The application of best management practices increases the profitability and sustainability of rice farming in the central plains of Thailand

Stuart, Alexander M.; Pame, Anny Ruth P.; Vithoonjit, Duangporn; Viriyangkura, Ladda; Pithuncharurnlap, Julmanee; Meesang, Nisa; Suksiri, Prarthana; Singleton, Grant R.; Lampayan, Rubenito M.

doi:10.1016/j.fcr.2017.02.005

Cited by 42 publications

(45 citation statements)

References 24 publications

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“…Mean differences in total crop growth duration between SA 45 and SA 15 were 17 d in 2014 and 20 d in 2015. The mean difference between SA 35 and SA 15 (10-13 d) was observed in both years, while a difference of 6-7 d was observed in both years between SA 25 and SA 15 . In terms of plant growth duration in the main field (from transplanting to harvest), the older the seedlings at transplanting, the shorter the crop duration.…”

Section: Crop Growth and Developmentmentioning

confidence: 89%

“…No significant interactions between treatments were revealed in the ANOVA. The number of days from sowing to panicle initiation and from sowing to harvest was highest in SA 45 and lowest in SA 15 between SA treatments. Mean differences in total crop growth duration between SA 45 and SA 15 were 17 d in 2014 and 20 d in 2015.…”

Section: Crop Growth and Developmentmentioning

confidence: 91%

“…In this experiment, seedling age at the time of transplanting (SA) was assigned as the main plot, seedling density (SD) as the subplot, and variety (V) as the sub-subplot. Four levels of SA were used: 15 (SA 15 ), 25 (SA 25 ), 35 (SA 35 ), and 45 (SA 45 ) d-old seedlings; three levels for SD: One (SD 1 ), three (SD 3 ), and five (SD 5 ) seedlings per hill; and three different waxy or glutinous varieties: IRUBN0300-63-5-4 (V 1 ), TDK10239-SSD4-303-1 (V 2 ), and TDK-8 (V 3 ). V 1 was considered a high-tillering variety, while V 2 and V 3 were relatively low and medium tillering varieties, respectively.…”

Section: Experimental Setup and Treatment Detailsmentioning

confidence: 99%

“…At a 10 d transplanting interval, SA 15 was transplanted first, then followed by SA 25 , SA 35 , and SA 45 treatments, respectively. Transplanting dates during 2014 were the following: 1 July (SA 15 ), 10 July (SA 25 ), 20 July (SA 35 ), and 30 July (SA 45 ); whereas during 2015, transplanting dates were 2 July (SA 15 ), 12 July (SA 25 ), 23 July (SA 35 ), and 2 August (SA 45 ). Transplanting of seedlings was carefully done at a regular spacing of 20 cm × 20 cm in all treatments to minimize seedling transplanting shock and to allow the plants to recover quickly in the experimental field.…”

Section: Experimental Setup and Treatment Detailsmentioning

confidence: 99%

“…Irrigation dates were all noted and during irrigation events, field water tubes were read before and after each irrigation. The irrigation water input under AWD conditions was then computed using a procedure outlined by [15] as follows:…”

Section: Data Collection and Calculationmentioning

confidence: 99%

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Crop Performance and Water Productivity of Transplanted Rice as Affected by Seedling Age and Seedling Density under Alternate Wetting and Drying Conditions in Lao PDR

Lampayan

Xangsayasane

Bueno

2019

Water

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Drought is common under rainfed lowlands in Lao People's Democratic Republic, and with the uncertain onset of rains during the wet season, delay in transplanting results in yield reduction. This study aims to explore ways to ameliorate the negative influence of delayed transplanting on rice crop. A field experiment was conducted for two wet seasons to investigate the effect of seedling age and seedling density on crop performance in terms of grain yield and water productivity. The experiment was laid out in a split-split plot design in four replicates, with seedling age as the main plot, seedling density as the subplot, and varieties as the sub-sub plot. In both years, there were significant seedling age and variety interactions on grain yield. Higher grain yields were observed with older seedlings having stronger tillering propensity. Seedling density did not affect grain yields in both years, but on grain yield components. Shorter duration variety received less supplemental irrigation than longer duration varieties. Late transplanting improved total water productivity but decreased irrigation water productivity due to harvesting delay. The total crop growth duration (from sowing to maturity) was prolonged with transplanting delay. However, the total stay of plants in the main field (from transplanting to maturity) was reduced by 3-5 d for every 10 d delay in transplanting. The results indicated that a good selection of varieties and increasing seedling density improve crop performance and water productivity with delayed transplanting.

