Revisiting yield gaps and the scope for sustainable intensification for irrigated lowland rice in Southeast Asia

Silva, João Vasco; Pede, Valerien O.; Radanielson, Ando Mariot; Kodama, Wataru; Duarte, Antônia Eliene; Guia, Annalyn H. de; Malabayabas, Arelene Julia B.; Pustika, Arlyna Budi; Argosubekti, N; Vithoonjit, Duangporn; Hieu, Pham Thi Minh; Pame, Anny Ruth P.; Singleton, Grant R.; Stuart, Alexander M.

doi:10.1016/j.agsy.2022.103383

Cited by 23 publications

(5 citation statements)

References 51 publications

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“…Since Thailand is one of the world's major rice exporters, rice is a key economic plant of the country. Rice is vastly cultivated nationwide and consumed not only domestically but also internationally [8]. Nowadays, geoinformatics has been widely applied to contemporary agriculture, including rice cultivation, due to its rapid advancement [11]and [12].…”

Section: Discussionmentioning

confidence: 99%

“…However, the demand for rice has been tremendously rising [3]and [4]owing to myriad global concerns such as overpopulation [5], food insecurity [6], and climate change [7] Countries in Southeast Asia, a major rice-producing region, such as Vietnam, Myanmar, and Thailand are widely acknowledged as primary rice exporters across the globe. In particular, the Chao Phraya River Basin [8], the largest basin of Thailand, is one of the most intensive rice-producing areas worldwide. In 2019, around 40% of the total labor force in Thailand belonged to the agricultural sector, and 6.04 million tons of rice (with a value of 3.74 billion USD) were exported, making the country become the world's second largest rice exporter of that year [9].…”

Section: Introductionmentioning

confidence: 99%

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The Application of Unmanned Aerial Vehicles (UAVs) and Extreme Gradient Boosting (XGBoost) to Crop Yield Estimation: A Case Study of Don Tum District, Nakhon Pathom, Thailand

2023

IJG

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Rice (Oryza sativa L.) is a staple food for more than half of the global population. This research, therefore, aims to explore the estimation of crop yields towards the application of unmanned aerial vehicles (UAVs). The research areas are the sample rice fields owned by Sam Ngam Large-Scale Rice Production Community Enterprise in Don Tum District, Nakhon Pathom. The data collected by both RGB and multispectral UAVs was used for estimating the crop yields of Rice Department 41 (RD41), a rice variety, and then analyzed by a geographic information system (GIS). Multiple Linear Regression was applied to factor analysis for the purpose of crop yield estimation based on the factors investigated and obtained by the UAVs. These factors included vegetation indexes (i.e. Normalized Difference Vegetation Index, Green Normalized Difference Vegetation Index, and Triangular Greenness Index), plant height, and canopy coverage. The prediction of the analysis model was proved to be valid (R2 = 0.99; RMSE = 2.506 g.). Extreme Gradient Boosting (XGBoost) was applied to increase the accuracy of the estimation (RMSE = 0.557 g.; MAE = 0.364). The findings of study showed that the utilization of UAVs could contribute to the estimation of crop yield in the research areas.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Application of Unmanned Aerial Vehicles (UAVs) and Extreme Gradient Boosting (XGBoost) to Crop Yield Estimation: A Case Study of Don Tum District, Nakhon Pathom, Thailand

2023

IJG

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“…Four subsequent yield gaps were estimated, that is, the overall yield gap calculated as the difference between Yp and Ya, which was further decomposed into its technology, resource, and e ciency components. The technology yield gap refers to the difference between Yp and Y HF , hence re ecting the inability of farm technologies to achieve Yp (see Silva et al 2022;2017a). The resource yield gap refers to the difference between Y HF and Y TEx , hence capturing the yield penalty due to sub-optimal rates of applied inputs.…”

Section: Yield Levels and Yield Gapsmentioning

confidence: 99%

Opportunities to narrow potato yield gaps and increase resource use efficiency in West Java, Indonesia

