Closing Indonesia’s Sugar Yield Gap: Reconstructing Farm-to-Mill Productivity from Historical Highs toward a Competitive, Digital, and Climate-Resilient Sugarcane System

Authors

  • Loso Judijanto IPOSS Jakarta

DOI:

https://doi.org/10.59890/ijaamr.v4i9.316

Keywords:

Indonesia, Sugarcane, Sugar Yield Gap, Sugar Productivity, Ratoon Management, Irrigation, Precision Agriculture, Milling Recovery, Smallholder Farming, Sugar Self-Sufficiency

Abstract

Indonesia’s sugar industry faces a persistent productivity gap between contemporary performance and the much higher yields historically reported for Java. This qualitative literature review synthesises recent peer-reviewed evidence published mainly during 2020–2026 to explain that gap through an integrated farm-to-mill perspective. Rather than equating productivity with cane tonnage, the review conceptualises realised sugar yield per hectare as the combined outcome of cane biomass yield, recoverable sucrose concentration, post-harvest quality retention and factory recovery. Evidence across agronomy, genetics, water and soil management, ratoon systems, crop protection, mechanisation, digital agriculture, logistics and farm institutions indicates that losses accumulate across the value chain. Key constraints include weak varietal adaptation, uneven planting-material quality, water stress, inefficient nutrient use, ratoon decline, disease pressure, machinery-induced compaction, delayed cut-to-crush times, variable milling performance, credit constraints and fragmented farmer–mill coordination. Remote sensing, machine learning, precision irrigation, controlled traffic, improved breeding and integrated nutrient management can raise productivity, but their effects depend on sequencing and institutional capacity. The review proposes an integrated transformation architecture in which foundational agronomy precedes operational integration, digitalization and frontier innovation. Sustainable gains in Indonesia’s sugar yield therefore require coordinated improvements across farms, logistics, mills and enabling institutions rather than a single technology or headline productivity target.

References

Arefin, M.S., Islam, M.A., Rahman, M.M., Alim, M.A., Hassan, S. et al. (2022) ‘Integrated nutrient management improves productivity and quality of sugarcane (Saccharum officinarum L.)’, Phyton—International Journal of Experimental Botany, 91(2), pp. 439–469. https://doi.org/10.32604/phyton.2022.017359.

Ariyanto, F., Ubaidillah, M. and Hartatik, S. (2023) ‘Yield component evaluation of mutated sugarcane at first and ratooning plantations’, Jurnal Agronomi Indonesia, 51, pp. 73–79. https://doi.org/10.24831/ija.v51i1.41860.

Bao, D., Zhou, J., Bhuiyan, S.A., Adhikari, P., Tuxworth, G., Ford, R. and Gao, Y. (2024) ‘Early detection of sugarcane smut and mosaic diseases via hyperspectral imaging and spectral-spatial attention deep neural networks’, Journal of Agriculture and Food Research, 18, 101369. https://doi.org/10.1016/j.jafr.2024.101369.

Barbosa, F.S., Coelho, R.D., Barros, T.H.S., Lizcano, J.V., Fraga Júnior, E.F. et al. (2024) ‘Sugarcane water productivity for bioethanol, sugar and biomass under deficit irrigation’, AgriEngineering, 6, pp. 1117–1132. https://doi.org/10.3390/agriengineering6020064.

Bhuiyan, S.A., Magarey, R.C., McNeil, M.D. and Aitken, K.S. (2021) ‘Sugarcane smut, caused by Sporisorium scitamineum, a major disease of sugarcane: A contemporary review’, Phytopathology, 111(11), pp. 1905–1917. https://doi.org/10.1094/PHYTO-05-21-0221-RVW.

Canata, T.F., Wei, M.C.F., Maldaner, L.F. and Molin, J.P. (2021) ‘Sugarcane yield mapping using high-resolution imagery data and machine learning technique’, Remote Sensing, 13(2), 232. https://doi.org/10.3390/rs13020232.

