Academia.eduAcademia.edu

Yield gap variation in rice cultivation in Indonesia

Profile image of Muhamad HidayantoMuhamad Hidayanto

2023, Open Agriculture

https://doi.org/10.1515/OPAG-2022-0241
visibility

…

link

1 file

Abstract

The rice yield gap (YG) is a global concern, requiring more detailed studies spatially and temporally. As a staple food in Indonesia, rice was produced from 7.4 Mha paddy fields in 2019. Better insight into the YG helps assess measures to boost rice production. However, the information on YG variation among regions scale is limited. This study aimed to identify the rice YG based on 295 historical trial datasets from 23 provinces in Indonesia. We surveyed published trial results from 2012 to 2022 and analyzed YGs, expressed as the percentage of farmer yield (FY). The potential yield (PY) was estimated from field trial results using introduced rice cultivation technology package, whereas FY from results using existing farmer practices. Our study showed that the average YG was 62% in rainfed, 54% in tidal, and 32% in irrigated paddy fields. The YG was significantly high in the paddy fields of Kalimantan (74%) and Maluku-Papua (49%), while the lowest was in Sulawesi (27%) and Java (31%). The YG varied significantly with geo-regions, rice varieties, and cultivation technology packages. Closing the YG and ensuring sustainable rice production requires the implementation of sustainable intensification through applying site-specific technology packages, reallocation of agricultural interventions to a higher YG region, and rice variety improvement to increase PY.

Related papers

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

Agricultural Systems, 2022

Food security Smallholder agriculture OBJECTIVE: The objective of this study was to decompose rice yield gaps into their efficiency, resource, and technology components and to map the scope to sustainably increase rice production across four lowland irrigated rice areas in Southeast Asia through improved crop management. METHODS: A novel framework for yield gap decomposition accounting for the main genotype, management, and environmental factors explaining crop yield in intensive rice irrigated systems was developed. A combination of crop simulation modelling at field-level and stochastic frontier analysis was applied to household survey data to identify the drivers of yield variability and to disentangle efficiency, resource, and technology yield gaps, including decomposing the latter into its sowing date and genotype components. RESULTS AND CONCLUSION: The yield gap was greatest in Bago, Myanmar (75% of Yp), intermediate in Yogyakarta, Indonesia (57% of Yp) and in Nakhon Sawan, Thailand (47% of Yp), and lowest in Can Tho, Vietnam (44% of Yp). The yield gap in Myanmar was largely attributed to the resource yield gap, reflecting a large scope to sustainably intensify rice production through increases in fertilizer use and proper weed control (i.e., more output with more inputs). In Vietnam, the yield gap was mostly attributed to the technology yield gap and to resource and efficiency yield gaps in the dry season and wet season, respectively. Yet, sustainability aspects associated with inefficient use of fertilizer and low profitability from high input levels should also be considered alongside precision agriculture technologies for site-specific management (i.e., more output with the same or less inputs). The same is true in Thailand, where the yield gap was equally explained by the technology, resource, and efficiency yield gaps. The yield gap in Indonesia was mostly attributed to efficiency and technology yield gaps and yield response curves to N based on farmer field data in this site suggest it is possible to reduce its use while increasing rice yield (i.e., more output with less inputs). SIGNIFICANCE: This study provides a novel approach to decomposing rice yield gaps in Southeast Asia's main rice producing areas. By breaking down the yield gap into different components, context-specific opportunities to narrow yield gaps were identified to target sustainable intensification of rice production in the region.

View PDFchevron_right
Yield gaps in rice-based farming systems: Insights from local studies and prospects for future analysis
Grant R Singleton