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Section: Crop Growth and Developmentmentioning

confidence: 89%

Section: Crop Growth and Developmentmentioning

confidence: 91%

Section: Experimental Setup and Treatment Detailsmentioning

confidence: 99%

Section: Experimental Setup and Treatment Detailsmentioning

confidence: 99%

Section: Data Collection and Calculationmentioning

confidence: 99%

See 3 more Smart Citations

Crop Performance and Water Productivity of Transplanted Rice as Affected by Seedling Age and Seedling Density under Alternate Wetting and Drying Conditions in Lao PDR

Lampayan

Xangsayasane

Bueno

2019

Water

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Optimizing wheat production and reducing environmental impacts through scientist–farmer engagement: Lessons from the North China Plain

Jiang

Zhu

Wang

et al. 2020

Food and Energy Security

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Producing high economic benefits and high grain yields with limited environmental impacts is crucial for feeding the world's growing population. Yet it remains challenging to improve the performance of one objective without creating unintended consequences for other objectives. This is especially difficult for smallholders navigating a diverse array of environmental and personal demands. This study demonstrates how combining participatory research through the Science and Technology Backyards (STB) approach with Pareto‐based ranking modeling can increase smallholder production while also reducing environmental impact. Through an intensive farmer survey in a 1 × 1 km grid in Quzhou County, we demonstrate that farmers engaged in STBs performed better according to multiple objectives (i.e., optimizing overall grain yield, benefit‐cost ratio, and GHG emissions, without compromising any one of these objectives) than farmer's not engaged in STBs. Moreover, we used a Pareto optimization approach (OPT) to determine the optimal smallholder scenario. We found that under OPT, grain yield could reach 9.5 t/ha, with a benefit‐cost ratio of 2.1, a 100% N recovery efficiency, and 7,395 kg CO2eq ha−1 GHG emissions. With OPT as a final goal, our research team worked with STB farmers to improve economic and environmental outcomes without compromising yield. Our findings demonstrate that no significant difference was obtained between farmers engaged in STBs and these under OPT. Compared with non‐STB farmers, STB farmers’ grain yield improved by 18%, benefit‐cost ratio improved by 26% due to improved N recovery efficiency, and GHG emissions were reduced by 31%. These improvements demonstrate the power of scientist–farmer engagement for optimizing wheat production. Such engagement allows farmers to modify their agronomic practices to more closely match Pareto optimal conditions, thus improving environmental and economic benefits without compromising yield. Our results provide solid evidence of the potential for sustainable wheat production by combining modeling with participatory research.

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The Goal Programming as a Tool for Measuring the Sustainability of Agricultural Production Chains of Rice

Silva

Varela

Lezama

et al. 2019

Advances in Neural Networks – ISNN 2019

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Agricultural activity is characterized by an intensive use of capital and a considerable dependence on external financing. Access to credit is often limited by the scarcity of resources and lack of guarantees, seriously affecting the productivity and economic performance of agricultural exploitations. The objective of this paper is to assess the sustainability of agricultural production chain of rice in Latin America using multi-criteria analysis tools to facilitate decision-making through a benchmarking process to contribute to their economic sustainability. The implementation of the model in an exploitation typy depending on financing sources (conservative, intermediate, and innovative) has revealed the conflict between the goals, being the intermediate exploitation, which gets the best results. The conclusions show that the flexibilization of financing options positively affects the economic performance.

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The application of best management practices increases the profitability and sustainability of rice farming in the central plains of Thailand

Cited by 42 publications

References 24 publications

Crop Performance and Water Productivity of Transplanted Rice as Affected by Seedling Age and Seedling Density under Alternate Wetting and Drying Conditions in Lao PDR

Crop Performance and Water Productivity of Transplanted Rice as Affected by Seedling Age and Seedling Density under Alternate Wetting and Drying Conditions in Lao PDR

Optimizing wheat production and reducing environmental impacts through scientist–farmer engagement: Lessons from the North China Plain

The Goal Programming as a Tool for Measuring the Sustainability of Agricultural Production Chains of Rice

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