Chen, F., He, X., Liu, Q., Gao, F., Zeng, C. and Li, D. (2025) ‘Bio-organic fertilizer modulates the rhizosphere microbiome to enhance sugarcane growth and suppress smut disease’, Microorganisms, 13(11), 2563. https://doi.org/10.3390/microorganisms13112563.

Das, A. et al. (2023) ‘Machine learning model ensemble for predicting sugarcane yield through synergy of optical and SAR remote sensing’, Remote Sensing Applications: Society and Environment, 30, 100962. https://doi.org/10.1016/j.rsase.2023.100962.

Delmond, J.G., Guimarães Júnnyor, W.D.S., de Brito, M.F., Rossoni, D.F., Araujo-Junior, C.F., da Costa Severiano, E. and Severiano, E.C. (2024) ‘Which operation in mechanized sugarcane harvesting is most responsible for soil compaction?’, Geoderma, 448, 116979. https://doi.org/10.1016/j.geoderma.2024.116979.

Desalegn, B., Kebede, E. and Legesse, H. (2023) ‘Sugarcane productivity and sugar yield improvement: Selecting variety, nitrogen fertilizer rate, and bioregulator as a first-line treatment’, Heliyon, 9, e15520. https://doi.org/10.1016/j.heliyon.2023.e15520.

Dimov, D., Uhl, J.H., Löw, F. and Seboka, G.N. (2022) ‘Sugarcane yield estimation through remote sensing time series and phenology metrics’, Smart Agricultural Technology, 2, 100046. https://doi.org/10.1016/j.atech.2022.100046.

Directorate General of Estate Crops, Ministry of Agriculture of the Republic of Indonesia (2026) ‘Produksi Gula 2025 Capai 2,67 Juta Ton, Kementan Percepat Langkah Menuju Swasembada’, 10 February. Available at: https://ditjenbun.pertanian.go.id/produksi-gula-2025-capai-267-juta-ton-kementan-percepat-langkah-menuju-swasembada/ (Accessed: 17 September 2026).

Dlamini, N. and Zhou, M. (2022) ‘Soils and seasons effect on sugarcane ratoon yield’, Field Crops Research, 284, 108588. https://doi.org/10.1016/j.fcr.2022.108588.

Esteban, D.A.A., de Souza, Z.M., da Silva, R.B., de Souza Lima, E., Lovera, L.H. and de Oliveira, I.N. (2020) ‘Impact of permanent traffic lanes on the soil physical and mechanical properties in mechanized sugarcane fields with the use of automatic steering’, Geoderma, 362, 114097. https://doi.org/10.1016/j.geoderma.2019.114097.

Esteban, D.A.A., Souza, Z.M., Tormena, C.A., Gomes, M.G.S., Parra, J.A.S., Guimarães Júnnyor, W.S. and Moraes, M.T. (2024) ‘Risk assessment of soil compaction due to machinery traffic used in infield transportation of sugarcane during mechanized harvesting’, Soil & Tillage Research, 244, 106206. https://doi.org/10.1016/j.still.2024.106206.

Gasparotto, L., Rosa, J.M., Grassini, P. and Marin, F.R. (2022) ‘Developing an operational framework to diagnose yield gaps in commercial sugarcane mills’, Field Crops Research, 278, 108433. https://doi.org/10.1016/j.fcr.2022.108433.

Guhan, V., Annadurai, K., Easwaran, S., Marimuthu, M., Balu, D., Vigneswaran, S. et al. (2024) ‘Assessing the impact of climate change on water requirement and yield of sugarcane over different agro-climatic zones of Tamil Nadu’, Scientific Reports, 14, 8239. https://doi.org/10.1038/s41598-024-58771-8.