The important contribution of rice to global food security requires an understanding of yield gaps in rice-based farming systems. However, estimates of yield gaps are often compromised by a failure to recognize the components that determine them at a local scale. It is essential to define yield gaps by the biological limitations of the genotype and the environment. There exist a number of methods for estimating rice yield gaps, including the use of crop growth simulation models, field experiments and farmer yields. We reviewed the existing literature to (i) assess the methods used to estimate rice yield gaps at a local scale and to summarize the yield gaps estimated in those studies, (ii) identify practical methods of analysis that provides realistic estimates of exploitable rice yield gaps, and (iii) provide recommendations for future studies on rice yield gaps that will allow accurate interpretation of available data at a local level. Rice yield gap analysis can be simplified without sacrificing precision and context specificity. This review identifies the comparison of the attainable farm yield (the mean of the top decile) with the population mean, as a practical and robust approach to estimate an exploitable yield gap that is highly relevant at the local level, taking into account what is achievable given the local socioeconomic conditions. With this method we identified exploitable yield gaps ranging from 23 to 42% for one particular season in four different rice growing areas in Southeast Asia. To enable accurate estimation and interpretation of yield gaps in rice production systems, we propose a minimum dataset needed for rice yield gap assessment. Future studies on rice yield gaps should consider the region, season and crop ecosystem (e.g. upland rain-fed, lowland irrigated) as a minimum to facilitate decisions at a local level. In addition, we recommend taking into account the cultivar, soil type, planting date, crop establishment method and nitrogen application rates, as well as field topography and toposequence for rainfed systems. A good understanding of rice yield gaps and the factors leading to yield gaps will allow better targeting of agricultural research and development priorities for livelihood improvement and sustainable rice production.

View PDFchevron_right
Assessing Opportunities to Increase Yield and Profit in Rainfed Lowland Rice Systems in Indonesia
Ahmad Suriadi

Agronomy, 2021

In this study, we aimed to improve rice farmers’ productivity and profitability in rainfed lowlands through appropriate crop and nutrient management by closing the rice yield gap during the dry season in the rainfed lowlands of Indonesia. The Integrated Crop Management package, involving recommended practices (RP) from the Indonesian Agency for Agricultural Research and Development (IAARD), were compared to the farmers’ current practices at ten farmer-participatory demonstration plots across ten provinces of Indonesia in 2019. The farmers’ practices (FP) usually involved using old varieties in their remaining land and following their existing fertilizer management methods. The results indicate that improved varieties and nutrient best management practices in rice production, along with water reservoir infrastructure and information access, contribute to increasing the productivity and profitability of rice farming. The mean rice yield increased significantly with RP compared with FP...

View PDFchevron_right
Yield gap of rainfed rice in farmers’ fields in Central Java, Indonesia
Annie Boling

Agricultural Systems, 2010

Yield constraint analysis for rainfed rice at a research station gives insight into the relative role of occurring yield-limiting factors. However, soil nutrient status and water conditions along toposequences in rainfed farmers' fields may differ from those at the research station. Therefore, yield constraints need to be analyzed in farmers' fields in order to design management strategies to increase yield and yield stability. We applied production ecological concepts to analyze yield-limiting factors (water, N) on rice yields along toposequences in farmers' fields using data from on-farm experiments conducted in 2000-2002 in Indonesia. Potential, water-limited, and N-limited yields were simulated using the ORYZA2000 crop growth model. Farmers' fields showed large spatial and temporal variation in hydrology (354-1235 mm seasonal rainfall, À150 to 50 cm field-water depth) and fertilizer doses (76-166 N, 0-45 P, and 0-51 kg K ha À1 ). Farmers' yields ranged from 0.32 to 5.88 Mg ha À1 . The range in yield gap caused by water limitations was 0-28% and that caused by N limitations 35-63%, with large temporal and spatial variability. The relative limitations of water and N in farmers' fields varied strongly among villages in rainfed rice areas and toposequence positions, with yield gaps due to water and N at the top and upper middle positions higher than at the lower middle and bottom toposequence positions, and yield gaps in late wet seasons higher than those in early wet seasons. Management options (e.g. crop establishment dates, shortening turnaround time, using varieties with shorter duration, supplemental irrigation) to help the late-season crop escape, or minimize the negative effects of, late-season droughts and supplying adequate N-fertilizer are important for increasing yield in rainfed lowland rice in Indonesia. More N-fertilizer should be given to upper toposequence positions than to lower positions because the former had a lower indigenous nutrient supply and hence a better response to N-fertilizer inputs. Systems approaches using production ecological concepts can be applied in yield constraint analysis for indentifying management strategies to increase yield and yield stability in farmers' fields in other rainfed lowland areas.

