IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v13y2023i2p309-d1048569.html
   My bibliography  Save this article

Response of Maize Yield and Nutrient Uptake to Indigenous Organic Fertilizer from Corn Cobs

Author

Listed:
  • Maria Theresia Sri Budiastuti

    (Department of Agrotechnology, Faculty of Agriculture, Sebelas Maret University, Surakarta 57126, Indonesia)

  • Djoko Purnomo

    (Department of Agrotechnology, Faculty of Agriculture, Sebelas Maret University, Surakarta 57126, Indonesia)

  • Bambang Pujiasmanto

    (Department of Agrotechnology, Faculty of Agriculture, Sebelas Maret University, Surakarta 57126, Indonesia)

  • Desy Setyaningrum

    (Diploma in Agribusiness, Vocational School, Sebelas Maret University, Surakarta 57126, Indonesia)

Abstract

Indonesia’s corn harvest area is decreasing so that corn production is also decreasing. The use of suboptimal land can be done to increase the harvested corn area by adding nutrients with organic fertilizers. One of the organic fertilizer ingredients is corn cob waste. The aim of the study was to examine the role of corn cob fertilizer on the growth, yield and nutrient uptake of corn. The study used a completely randomized block design with one fertilization factor with six levels, namely chemical fertilizers and corn cob organic fertilizer at a dose of 2.5, 5, 7.5, 10 or 12.5 tons/ha. Corn cob organic fertilizer has met the standard as an organic fertilizer with an organic C content of 62.21% and organic matter of 85.71%, ranking it in the high category. The total nitrogen is 1.44%, total phosphate is 1.43% and total potassium is 2.17%. Corn cob organic fertilizer had an effect on the leaf area index, root length, levels of chlorophyll a and chlorophyll b, weight of 100 seeds, cob diameter and phosphate uptake. Doses of 12.5 tons/ha produced the highest changes in chlorophyll a and b, root length and phosphate uptake. Phosphate and potassium uptake correlated with plant biomass and root length. Therefore, the results of the present study suggest that corn cob organic fertilizer is able to support the growth, yield and nutrient uptake of corn in sub-optimum land. Several gaps and research priorities in soil fertility have been identified, which need to be addressed in the future.