Jimenez, K.J., Rolim, M.M., Gomes, I.F., de Lima, R.P., Berrío, L.L.A. and Ortiz, P.F.S. (2021) ‘Numerical analysis applied to the study of soil stress and compaction due to mechanised sugarcane harvest’, Soil & Tillage Research, 206, 104847. https://doi.org/10.1016/j.still.2020.104847.

Khan, A., Jiang, H., Bu, J., Adnan, M., Gillani, S.W. and Zhang, M. (2022) ‘An insight to rhizosphere bacterial community composition and structure of consecutive winter-initiated sugarcane ratoon crop in Southern China’, BMC Plant Biology, 22, 74. https://doi.org/10.1186/s12870-022-03463-6.

Khonghintaisong, J., Onkaeo, A., Songsri, P. and Jongrungklang, N. (2024) ‘Water use efficiency characteristics and their contributions to yield in diverse sugarcane genotypes with varying drought resistance levels under different field irrigation conditions’, Agriculture, 14(11), 1952. https://doi.org/10.3390/agriculture14111952.

Krishnapriya, V., Manimekalai, R., Gomathi, R., Duong, V.H., Arunkumar, R. et al. (2026) ‘Strategic considerations for nutrient use efficiency in sugarcane: Physiological, molecular and genetic perspectives’, Plant Science, 364, 112940. https://doi.org/10.1016/j.plantsci.2025.112940.

Lu, G., Liu, P., Wu, Q., Zhang, S., Zhao, P., Zhang, Y. and Que, Y. (2024) ‘Sugarcane breeding: A fantastic past and promising future driven by technology and methods’, Frontiers in Plant Science, 15, 1375934. https://doi.org/10.3389/fpls.2024.1375934.

Luciano, A.C.S., Picoli, M.C.A., Duft, D.G., Rocha, J.V., Leal, M.R.L.V. and le Maire, G. (2021) ‘Empirical model for forecasting sugarcane yield on a local scale in Brazil using Landsat imagery and random forest algorithm’, Computers and Electronics in Agriculture, 184, 106063. https://doi.org/10.1016/j.compag.2021.106063.

Luz, F.B., Gonzaga, L.C., Castioni, G.A.F., Lima, R.P., Carvalho, J.L.N. and Cherubin, M.R. (2023) ‘Controlled traffic farming maintains soil physical functionality in sugarcane fields’, Geoderma, 432, 116427. https://doi.org/10.1016/j.geoderma.2023.116427.

Maharani, I., Kusnadi, N. and Fariyanti, A. (2024) ‘The impact of credit constraint on productivity and technical efficiency of sugarcane in Indonesia’, Jurnal Manajemen dan Agribisnis, 21(1), p. 35. https://doi.org/10.17358/jma.21.1.35.

Mahasuweerachai, P. and Suksawat, J. (2022) ‘Incentives for mechanized cane harvesting in Thailand: A choice experiment’, Journal of Asian Economics, 78, 101434. https://doi.org/10.1016/j.asieco.2021.101434.

Mehdi, F., Cao, Z., Zhang, S., Gan, Y., Cai, W., Peng, L., Wu, Y., Wang, W. and Yang, B. (2024) ‘Factors affecting the production of sugarcane yield and sucrose accumulation: Suggested potential biological solutions’, Frontiers in Plant Science, 15, 1374228. https://doi.org/10.3389/fpls.2024.1374228.

Misra, V., Mall, A.K., Solomon, S. and Ansari, M.I. (2022) ‘Post-harvest biology and recent advances of storage technologies in sugarcane’, Biotechnology Reports, 33, e00705. https://doi.org/10.1016/j.btre.2022.e00705.

Mohanraj, K., Hemaprabha, G. and Vasantha, S. (2021) ‘Biomass yield, dry matter partitioning and physiology of commercial and Erianthus-introgressed sugarcane clones under contrasting water regimes’, Agricultural Water Management, 255, 107035. https://doi.org/10.1016/j.agwat.2021.107035.