View PDFchevron_right
Quantifying rice yield gaps and their causes in Eastern and Southern Africa
Bayuh Belay

Journal of Agronomy and Crop Science, 2020

The demand for rice in Eastern and Southern Africa is rapidly increasing because of changes in consumer preferences and urbanization. However, local rice production lags behind consumption, mainly due to low yield levels. In order to set priorities for research and development aimed at improving rice productivity, there is a need to characterize the rice production environments, to quantify rice yield gaps—that is, the difference between average on‐farm yield and the best farmers’ yield—and to identify causes of yield gaps. Such information will help identifying and targeting technologies to alleviate the main constraints, and consequently to reduce existing yield gaps. Yield gap surveys were conducted on 357 rice farms at eight sites (19–50 farmers per site) across five rice‐producing countries in Eastern and Southern Africa—that is Ethiopia, Madagascar, Rwanda, Tanzania and Uganda—for one or two years (2012–13) to collect both quantitative and qualitative data at field and farm le...

View PDFchevron_right
Yield gaps in intensive rice-maize cropping sequences in the humid tropics of Indonesia
Yulianes Hosang

Field Crops Research, 2019

Multiple crops can be grown sequentially on the same field within a 12-month period in tropical humid environments. Yield gap analysis focusing on both individual crop cycles and cropping systems can help identifying opportunities to increase annual productivity. Indonesia was used as a case study to evaluate options for increasing annual productivity in rice and maize through closure of existing yield gaps at both crop-cycle and cropping-system levels. A total of 31 (rice) and 11 (maize) sites for irrigated crops, and 24 (rice) and 29 (maize) sites for rainfed crops were selected based on their share of national harvested area. Crop modeling based on local weather, soil, and management data, together with average farmer yield data, were used to estimate yield potential and yield gaps for individual crop cycles (total: 367) and cropping systems (total: 154). Extra rice and maize production potential were estimated for different scenarios of crop intensification and/or cropland expansion and compared against projected increase in grain demand for the two crops by year 2035. Yield gaps were substantially larger in maize versus rice and, in the case of rice, yield gap was larger in rainfed lowland versus irrigated conditions. At national level, average farmer yield for irrigated rice and maize represented 63% and 44% of their respective yield potential (9.5 and 13.6 Mg ha −1) while, in rainfed conditions, average farmer yield was 52% (rice) and 42% (maize) of respective water-limited yield potential (9.2 and 12.2 Mg ha −1). Scenario assessment indicated that Indonesia can produce an extra 24 and 16 million metric tons (MMT) of rice and maize annually (respective 31 and 67% increase relative to current production) and reach near self-sufficiency for both crops on existing cropland area by closing current yield gaps to a level equivalent to 80% of yield potential (irrigated crops) or 70% of water-limited yield potential (rainfed crops). Analysis of cropping-system yield gaps indicated an additional potential increase in annual rice (3 MMT) and maize (11 MMT) production derived from adoption of crop sequences with highest annual yield potential combined with yield gap closure, though this may be limited by extra input requirements and/or increasing risk. Findings from this study demonstrate the utility of yield-gap analysis to estimate extra crop production potential derived from intensification at both individual-crop and cropping-systems levels.

View PDFchevron_right
This document is currently being converted. Please check back in a few minutes.

References (66)