Pronk,

Gunadi,

Hermelink

et al. 2024

Preprint

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Consumer demand for potato in Indonesia increases while production stagnates. Government policy recognized this discrepancy and prioritized efforts to increase potato yields through farmer support programs with moderate effects to date. This study aimed to decompose potato yield gaps and identify agronomic yield constraints in West Java. Actual yield and management practices of 178 farm registrations over five consecutive growing seasons were analyzed with stochastic frontier analysis. The potential yield (Yp) for each registration was simulated with the LINTUL-POTATO-DSS crop model. The overall yield gap was decomposed into its efficiency, resource, and technology components. The potato yield gap was 21.5 t ha -1, corresponding to 54% of Yp. The efficiency and technology yield gaps were both ca. 10 t ha -1, corresponding to 26% of Yp, and the resource yield gap was negligible. All fields received sufficient inputs for potential production but most inputs were used inefficiently. An early first fungicide spray after emergence and frequently spraying to control late blight increased yields significantly. The seed generation planted was critical to potato yield gaps as yield decreased significantly with older generations. Some high yielding fields, however, were also planted with older generations, so other production factors contributed to the yield gap as well. Improving potato yield will require well performed late blight control, the use of high-quality seed, and improved management practices, which include reduced input rates, to reduce current yield gaps sustainably.

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“…Dengan kata lain produktivitas potensial adalah kemungkinan hasil maksimum yang dapat diperoleh dalam kondisi terkendali (Chandrasekaran et al, 2010). Silva et al (2022) merinci gap produktivitas adalah akibat gap teknologi, sumberdaya, dan efisiensi.…”

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“…Terdapat berbagai kendala agronomis dan sosial ekonomi sehingga terjadi gap produktivitas yang cukup besar antara potensial dan aktual. Untuk menurunkan gap hasil, maka produktivitas perlu ditingkatkan dengan cara peningkatan input (Lobell, Cassman, and Field 2009) atau melakukan intensifikasi (Woittiez et al 2017) seperti peningkatan penggunaan pupuk (Silva et al 2022) dan peningkatan teknologi (Najafi et al 2018) seperti penggunaan varietas unggul baru, pupuk dan irigasi.…”

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Gejala Produktivitas Rendah dan Pertanian Degeneratif

Evizal

Prasmatiwi²

2022

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Agronomy examines complex agricultural production concepts such as Sustainable Agriculture, Good Agricultural Practices, Regenerative Agriculture into the best practical technologies that farmers can apply. Important agronomic variables in agricultural cultivation include production and productivity. Plant productivity is influenced by many interacting factors. This paper aims to examine the symptoms of decreased productivity and symptoms of degenerative agriculture. The decline in production and productivity that continues in the long term indicates a degenerative agro-ecosystem. Degenerative agriculture is an agricultural practice that causes productivity to continue to decline as a result of a decrease in the carrying capacity of agro-ecosystems, including soil, plants and other flora, fauna, microbes, climate and society. The decrease in the carrying capacity of the soil is shown, among others, by land degradation, a decrease in soil organism diversity and activity, declining of organic matter content and the availability of nutrients in the soil due to nutrient depletion transported by harvest, erosion and inappropriate cultivation practices. In addition, it will discuss the factors driving the degenerative agroecosystem that interact with each other. These factors include land degradation, decreased biodiversity, continuous planting of varieties and species of plants, use of chemical inputs, pest and disease attacks, and climate change. Mitigating these factors means choosing a path to regenerative agriculture. Key words : Agroecosystem, biodiversity, degenerative, sustainable, regenerative, productivity

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Revisiting yield gaps and the scope for sustainable intensification for irrigated lowland rice in Southeast Asia

Cited by 23 publications

References 51 publications

The Application of Unmanned Aerial Vehicles (UAVs) and Extreme Gradient Boosting (XGBoost) to Crop Yield Estimation: A Case Study of Don Tum District, Nakhon Pathom, Thailand

The Application of Unmanned Aerial Vehicles (UAVs) and Extreme Gradient Boosting (XGBoost) to Crop Yield Estimation: A Case Study of Don Tum District, Nakhon Pathom, Thailand

Opportunities to narrow potato yield gaps and increase resource use efficiency in West Java, Indonesia

Gejala Produktivitas Rendah dan Pertanian Degeneratif

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