Msomba, B.H., Ndaki, P.M. and Joseph, C.O. (2024) ‘Sugarcane sustainability in a changing climate: A systematic review on pests, diseases, and adaptive strategies’, Frontiers in Agronomy, 6, 1423233. https://doi.org/10.3389/fagro.2024.1423233.

Natarajan, S., Basnayake, J., Lakshmanan, P. and Fukai, S. (2020) ‘Limited contribution of water availability in genotype-by-environment interaction in sugarcane yield and yield components’, Journal of Agronomy and Crop Science, 206. https://doi.org/10.1111/jac.12407.

Natarajan, S., Basnayake, J., Lakshmanan, P. and Fukai, S. (2021) ‘Genotypic variation in intrinsic transpiration efficiency correlates with sugarcane yield under rainfed and irrigated field conditions’, Physiologia Plantarum, 172(2), pp. 976–989. https://doi.org/10.1111/ppl.13221.

Oliveira, B.G., Lourenço, K.S., Carvalho, J.L.N., Gonzaga, L.C., Teixeira, M.C., Tamara, A.F., Soares, J.R. and Cantarella, H. (2023) ‘New trends in sugarcane fertilization: Implications for NH3 volatilization, N2O emissions and crop yields’, Journal of Environmental Management, 342, 118233. https://doi.org/10.1016/j.jenvman.2023.118233.

Paul, J. and Criado, A.R. (2020) ‘The art of writing literature review: What do we know and what do we need to know?’, International Business Review, 29(4), 101717. https://doi.org/10.1016/j.ibusrev.2020.101717.

Qin, N., Lu, Q., Fu, G., Wang, J., Fei, K. and Gao, L. (2023) ‘Assessing the drought impact on sugarcane yield based on crop water requirements and standardized precipitation evapotranspiration index’, Agricultural Water Management, 275, 108037. https://doi.org/10.1016/j.agwat.2022.108037.

Ridwan, A.F., Purwono and Widodo, W.D. (2022) ‘Growth and yield of sugarcane first ratoon on residual of filter cake and residual of inorganic fertilizer’, Jurnal Agronomi Indonesia, 50(3), pp. 357–364. https://doi.org/10.24831/jai.v50i3.41761.

Rosidah, A., Irham, Masyhuri and Perwitasari, H. (2023) ‘Sugarcane production efficiency: A case study on PTPN X partner farmers’, Jurnal Manajemen dan Agribisnis, 20(1), p. 56. https://doi.org/10.17358/jma.20.1.56.

Santosa, A., Rahayu, E.S., Sutrisno, J. and Kusnandar, K. (2024) ‘Technical efficiency of sugarcane farming in East Java, Indonesia: A bootstrap data envelopment analysis’, Open Agriculture, 9(1), 20220378. https://doi.org/10.1515/opag-2022-0378.

Shailesh, J., Singels, A., Hoffman, N. et al. (2024) ‘Aerial phenotyping for sugarcane yield and drought tolerance’, Field Crops Research, 308, 109275. https://doi.org/10.1016/j.fcr.2024.109275.

Shendryk, Y., Davy, R. and Thorburn, P.J. (2021) ‘Integrating satellite imagery and environmental data to predict field-level cane and sugar yields in Australia using machine learning’, Field Crops Research, 260, 107984. https://doi.org/10.1016/j.fcr.2020.107984.

Shukla, S.K., Jaiswal, V.P., Sharma, L., Tiwari, R., Pathak, A.D., Gaur, A., Awasthi, S.K. and Srivastava, A. (2022) ‘Trash management and Trichoderma harzianum influencing photosynthesis, soil carbon sequestration, and growth and yield of sugarcane ratoon in subtropical India’, European Journal of Agronomy, 141, 126631. https://doi.org/10.1016/j.eja.2022.126631.

Som-ard, J., Immitzer, M., Vuolo, F. et al. (2024a) ‘Sugarcane yield estimation in Thailand at multiple scales using the integration of UAV and Sentinel-2 imagery’, Precision Agriculture, 25, pp. 1581–1608. https://doi.org/10.1007/s11119-024-10124-1.