  1. Godfray HCJ, Beddington JR, Crute IR, Haddad L, Lawrence D, Muir JF, et al. Food security: the challenge of feeding 9 billion people. Science. 2010;327:812-8. doi: 10.1126/science.1185383.
  2. Foley JA, Ramankutty N, Brauman KA, Cassidy ES, Gerber JS, Johnston M, et al. Solutions for a cultivated planet. Nature. 2011;478:337-42. doi: 10.1038/nature10452.
  3. Suh S, Johnson JA, Tambjerg L, Sim S, Broeckx-Smith S, Reyes W, et al. Closing yield gap is crucial to avoid potential surge in global carbon emissions. Glob Environ Change. 2020;63:102100. doi: 10. 1016/j.gloenvcha.2020.102100.
  4. Bruinsma J. The resource outlook to 2050: by how much do land, water and crop yields need to increase by 2050? Feed World 2050 Proc. Tech. Meet. Experts Rome Italy 24-26 June 2009. Food and Agriculture Organization of the United Nations. FAO; 2009. p. 1-33.
  5. Hengsdijk H, Langeveld JWA. Yield trends and yield gap analysis of major crops in the world. Wageningen: Wettelijke Onderzoekstaken Natuur & Milieu; 2009.
  6. Byerlee D. Technical change, productivity, and sustainability in irrigated cropping systems of South Asia: emerging issues in the post-green revolution era. J Int Dev. 1992;4:477-96.
  7. Van Ittersum MK, Cassman KG, Grassini P, Wolf J, Tittonell P, Hochman Z. Yield gap analysis with local to global relevance -A review. Field Crops Res. 2013;143:4-17. doi: 10.1016/j.fcr.2012. 09.009.
  8. Evans LT, Fischer RA. Yield potentials: Its definition, measurement, and significance. Crop Sci. 1999;39:1544-51. doi: 10.2135/ cropsci1999.3961544x.
  9. Fischer RA, Byerlee D, Edmeades GO. Can technology deliver on the yield challenge to 2050. Expert meeting on "How to feed the world in 2050", Rome, 24-26 June 2009. Rome: FAOIO; 2009.
  10. Rattalino Edreira JI, Andrade JF, Cassman KG, van Ittersum MK, van Loon MP, Grassini P. Spatial frameworks for robust estimation of yield gaps. Nat Food. 2021;2:773-9. doi: 10.1038/s43016-021- 00365-y.
  11. Agus F, Andrade JF, Edreira JIR, Deng N, Purwantomo DK, Agustiani N, et al. Yield gaps in intensive rice-maize cropping sequences in the humid tropics of Indonesia. Field Crops Res. 2019;237:12-22. doi: 10.1016/j.fcr.2019.04.006.
  12. Yuan S, Stuart AM, Laborte AG, Rattalino Edreira JI, Dobermann A, Kien LVN, et al. Southeast Asia must narrow down the yield gap to continue to be a major rice bowl. Nat Food. 2022;3:217-26. doi: 10. 1038/s43016-022-00477-z.
  13. Fischer RA. Definitions and determination of crop yield, yield gaps, and of rates of change. Field Crops Res. 2015;182:9-18. doi: 10.1016/ j.fcr.2014.12.006.
  14. Fischer RA, Byerlee D, Edmeades GO. Crop yields and global food security: will yield increase continue to feed the world?. Canberra: Australian Centre for International Agricultural Research; 2014.
  15. BPN. Luas Lahan Baku Sawah Nasional Tahun 2019. Jakarta: Kementerian ATR/BPN; 2019.
  16. BPS. Proyeksi Penduduk Indonesia, 2010-2035. Jakarta: Badan Pusat Statistik; 2013.
  17. Ruminta H. Vulnerability assessment of climate on agriculture sector in the South Sumatra Province, Indonesia. Asian J Crop Sci. 2016;8:31-42. doi: 10.3923/ajcs.2016.31.42.
  18. Schneider P, Asch F. Rice production and food security in Asian Mega deltas -A review on characteristics, vulnerabilities and agricultural adaptation options to cope with climate change. J Agron Crop Sci. 2020;206:491-503. doi: 10.1111/jac.12415.
