitable genotypes for different cassava production environments for Thailand, and that this approach could be applicable to other cassava growing areas.

Growth and photosynthesis performance of cassava during early vegetative growth are important determinants of final biomass. The objective of this work was to investigate canopy structure and photosynthesis performance of four cassava genotypes (Rayong 9, Rayong 11, Kasetsart 50, and CMR38-125-77) growing under irrigation at 3 and 6 months after planting (3MAP and 6MAP). Data for the 3MAP plants were collected from cassava planted on 30 June (Rainy PD), 10 November (Cool PD1), and 15 December (Cool PD2) 2015; and for the 6MAP from those planted on 20 April 2015 (Hot PD), Rainy PD, and Cool PD1. The plants growing in the rainy season had significantly higher leaf area index (LAI) than those growing in the cool and hot seasons. Consequently, they had lower percentage light penetration at the bottom of canopy, and therefore more light interception through the canopy, and hence a higher mean net photosynthesis rate (Pn) across the six canopy levels. At the 3MAP, which is the stage of maximum rate of leaf and stem growth, the Rainy PD and Cool PD2 plants of CMR38-125-77 showed the highest LAI and highest mean Pn. Similarly, the Cool PD1 plants of Kasetsart 50 showed the highest LAI and highest mean Pn. In contrast, at 6MAP during the stage of active starch accumulation in storage roots, the genotypes with the highest mean Pn were the ones having an intermediate (CMR38-125-77 for the Hot PD) or low LAI (Rayong 9 for the Rainy PD, and CMR38-125-77 for the Cool PD1). Data on variations in canopy structure and photosynthesis potentials of different cassava genotypes in response to seasonal variations may be useful for crop growth modeling and may be employed as a criterion for the selection of suitable genotypes for each growing season.

The objective of this study was to investigate the effect of canopy size (CS) on light penetration and leaf photosynthesis of three cassava genotypes (Kasetsart 50 (KU50), Rayong 11 and CMR38-125-77) under two planting dates in two years. Data were recorded for CS, leaf area index (LAI), leaf photosynthesis, biomass (BM), storage root yield (SRY), starch content (SC) and harvest index (HI). The variation of CS depended on temperature, solar radiation (SR), relative humidity (RH) and day length (DL). In early growth stages, the crops planted in May had higher CS than the crops planted in November, because they were subjected to higher temperature, more SR, higher RH and longer DL. In contrast, the storage root accumulation of the crops planted in November was under better climatic factors than the crops planted in May. Therefore, the crops planted in November had higher BM and SRY than the crops planted in May for KU50 and CMR38-125-77. However, Rayong 11 in the May planting date maintained higher CS during storage root accumulation than the other genotypes, and BM and SRY of Rayong 11 were not different for the two planting dates in both years. KU50 and CMR38-125-77 had higher BM and SRY in the November planting, whereas in the May planting, the SRY and BM of the three genotypes were not significantly different. Genotypes that maintained high CS at the storage root accumulation stage could be indirectly selected for high BM and SRY in cassava breeding programs.

This study aims to evaluate seasonal variation on starch production of different cassava genotypes planted under irrigated condition. Three cassava genotypes (Kasetsart 50, Rayong 11 and CMR38-125-77) were evaluated in two different growing seasons, i.e., early rainy seasons (ERS) and post rainy seasons (PRS) for two years. A randomized complete block design with four replicates was employed in each growing season. The starch yield was more strongly associated with growing season (28.3%), whereas starch content, amylose content, amylose-amylopectin ratio were more associated with genotypes (19.9–30.7%). Planting cassava in the ERS had rapid growth rates of starch yield and granule size in early growth stages, whereas planting cassava in the PRS had rapid growth rates of these traits in the middle to late growth stages. Cassava planted in the PRS had higher starch yield than the ERS for most genotypes except for Rayong 11, which had no significant differences between growing seasons. The yield and content of starch and size of starch granule continuously increased from four to twelve months after planting (MAP) for most cassava genotypes. Unlike other genotypes, CMR38-125-77 in the ERS gave the highest starch yield and its granule at 10 MAP; however, at 12 MAP, it was still higher than other genotypes. CMR38-125-77 was a preferable genotype, since it had a faster rate of starch formation and more starch and amylose contents, as well as starch yield in both ERS and PRS.

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.

