Open Journal Systems

Embracing smart irrigation management techniques empowers growers to irrigate with greater efficiency, thereby promoting sustainable agricultural production. In this context, growers often rely on crop evapotranspiration (ETc) as a key factor in making informed irrigation decisions, underscoring the significance of accurately determining and spatially mapping crop water status. Technological progress, exemplified by the emergence of unmanned aerial vehicles (UAVs), has brought about a revolutionary shift in agricultural monitoring. UAV platforms can capture high-resolution images with centimeter-level spatial accuracy and offer higher temporal coverage compared to satellite imagery. Considering these advancements, this study introduces a robust method for classifying water stress in cotton using a compact UAV platform and convolutional neural networks (CNN). The experiment was conducted at the USDA-ARS Cropping Systems Research Laboratory (CSRL) in Lubbock, Texas, where the cotton field was divided into 12 drip zones. The study included three replications to evaluate four irrigation treatments: “rainfed”, “full irrigation”, “percent deficit of full irrigation”, and “time delay of full irrigation”. The results demonstrated that the CNN model successfully classified the cotton water stress using the UAV-based RGB image, achieving an overall best prediction accuracy of approximately 91%. By segmenting the original cotton images into separate canopy and soil areas using morphological image processing methods, the authors also isolated and analyzed the individual contributions of these components to cotton water stress. Additionally, a random forest classifier revealed the relative importance of different image features in the classification process through feature importance analysis. These findings highlighted the state-of-the-art performance of the proposed system in cotton water stress classification and provided valuable insights into the key image features contributing to accurate classification. The authors concluded that integrating UAV-based RGB imagery and CNN models had great potential for assessing water stress in cotton.

A new approach to measure spatial variability of soil parameters and field technique to test-value specific fertilizer

Information on the distribution of soil properties is important to know the status of nutrients in the soils based on which fertilizer nutrients are recommended. Given the variability of nutrients in the soils, making a site-specific fertilizer recommendation seems to be a compelling work. To determine the spatial variability of soil nutrients and to make judicious and precise fertilizer recommendations, new measures are designed with this study. These measures are tested against the soil samples (n = 43) for total nitrogen (N), organic matter (OM), phosphorus (P2O5), and potassium (K2O) in the study area. The descriptive statistical analysis indicated an average of low nitrogen and organic matter, while phosphorus was found to be very high and the level of potassium was high. The spread of nutrients across the data sets, however, included low, medium, high, and very high levels of ratings. The Deviation Square Index was developed and applied for the variability measurement and found that the largest variation was with phosphorus distribution, followed by potassium, nitrogen, and organic matter. The coefficient of variation (CV%) analysis also exhibited similar trends in nutrient distributions. Nitrogen was the main determinant explaining the variations in rice yield, while phosphorus and potash were negatively related to the yield. An index of fertilizer nutrient recommendation called Test-Value Specific Dose (TVSD) was developed and used to calculate the nutrient recommendation for each sampled location. This new method gave easy and more accurate doses of fertilizer over the blanket recommendation to fit the variations across the soil samples.

Efficacy of different irrigation methods in saving water and ameliorating pollution in paddy field: Take Pinghu as an example

Yi Xu, Yongxiang Wu, Gaoxu Wang, Pei Liu, Ting Guo

Article ID: 2027
Vol 1, Issue 1, 2020

DOI: https://doi.org/10.54517/ama.v1i1.2027
VIEWS - 4224 (Abstract)

Download PDF

Abstract

Objective: Improving water use efficiency and ameliorating pollution is a challenge facing agriculture, and this paper aims to present an experimental study on the efficacy of different irrigation methods in saving water and reducing pollution in paddy fields in an attempt to provide suitable management for paddy fields in plain regions. Method: We examined three irrigation methods: flooding irrigation, shallow-water irrigation, and rain-collecting irrigation in Pinghu, Zhejiang province. For each irrigation, we measured TN, TP, NH₄⁺-H, NH₃-N, and COD in both irrigation water and drainage water. Result: Compared with flooding and shallow-water irrigation, rain-collecting irrigation reduced the amount of irrigation water by 67.4% and 43.4%, TN loss by 86.9% and 90.7%, emissions of NH₄⁺-H by 96.7% and 98.3%, and COD emissions by 61.5% and 62.5%, respectively. The difference in change of TP and NH₃-N between all three irrigation methods was not significant. Conclusion: For the areas we studied, rain-collecting irrigation is most effective in saving water and reducing pollution.

Keywords

agroecology; traditional agriculture; resilience; adaptation; climate change

References

1. 2016 Jiaxing City Water Resources Bulletin (Chinese). Available online: https://zjjcmspublic.oss-cn-hangzhou-zwynet-d01-a.internet.cloud.zj.gov.cn/jcms_files/jcms1/web3028/site/attach/0/2a6fd7a8a00648c390054ba0dbe0e30b.pdf (accessed on 6 March 2020).

2. Yang B, Chen X, Zhang Y, et al. The application analysis of the application of rice waters in Taihu Basin (Chinese). China Water Conservancy 2018; 7: 55–57.