  19. Vanlauwe B, Coyne D, Gockowski J, Hauser S, Huising J, Masso C, et al. Sustainable intensification and the African smallholder farmer. Curr Opin Environ Sustain. 2014;8:15-22. doi: 10.1016/j. cosust.2014.06.001.
  20. Godfray HCJ, Garnett T. Food security and sustainable intensifica- tion. Philos Trans R Soc B Biol Sci. 2014;369:20120273. doi: 10.1098/ rstb.2012.0273.
  21. Kementerian Pertanian. Pedoman Umum PTT Padi Sawah. 3rd edn. Bogor: Pusat Penelitan dan Pengembangan Tanaman Pangan; 2015.
  22. Kementerian Pertanian. Petunjuk Teknis Budidaya Padi Jajar Legowo Super. 2nd edn. Jakarta: Badan Penelitian dan Pengembangan Pertanian; 2016.
  23. Sutrisna N, Sulaeman Y, Wiratno, Susanto B, Surdianto Y, Darojat, et al. Budidaya Padi Ramah Lingkungan. Bogor: IPB Press; 2022.
  24. Hossain M. Boosting rice production through narrowing of exploitable yield gap. SAARC J Agric. 2020;18:167-80. doi: 10.3329/ sja.v18i2.51117.
  25. BPS. Luas Panen dan Produksi Padi di Indonesia 2021 (Angka Tetap). Jakarta: Badan Pusat Statistik; 2022.
  26. Mohr ECJ, Van Baren FA, Schuylenborgh JV. Tropical Soils. A Comprehensive Study of Their Genesis. 3rd edn. The Hague, Netherlands: Van Hoeve; 1972.
  27. R Core Team. R: A language and environment for statistical com- puting; 2021.
  28. Ran Y, Chen H, Ruan D, Liu H, Wang S, Tang X, et al. Identification of factors affecting rice yield gap in southwest China: An experimental study. PloS One. 2018;13:e0206479. doi: 10.1371/journal.pone. 0206479.
  29. Tseng M-C, Roel Á, Macedo I, Marella M, Terra J, Zorrilla G, et al. Field-level factors for closing yield gaps in high-yielding rice sys- tems of Uruguay. Field Crops Res. 2021;264:108097.
  30. Maclean J, Hardy B, Hettel G. Rice Almanac. 4th edn. Los Banos, The Philippines: IRRI; 2013.
  31. Khanal AR, Regmi M. Financial constraints and production effi- ciency: A case from rice growers in drought prone areas of Indonesia. Agric Finance Rev. 2017;78(1):25-40. doi: 10.1108/AFR- 07-2016-0068.
  32. Debnath S, Mishra A, Mailapalli D, Raghuwanshi N, Sridhar V. Assessment of rice yield gap under a changing climate in India. J Water Clim Change. 2021;12:1245-67. doi: 10.2166/wcc.2020.086.
  33. Husnain ND, Syakir M. Teknologi pemupukan mendukung Jarwo Super. J Sumberd Lahan. 2016;10:1-10. doi: 10.21082/jsdl.v10n1. 2016.%25p.
  34. Saikia P, Baruah KK, Bhattacharya SS, Choudhury C. Organic based integrated nutrient management scheme enhances soil carbon storage in rainfed rice (Oryza sativa) cultivation. Soil Res. 2019;57:894-907. doi: 10.1071/SR17287.
  35. Silitonga TS. Pengelolaan dan pemanfaatan plasma nutfah padi di Indonesia. Bul Plasma Nutfah. 2004;10:56-71. doi: 10.21082/blpn. v10n2.2004.p56-71.
  36. Paiman, Ardiyanta, Ansar M, Effendy I, Sumbodo BT. Rice cultiva- tion of superior variety in swamps to increase food security in Indonesia. Rev Agric Sci. 2020;8:300-9. doi: 10.7831/ras.8.0_300.
  37. Ratmini NPS, Hendra H. Produktivitas varietas padi lahan rawa pasang surut pada berbagai tipe luapan air pasang. Pros. Semin. Nas. Lahan Suboptimal 2019 Plb. 4-5 Sept. 2019. Palembang: UNSRI Press; 2019. p. 559-66.
  38. Dianawati M, Sujitno E. Kajian berbagai varietas unggul terhadap serangan wereng batang cokelat dan produksi padi di lahan sawah Kabupaten Garut. Jawa Barat. Pros. Semin. Nas. Masy. Biodivers. Indones. Vol. 1. Jakarta: Masyarakat Biodiversitas Indonesia; 2015. p. 868-73. doi: 10.13057/psnmbi/m010437.