Although cassava can be planted throughout the year, its starch qualities may vary based on the date of planting. Seasonal variation on starch content, starch yield, starch granule size and amylose content of cassava cv. Rayong 9 grown under irrigated and rainfed conditions were studied for four planting dates in Thailand. A randomized complete block design with four replications was used in each planting. Planting dates consisted of hot-dry (20-Apr), early-rainy (30-Jun), late-rainy (5-Oct) and cool seasons (15-Dec). At final harvest, planting date accounted for the largest variations for starch yield (60.8%), starch granule size (38.2%), amylose content (50.5%) and ratio of amylose to amylopectin (53.7%), whereas starch content was affected more by water regime (52.1%). Supplemental irrigation did not significantly increase starch yield and other parameters for most planting dates, except for starch yield of the crop planted in the hot-dry season. This indicated that irrigation at the late-growth stages (during Sep to Mar) for the crop planted in the hot-dry season helped to increase starch yield; however, irrigation was unnecessary for other planting dates once cassava was established. The crops planted in the late-rainy and cool seasons had a greater starch content and starch yield than other planting dates for both irrigated and rainfed crops, whereas the crop planted in the hot-dry season had high starch yield for the irrigated crops only. In this study, the crops planted in the early-rainy season showed the worst performances for starch content and starch yield for both irrigated and rainfed crops. The data provided information on the responses of starch yield and its characteristics under irrigated and rainfed conditions at different planting dates, which can be useful for designing cultural practices with respect to water management and planting period in order to obtain optimum starch yield and qualities.

The cropping system model, namely, the crop environment resource synthesis-rice (CSM-CERES-Rice) model, is a decision supporting tool for the design of crop management. This study aimed to determine management practices for increasing rice (Oryza sativa L.) production in Laos by using the CSM-CERES-Rice model. The model was evaluated with data sets from the TDK8 and TDK11 cultivars in farmers’ fields in the Vientiane plain in 2012. Anthesis and harvesting dates, growth and yield for various management scenario combinations (eight transplanting dates × two levels of plant densities × three rates of nitrogen (N) fertilizer application) for both cultivars were simulated by the model from 1980 to 2012. The model evaluation results showed strong agreement between simulated and observed data for days to harvest with a difference within four days. The model provided acceptable accuracy for grain yields with normalized root mean square error values ranging between 1 and 16 %. The results from the model application indicated that TDK8 and TDK11 produced similar yields. Transplanting TDK8 with two plant densities produced similar yields. The highest yield for both cultivars was achieved on the transplanting date of 15 Jan. N-fertilizer application at 60 and 120 kg N ha−1 was able to increase yield for TDK8 by 50 and 87 %, respectively, and for TDK11 by 54 and 70 %, respectively. Rice transplanted on 15 Jan with 5 seedlings hill−1 and N-fertilizer at 120 kg N ha−1 had the highest average yield for both cultivars with 6,460 and 6,351 kg ha−1 for TDK8 and TDK11, respectively. The CSM-CERES-Rice model is an alternative tool in determining crop management practices for rice production.

Climate change is viewed as a cause in accelerating the rate of invasion by alien species in addition to the globalization of anthropogenic activities. Ecological niche modeling has become an instrument in predicting invasion from natural or invaded ranges to uninvaded ranges based on the presence records of organisms and environmental parameters. This study explored the changes in the distributions of globally noxious alien species (Aegratina adenophora, Ageratum conyzoides, Chromolaena odorata, Lantana camara, Mikania micrantha, and Parthenium hysterophorus) in Bhutan, to provide evidence that even a mountain environment is under the threat of invasion given the change in climatic conditions. With fairly high accuracy, the model results suggest that there will be a potential increase in the areas of invasion among most of the species, except Parthenium hysterophorus, which will experience a northerly shift and decline in distribution. The results also indicate changes in patterns of invasion, some becoming more concentrated toward a given direction, while others become more dispersed over time. This study provides a framework that can be used in the strategic control of the species, future detection surveys, and further research.

