Phenology, Growth and Pod Yield of French Bean (Phaseolus vulgaris L.) as Influenced by Temperature Variations Under Different Sowing Dates

Kakon, SS; Mian, M. A. Rouf; Saha, Ripon K.; Nasreen, SS; Naher, Q; Hossain, MA

doi:10.3329/baj.v21i2.44489

Cited by 4 publications

(5 citation statements)

References 7 publications

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“…It was observed that in both varieties the flowering dynamics follow the same linear pattern, increasing the number of floral nodes with an increase in the GDD. This linear relation between the number of open flowers and the GDD was also observed in field conditions in bean cultivation (Jenni et al, 2000;Kakon et al, 2019). The flowering dynamics varied between different environmental conditions (Table 2).…”

Section: Resultssupporting

confidence: 69%

Flowering Dynamics in Alfalfa (Medicago sativa L.) Based on Heat Units

Bolaños-Aguilar¹,

Huyghe²,

Enríquez-Quiroz³

2021

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Objective: To describe the sequential pattern of reproductive development of Medicago sativa L. (flowering dynamic) using the relation between principal floral stem nodes and accumulated growing degree day (GDD) in different environmental conditions, and to determine the use of this relationship as a predictor of the seed harvesting date. Design/Methodology/Approach: It was carried out in random blocks and factorial arrangement of 2?5, with two repetitions. Each repetition was made up of 30 plants. Results: The flowering dynamic followed the same pattern between varieties, with a linear relation between GDD and number of floral nodes. The year A0 was different from the years A1 and A2. Therefore, A1 with cutting, and A2 with and without cutting presented less GDD during the flowering stage. In contrast, A0 showed more GDD during this period. In the different environmental conditions, the linear curves of flowering dynamic turned erratic after the tenth floral node (300 GDD) due to a low rate of plants with more than 10 floral nodes along the principal stem. Study Limitations/Implications: It is necessary to have a meteorological station near the alfalfa seed production site, in order to specify the GDD required for predicting the correct moment to harvest seeds. Findings/Conclusions: The reproductive development of M. sativa presents a linear relation between the number of floral nodes and GDD, which allows the prediction of the optimal seed harvesting date, in any environmental condition present.

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Section: Resultssupporting

confidence: 69%

Flowering Dynamics in Alfalfa (Medicago sativa L.) Based on Heat Units

Bolaños-Aguilar¹,

Huyghe²,

Enríquez-Quiroz³

2021

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“…The differences in Number of pods/ plant among varieties might be seen because of the difference in their genetic make-up [3]. Sowing dates based on temperature variation significantly affects the flowering behavior and pod yield of bean varieties [6].…”

Section: Number Of Pod Per Plant At Harvestmentioning

confidence: 99%

“…Green pods are rich in vitamins, protein and minerals. Moreover, a huge amount of French bean is consumed as soup [6]. The average national productivity of French bean is very small due to the inaccessibility of high yielding improved varieties and package of cultivation practices.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of French Bean (Phaseolus vulgaris L.) Genotypes for Growth, Yield and Seed Production at Khumaltar

Thapa¹,

Lamsal²,

Ghimire³

et al. 2022

Malaysian Journal of Halal Research

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The experiment was conducted at the end of July in NHRC, Khumaltar (1332 masl) located at Longitude 27.6485o N and Latitude 85.3253o E situated at Province no. 3, Lalitpur, Nepal in 2077/04/18 to 2077/04/28. The experiment was carried out in Randomised Complete Block Design (RCBD) with four treatments and five replications. The genotypes Trishuli, Chaumase, Semi Light Long and Semi Long Green Bean were used as treatment. Phenotypic traits like Plant Height, Days to maturity, Number of node at harvest in main stem, Flower colour, No of pod per plant at harvest, Dry pod colour, Single pod weight at harvest, pod length, Seed yield per plant, Seed weight per pod, 1000 seed weight, Moisture %, Seed weight per plant(gm), seed weight per pod after drying per plant (gm), seed weight after drying were taken. Plant height was highest in Semi long ligh which is 332 cmt and lowest in Trishuli which is 294.48 cm. Total number of seed was found highest in Semi Long Green 8.6 and least in Trishuli 7. The highest yield was found in Trishuli 2.69 ton/ha followed by Chaumase 2.56 ton/ha, Semi long green 2.33 ton/ha, and the lowest was seen in Semi Long Light 1.51 ton/ha.

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“…We allowed the base temperature to vary between 5°C and 8°C, choosing the upper limit based upon Kakon et al. (2018). Because our sample of genotypes is phonologically diverse, we allowed thermal time requirements to vary from between 28°C and 38°C.…”

Section: Methodsmentioning

confidence: 99%

“…We used joint numerical optimisation (scipy.optimize.minimize) to select genotype-specific base temperatures and thermal time requirements. We allowed the base temperature to vary between 5 C and 8 C, choosing the upper limit based upon Kakon et al (2018).…”

Section: Description Of the Modelsmentioning

confidence: 99%

A new framework for predicting and understanding flowering time for crop breeding

Deva,

Dixon,

Urban

et al. 2023

Plants People Planet

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Societal Impact StatementAs the growing season changes, the development of climate resilient crop varieties has emerged as a crucial adaptation in agricultural systems. Breeding new varieties for a changing climate requires enhanced capacity to predict the complex interactions between genotype and environment that determine flowering time. Hundreds of experiments with observations of flowering, the environment and plant genetics were used to build a model that can predict when a variety of common bean is going to flower. This model will help breeders to explore the phenological characteristics of their germplasm, speeding up selection for climate adaptation.Summary There is an urgent need to accelerate crop breeding for adaptation to a changing climate. As the growing season changes, crop improvement programmes must ensure that the phenological characteristics of the varieties they develop remain well suited to their target population of environments. Meeting this challenge will require a clear understanding of how existing germplasm behave across Genotype ∗ Environment (G ∗ E) to enhance the efficiency of selection. Recent work calls for the development of simple models that can accurately simulate genotypic variation in key traits across target population of environments. Accordingly, we develop a simple machine learning framework for modelling time to flowering across G ∗ E and apply this to common bean in an equatorial target population of environments. Within this framework, we test three machine learning models and find that the best performing models display high levels of accuracy across G ∗ E. We advance understanding of the environmental drivers of flowering time in equatorial conditions by showing that thermal time and accumulated evaporation are powerful predictors of flowering time across all three models.

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Phenology, Growth and Pod Yield of French Bean (Phaseolus vulgaris L.) as Influenced by Temperature Variations Under Different Sowing Dates

Cited by 4 publications

References 7 publications

Flowering Dynamics in Alfalfa (Medicago sativa L.) Based on Heat Units

Flowering Dynamics in Alfalfa (Medicago sativa L.) Based on Heat Units

Evaluation of French Bean (Phaseolus vulgaris L.) Genotypes for Growth, Yield and Seed Production at Khumaltar

A new framework for predicting and understanding flowering time for crop breeding

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