  39. Silva JV, Pede VO, Radanielson AM, Kodama W, Duarte A, Annalyn H, et al. Revisiting yield gaps and the scope for sustainable intensifi- cation for irrigated lowland rice in Southeast Asia. Agric Syst. 2022;198:103383. doi: 10.1016/j.agsy.2022.103383.
  40. Boling AA, Tuong TP, Keulen HV, Bouman BAM, Suganda H, Spiertz JHJ. Yield gap of rainfed rice in farmers' fields in Central Java, Indonesia. Agric Syst. 2010;103:307-15. doi: 10.1016/j.agsy. 2010.02.003.
  41. Lobell DB, Cassman KG, Field CB. Crop yield gaps: their importance, magnitudes, and causes. Annu Rev Environ Resour. 2009;34:179-204. doi: 10.1146/annurev.environ.041008.093740.
  42. Grassini P, van Bussel LG, Van Wart J, Wolf J, Claessens L, Yang H, et al. How good is good enough? Data requirements for reliable crop yield simulations and yield-gap analysis. Field Crops Res. 2015;177:49-63. doi: 10.1016/j.fcr.2015.03.004.
  43. Alam MM, Karim MR, Ladha J. Integrating best management practices for rice with farmers' crop management techniques: A potential option for minimizing rice yield gap. Field Crops Res. 2013;144:62-8. doi: 10.1016/j.fcr.2013.01.010.
  44. Ladha JK, Radanielson AM, Rutkoski JE, Buresh RJ, Dobermann A, Angeles O, et al. Steady agronomic and genetic interventions are essential for sustaining productivity in intensive rice cropping. Proc Natl Acad Sci. 2021;118:e2110807118. doi: 10.1073/pnas. 2110807118.
  45. Sulaeman Y, Maftu'ah E, Mukhlis M, Anwar K, Karolinoerita V, Wakhid N, et al. Tidal rice yield assessment in Central Kalimantan, Indonesia, under different cultural practices. Resources. 2022;11:116. doi: 10.3390/resources11120116.
  46. Erythrina E, Anshori A, Bora CY, Dewi DO, Lestari MS, Mustaha MA, et al. Assessing opportunities to increase yield and profit in rainfed lowland rice systems in Indonesia. Agronomy. 2021;11:777. doi: 10. 3390/agronomy11040777.
  47. Banayo NP, Rahon RE, Sta Cruz P, Kato Y. Fertilizer responsiveness of high-yielding drought-tolerant rice in rainfed lowlands. Plant Prod Sci. 2021;24:279-86. doi: 10.1080/1343943X.2020.1847668.
  48. Makarim AK. Bridging the rice yield gap in Indonesia. Bridg. Rice Yield Gap Asia-Pac. Reg. Bangkok: FAO; 2000. p. 112-21.
  49. Silva JV. Using yield gap analysis to give sustainable intensification local meaning. PhD Thesis. Wageningen: Wageningen University and Research; 2017.
  50. Hairani A, Noor M. Water management on peatland for food crop and horticulture production: research review in Kalimantan. IOP Conf. Ser. Earth Environ. Sci. Vol. 499. IOP Publishing; 2020. p. 012006. doi: 10.1088/1755-1315/499/1/012006.
  51. Widowati LR, Sukristiyonubowo. Dynamics of pH, ferrum and mangan, and phosphorus on newly opened paddy soil having high soil organic matter on rice growth. J Trop Soils. 2019;17:1-8. doi: 10. 5400/jts.2012.v17i1.1-8.
  52. Alwi M, Yusuf W, Fahmi A. Improving productivity of rice yield on tidal swampland using soil amendment. IOP Conf. Ser. Earth Environ. Sci. Vol. 648. IOP Publishing; 2021. p. 012141. doi: 10.1088/ 1755-1315/648/1/012141.
  53. Noor A, Lubis I, Ghulamahdi M, Ningsih R, Anwar K, Chozin M, et al. The response by selected rice genotypes to organic ameliorants in tidal swampland which is affected by Fe toxicity. Agron Res. 2022;20:1044-59. doi: 10.15159/AR.22.043.
  54. Franzluebbers AJ, Doraiswamy PC. Carbon sequestration and land degradation. Clim. Land Degrad. Berlin: Springer; 2007. p. 343-58. doi: 10.1007/978-3-540-72438-4_18.