Suggested Citation

  • Maria Theresia Sri Budiastuti & Djoko Purnomo & Bambang Pujiasmanto & Desy Setyaningrum, 2023. "Response of Maize Yield and Nutrient Uptake to Indigenous Organic Fertilizer from Corn Cobs," Agriculture, MDPI, vol. 13(2), pages 1-11, January.
  • Handle: RePEc:gam:jagris:v:13:y:2023:i:2:p:309-:d:1048569
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/13/2/309/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2077-0472/13/2/309/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Li, Yibo & Song, He & Zhou, Li & Xu, Zhenzhu & Zhou, Guangsheng, 2019. "Tracking chlorophyll fluorescence as an indicator of drought and rewatering across the entire leaf lifespan in a maize field," Agricultural Water Management, Elsevier, vol. 211(C), pages 190-201.
    2. Zhang, Wentong & Xiong, Yunwu & Li, Yaping & Qiu, Yichao & Huang, Guanhua, 2022. "Effects of organic amendment incorporation on maize (Zea mays L.) growth, yield and water-fertilizer productivity under arid conditions," Agricultural Water Management, Elsevier, vol. 269(C).
    3. Anna Jama-Rodzeńska & Piotr Chohura & Bernard Gałka & Anna Szuba-Trznadel & Agnieszka Falkiewicz & Monika Białkowska, 2022. "Effect of Different Doses of Phosgreen Fertilization on Chlorophyll, K, and Ca Content in Butterhead Lettuce ( Lactuca sativa L.) Grown in Peat Substrate," Agriculture, MDPI, vol. 12(6), pages 1-11, May.
    4. Shao, Guomin & Han, Wenting & Zhang, Huihui & Liu, Shouyang & Wang, Yi & Zhang, Liyuan & Cui, Xin, 2021. "Mapping maize crop coefficient Kc using random forest algorithm based on leaf area index and UAV-based multispectral vegetation indices," Agricultural Water Management, Elsevier, vol. 252(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maria Roulia, 2024. "Sustainable Utilization of Humic Substances and Organic Waste in Green Agriculture," Agriculture, MDPI, vol. 14(1), pages 1-4, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rozenstein, Offer & Fine, Lior & Malachy, Nitzan & Richard, Antoine & Pradalier, Cedric & Tanny, Josef, 2023. "Data-driven estimation of actual evapotranspiration to support irrigation management: Testing two novel methods based on an unoccupied aerial vehicle and an artificial neural network," Agricultural Water Management, Elsevier, vol. 283(C).
    2. Song, Xingyang & Zhou, Guangsheng & He, Qijing & Zhou, Huailin, 2020. "Stomatal limitations to photosynthesis and their critical Water conditions in different growth stages of maize under water stress," Agricultural Water Management, Elsevier, vol. 241(C).
    3. Qian Cheng & Honggang Xu & Shuaipeng Fei & Zongpeng Li & Zhen Chen, 2022. "Estimation of Maize LAI Using Ensemble Learning and UAV Multispectral Imagery under Different Water and Fertilizer Treatments," Agriculture, MDPI, vol. 12(8), pages 1-21, August.
    4. Cai, Fu & Zhang, Yushu & Mi, Na & Ming, Huiqing & Zhang, Shujie & Zhang, Hui & Zhao, Xianli, 2020. "Maize (Zea mays L.) physiological responses to drought and rewatering, and the associations with water stress degree," Agricultural Water Management, Elsevier, vol. 241(C).
    5. Shao, Guomin & Han, Wenting & Zhang, Huihui & Zhang, Liyuan & Wang, Yi & Zhang, Yu, 2023. "Prediction of maize crop coefficient from UAV multisensor remote sensing using machine learning methods," Agricultural Water Management, Elsevier, vol. 276(C).
    6. Guo, Jinjin & Fan, Junliang & Xiang, Youzhen & Zhang, Fucang & Yan, Shicheng & Zhang, Xueyan & Zheng, Jing & Hou, Xianghao & Tang, Zijun & Li, Zhijun, 2022. "Maize leaf functional responses to blending urea and slow-release nitrogen fertilizer under various drip irrigation regimes," Agricultural Water Management, Elsevier, vol. 262(C).
    7. Duan, Chenxiao & Li, Jiabei & Zhang, Binbin & Wu, Shufang & Fan, Junliang & Feng, Hao & He, Jianqiang & Siddique, Kadambot H.M., 2023. "Effect of bio-organic fertilizer derived from agricultural waste resources on soil properties and winter wheat (Triticum aestivum L.) yield in semi-humid drought-prone regions," Agricultural Water Management, Elsevier, vol. 289(C).
    8. Zhang, Yu & Han, Wenting & Zhang, Huihui & Niu, Xiaotao & Shao, Guomin, 2023. "Evaluating maize evapotranspiration using high-resolution UAV-based imagery and FAO-56 dual crop coefficient approach," Agricultural Water Management, Elsevier, vol. 275(C).
    9. Du, Ruiqi & Xiang, Youzhen & Zhang, Fucang & Chen, Junying & Shi, Hongzhao & Liu, Hao & Yang, Xiaofei & Yang, Ning & Yang, Xizhen & Wang, Tianyang & Wu, Yuxiao, 2024. "Combing transfer learning with the OPtical TRApezoid Model (OPTRAM) to diagnosis small-scale field soil moisture from hyperspectral data," Agricultural Water Management, Elsevier, vol. 298(C).
    10. Aliloo, Jamileh & Abbasi, Enayat & Karamidehkordi, Esmail & Ghanbari Parmehr, Ebadat & Canavari, Maurizio, 2024. "Dos and Don'ts of using drone technology in the crop fields," Technology in Society, Elsevier, vol. 76(C).
    11. Bounajra, Afaf & Guemmat, Kamal El & Mansouri, Khalifa & Akef, Fatiha, 2024. "Towards efficient irrigation management at field scale using new technologies: A systematic literature review," Agricultural Water Management, Elsevier, vol. 295(C).
    12. Yulin Shen & Benoît Mercatoris & Zhen Cao & Paul Kwan & Leifeng Guo & Hongxun Yao & Qian Cheng, 2022. "Improving Wheat Yield Prediction Accuracy Using LSTM-RF Framework Based on UAV Thermal Infrared and Multispectral Imagery," Agriculture, MDPI, vol. 12(6), pages 1-13, June.
    13. Yun Yang & Yun Long & Shiwei Li & Xiaohong Liu, 2023. "Straw Return Decomposition Characteristics and Effects on Soil Nutrients and Maize Yield," Agriculture, MDPI, vol. 13(8), pages 1-12, August.
    14. Li, Yupeng & Gu, Xiaobo & Li, Yuannong & Fang, Heng & Chen, Pengpeng, 2023. "Ridge-furrow mulching combined with appropriate nitrogen rate for enhancing photosynthetic efficiency, yield and water use efficiency of summer maize in a semi-arid region of China," Agricultural Water Management, Elsevier, vol. 287(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:13:y:2023:i:2:p:309-:d:1048569. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.