Som-ard, J., Suwanlee, S.R., Pinasu, D., Keawsomsee, S., Kasa, K., Seesanhao, N., Ninsawat, S., Borgogno-Mondino, E. and Sarvia, F. (2024b) ‘Evaluating sugarcane yield estimation in Thailand using multi-temporal Sentinel-2 and Landsat data together with machine-learning algorithms’, Land, 13(9), 1481. https://doi.org/10.3390/land13091481.

Tegegn, D.A. and Dhont, F. (2023) ‘The downhill journey of the Java sugar economy in the Netherlands Indies (later Indonesia) from the late 19th century to the mid-20th century’, Cogent Arts & Humanities, 10(1), 2220213. https://doi.org/10.1080/23311983.2023.2220213.

Teixeira, E.S., Rangel, S., Florentino, H.O. and de Araujo, S.A. (2023) ‘A review of mathematical optimization models applied to the sugarcane supply chain’, International Transactions in Operational Research, 30(4), pp. 1755–1788. https://doi.org/10.1111/itor.13056.

Tischler, A.L., Jeronimo, E.M., Lúcio, A.D., Sari, B.G., Melo, P.J., Boesso, F.F., Diel, M.I. and Tartaglia, F.L. (2021) ‘Sugarcane harvest time for processing and technological quality of brown sugar’, Pesquisa Agropecuária Brasileira, 56, e02435. https://doi.org/10.1590/S1678-3921.pab2021.v56.26973.

Verma, A.K., Garg, P.K., Prasad, K.S.H. and Dadhwal, V.K. (2023) ‘Variety-specific sugarcane yield simulations and climate change impacts on sugarcane yield using DSSAT-CSM-CANEGRO model’, Agricultural Water Management, 275, 108034. https://doi.org/10.1016/j.agwat.2022.108034.

Wang, X., Feng, Y., Yu, L., Shu, Y., Tan, F., Gou, Y., Luo, S., Yang, W., Li, Z. and Wang, J. (2020) ‘Sugarcane/soybean intercropping with reduced nitrogen input improves crop productivity and reduces carbon footprint in China’, Science of the Total Environment, 719, 137517. https://doi.org/10.1016/j.scitotenv.2020.137517.

Yang, L., Zhou, Y., Meng, B., Zhan, J., Xi, M., Deng, Y., Wu, W., Lakshmanan, P., Chen, X. and Zhang, F. (2024) ‘High sugarcane yield and large reduction in reactive nitrogen loss can be achieved by lowering nitrogen input’, Agriculture, Ecosystems & Environment, 369, 109032. https://doi.org/10.1016/j.agee.2024.109032.

Zhao, Y., Liu, J., Huang, H., Zan, F., Zhao, P., Zhao, J., Deng, J. and Wu, C. (2022) ‘Genetic improvement of sugarcane (Saccharum spp.) contributed to high sucrose content in China based on an analysis of newly developed varieties’, Agriculture, 12(11), 1789. https://doi.org/10.3390/agriculture12111789.

Zhu, L., Liu, X., Wang, Z. and Tian, L. (2023) ‘High-precision sugarcane yield prediction by integrating 10-m Sentinel-1 VOD and Sentinel-2 GRVI indexes’, European Journal of Agronomy, 149, 126889. https://doi.org/10.1016/j.eja.2023.126889.

Zhu, S., Liang, P., Yang, L., Wei, B., Han, S., Wu, M., He, X., Zeng, W., He, Z., Xiao, J., Li, S. and Li, Z. (2025) ‘Effects of biochar-based fertilizers on Fenlong-ridging soil physical properties, nutrient activation, enzyme activity, bacterial diversity, and sugarcane yield’, Agronomy, 15(7), 1594. https://doi.org/10.3390/agronomy15071594.

Published

2026-10-13