  55. Lal R. Soil carbon sequestration to mitigate climate change. Geoderma. 2004;123:1-22. doi: 10.1016/j.geoderma.2004.01.032.
  56. Smith P, Soussana J-F, Angers D, Schipper L, Chenu C, Rasse DP, et al. How to measure, report and verify soil carbon change to realize the potential of soil carbon sequestration for atmospheric greenhouse gas removal. Glob Change Biol. 2020;26:219-41. doi: 10.1111/gcb.14815.
  57. Bhardwaj AK, Rajwar D, Mandal UK, Ahamad S, Kaphaliya B, Minhas PS, et al. Impact of carbon inputs on soil carbon fractio- nation, sequestration and biological responses under major nutrient management practices for rice-wheat cropping systems. Sci Rep. 2019;9:1-10. doi: 10.1038/s41598-019-45534-z.
  58. Anandakumar S, Bakhoum N, Chinnadurai C, Malarkodi M, Arulmozhiselvan K, Karthikeyan S, et al. Impact of long-term nutrient management on sequestration and dynamics of soil organic carbon in a semi-arid tropical Alfisol of India. Appl Soil Ecol. 2022;177:104549. doi: 10.1016/j.apsoil.2022.104549.
  59. Jat ML, Chakraborty D, Ladha JK, Parihar CM, Datta A, Mandal B, et al. Carbon sequestration potential, challenges, and strategies towards climate action in smallholder agricultural systems of South Asia. Crop Environ. 2022;1:86-101. doi: 10.1016/j.crope.2022.03.005.
  60. Snyder CS, Bruulsema TW, Jensen TL, Fixen PE. Review of green- house gas emissions from crop production systems and fertilizer management effects. Agric Ecosyst Environ. 2009;133:247-66. doi: 10.1016/j.agee.2009.04.021.
  61. Gupta Choudhury S, Yaduvanshi N, Chaudhari S, Sharma D, Sharma D, Nayak D, et al. Effect of nutrient management on soil organic carbon sequestration, fertility, and productivity under rice- wheat cropping system in semi-reclaimed sodic soils of North India. Environ Monit Assess. 2018;190:1-15. doi: 10.1007/s10661- 018-6486-9.
  62. Yang Z, Zhao N, Huang F, Lv Y. Long-term effects of different organic and inorganic fertilizer treatments on soil organic carbon sequestration and crop yields on the North China Plain. Soil Tillage Res. 2015;146:47-52. doi: 10.1016/j.still.2014.06.011.
  63. Tamilselvi S, Chinnadurai C, Ilamurugu K, Arulmozhiselvan K, Balachandar D. Effect of long-term nutrient managements on biological and biochemical properties of semi-arid tropical Alfisol during maize crop development stages. Ecol Indic. 2015;48:76-87. doi: 10.1016/j.ecolind.2014.08.001.
  64. Hidayat Y, Saleh Y, Waraiya M. Kelayakan usahatani padi varietas unggul baru melalui PTT di Kabupaten Halmahera Tengah. J Penelit Pertan Tanam Pangan. 2012;31:166-72. doi: 10.21082/jpptp.v31n3. 2012.p166-172.
  65. Raharjo B, Marpaung IS, Hutapea Y. Kajian kinerja alat tanam dan varietas unggul baru padi di lahan pasang surut Sumatera Selatan. J Pengkaj Dan Pengemb Teknol Pertan. 2013;16:191-201. doi: 10. 21082/jpptp.v16n3.2013.p%25p.
  66. Maryana YE, Suprihatin A, Raharjo B, Ratmini NPS. Increasing paddy productivity in tidal low lands of south Sumatra through the implementation of new superior varieties and amator. J Lahan Suboptimal. 2022;11:59-66. doi: 10.36706/jlso.11.1.2022.557.

Related topics

GeographyMathematicsArchaeologyEnvironmental ScienceMaterials ScienceEconomicsMacroeconomicsAgronomyAgricultural EconomicsBiologyAgricultureYield GapPaddy Field
580 California St., Suite 400
San Francisco, CA, 94104