The objectives of this study were to investigate the effect of seasonal variation on canopy size, and the effect of canopy size on light penetration of ‘Rayong 9′ cassava under irrigated and rainfed conditions. Rayong 9 was planted under two water regimes in a randomized complete block design with four replications in May and November for two years. At final harvest, years were significantly different (p ≤ 0.05) for biomass, shoot dry weight, and harvest index and contributed to large portions of total variations in shoot dry weight (56.8%) and HI (44.5%). Planting date was a significant source of variations in all measured characters, and it contributed to the largest portions of variations in biomass, storage root dry weight and storage root fresh weight (46.1−60.9%). Water regimes were not significantly different for most characters except for harvest index (p ≤ 0.01). The canopy of the crop planted in May grew rapidly in early growth stages in the rainy season and then slowly after the rainy season. The canopy of the crop planted in November grew rapidly in the middle to the late growth stages. Irrigation did not significantly increase root yield although it slightly increased canopy development, leaf area index (LAI), light penetration and photosynthesis. Irrigation at the late growth stages of the crop planted in May significantly increased storage root yield. Irrigation at these growth stages helped maintain canopy development, LAI and light penetration.

Photosynthesis performance during early vegetative growth is an important physiological trait determining yield of cassava, but limited information is currently available for the tropical savanna climate of Asia. Diurnal photosynthesis and chlorophyll fluorescence of the three-month-old plants of four commercial cassava genotypes (Rayong 9, RY9; Rayong 11, RY11; Kasetsart 50, KU50 and CMR38-125-77) grown under irrigation, were investigated in three seasons i.e., rainy, cool and hot. The mean daily net photosynthetic rate (Pn) across genotypes in the rainy season (11.75 µmolCO2/m2/s) was significantly lower than that in the cool season (14.60 µmolCO2/m2/s). Daily mean Pn in the hot season was 14.32 µmolCO2/m2/s. In the rainy season, maximum photochemical quantum yield of PSII (Fv/Fm) and effective quantum yield of PSII photochemistry (ΦPSII) were significantly higher than the other seasons, while electron transfer rate (ETR) and non-photochemical quenching (NPQ) were significantly lower. Genotypic variation was observed during the hot season in which RY11 had the highest and CMR38-125-77 the lowest mean daily Pn. The prominent mechanism to avoid damages from stress during afternoon in the hot season was to reduce leaf temperature by enhancing transpiration for RY11; to close stomata early for RY9, and to increase NPQ for CMR38-125-77.

Information on the forking, leaf area index, and biomass of cassava for different growing seasons could help design appropriate management to improve yield. The objective was to evaluate the forking date, leaf growth, and storage root yield of different cassava genotypes grown at different planting dates. Four cassava genotypes (Kasetsart 50, Rayong 9, Rayong 11, and CMR38–125–77) were evaluated using a randomized complete block design with four replications. The cassava genotypes were planted on 20 April, 25 May, 30 June, 5 October, 10 November, and 15 December 2015, and 19 May and 3 November 2016. The soil properties prior to the planting, forking date, leaf area index (LAI), dry weights, harvest index (HI), starch content, and weather data were recorded. The forking date patterns for all of the growing seasons varied depending on the cassava genotypes. The weather caused occurring in the first forking for the Rayong 11 and CMR38–125–77 and the second forking for Rayong 11, but not for Kasetsart 50. The forking CMR38–125–77 had a higher LAI, leaf dry weight, biomass, and storage root dry weight than the non-forking Rayong 9. The higher storage root yields in Rayong 9 compared with Rayong 11 were due to an increased partitioning of the storage roots.

The information on genotypic responses to the seasonal variation in the starch content, starch yield, and starch quality of cassava is limited. The objective of this research was to investigate the seasonal variation of starch characteristics of three cassava genotypes grown under irrigation. The experiment was conducted at four planting dates (20 April, 30 June, 5 October, and 15 December 2015). Three cassava genotypes (CMR38-125-77, Kasetsart 50, and Rayong 11) were evaluated in a randomized complete block design with four replications and the plants were harvested at 12 months. The planting date contributed the largest portion of the total variation in the starch content, starch yield, and starch granule size. The amylose content variability was heavily influenced by genotype. Cassava planted on 5 October or 15 December had greater starch content, starch yield, and starch granule in most genotypes. This was likely due to a higher temperature and solar radiation during the 3⁻9 months post-planting. CMR38-125-77 showed a consistently high starch content, starch yield, and high amylose content for most planting dates except for the starch yield on 20 April, of which Rayong 11 was the best. These findings will be useful for choosing suitable cassava genotypes for different growing seasons and for facilitating breeding efforts for high starch-yielding and high-quality cassava starch in the future.