3. Ye S, Wu Z, Sun Z, et al. Strengthen agricultural water saving management and reduce rural surface source pollution (Chinese). China Water Conservancy 2012; 11: 27–29.

4. Mao Z. Rice water-saving irrigation plays an important role in water saving, increasing yield and preventing pollution (Chinese). China Water Resources 2009; 21: 11–12.

5. Wan Y. Research on rice fields based on water-saving irrigation mode (Chinese). China Rural Water Conservancy and Hydropower 2012; 5: 42–44.

6. Xu J. Study on the Physiological Growth Response Mechanism of Water-Saving Controlled Irrigated Rice (Chinese) [PhD thesis]. Hohai University; 2007.

7. Tao M, Yu S, Ye X. The impact of water level regulation on the farmland on rice root system (Chinese). China Rural Water and Hydropower 2014; 10: 73–75.

8. Lv L, Feng C, Cui Y. The water utilization efficiency of different water-saving irrigation modes of rice: Take Jingmen and Guilin as an example (Chinese). Water Saving Irrigation 2011; 3: 15–17.

9. Mao Z. Water-saving irrigation of rice and its impact on the environment (Chinese). Engineering 2002; 7: 8–16.

10. Shao D, Qiao X, Liu H, et al. Different irrigation and row regulatory modes under the mode of water loss (Chinese). Wuhan University Study Journal (Engineering Edition) 2010; 3(4): 409–413.

11. Zhou J, Su B, Huang N, et al. The study of rice farmers pollution in different irrigation modes (Chinese). Environmental Science 2016; 37(3): 963–969.

12. Xiao W, Jia H, Qiu X, et al. The impact of rice irrigation of rice on rice fields on rice fields (Chinese). Journal of Irrigation and Drainage 2017; 36(11): 36–40.

13. Chi J, Zheng E, Ke H, et al. Zhejiang Province Single-quarter rice-saving irrigation test research (Chinese). Journal of Irrigation and Drainage 2007; 26(3): 23–26.

14. Jiang P, Yuan Y, Zhu R, et al., Water-saving irrigation conditions The characteristics of rice field runoff and leak loss features (Chinese). Journal of Agricultural Environment Sciences 2013; 32(8): 1592–1596.

15. Chen Z, Guo X, Yao J. The water-saving effect of water storage and irrigation of rice (Chinese). Journal of Hohai University (Natural Science Edition) 2011; 39(4): 426–430.

16. Guo Y, Guo X, Fan J, et al. Effects of water storage and irrigation control mode on rice yield and water production efficiency (Chinese). Journal of Irrigation and Drainage 2010; 29(3): 61–63.

17. Guo X, Wang F, Wang Z, et al. Effects of different irrigation modes on chlorophyll fluorescence characteristics and yield of rice after heading (Chinese). Journal of Irrigation and Drainage 2017; 36(3): 1–6.

18. Guo X, Yuan J, Guo F, et al. Rice water storage-controlling technology initial exploration (Chinese). Transactions of the Chinese Society of Agricultural Engineering 2009; 25(4): 70–73.

19. Xie S, Sun X, Zou D, et al. Research on water-saving and emission reduction effects of rice fertilizer management technology in the northern cold area (Chinese). Water Saving Irrigation 2018; 5: 44–47.

20. Yu S, Li C, Gao S, et al. Effects of controlled irrigation and drainage mode on water saving, high yield, emission reduction and pollution control in rice (Chinese). Transactions of the Chinese Society of Agricultural Engineering 2018; 34(7):128–136.

21. Ye Y, Liang X, Zhou K, et al. Effects of water-saving irrigation and controlled release fertilizer application on soil nitrogen leakage and loss in Taihu Lake, China (Chinese). Acta Scientiae Circumstatiae 2015; 35(1):270–279.

22. Li R, Xia Y, Wu A, et al. Water saving irrigation and nitrogen leaching of rice in Taihu Lake area (Chinese). Journal of Hohai University (Natural Science Edition) 2001; 29(2): 21–25.

23. Yang R, Tong J, Li J, et al. Numerical simulation and leaching rule of surface runoff nitrogen loss in paddy field (Chinese). Journal of Irrigation and Drainage 2018; 37(1):63–69.

24. Zheng S, Chen X, Zhang Z. Effects of thin dew irrigation on water quality of rice (Chinese). China Rural Water Conservancy and Hydropower 2005(3): 7–8.

25. Gao H, Peng S, Mao Z, et al. Regularities of nitrogen and phosphorus loss in paddy drainage under different irrigation and drainage patterns (Chinese). Water Saving Irrigation 2009; 9: 1–3.

26. Gao S, Yu S, Wang M, et al. Effects of controlled irrigation on water saving and nitrogen and phosphorus emission reduction in paddy fields under alternating drought and flood (Chinese). Transactions of the Chinese Society of Agricultural Engineering 2017; 33(5): 122–128.

27. Ye Y, Liang X, Li L, et al. Effects of different water and fertilizer management on phosphorus runoff and leakage loss in rice fields in Taihu Lake Basin (Chinese). Acta Scientiae Circumstatiae 2015; 35(4): 1125–1135.

Refbacks

There are currently no refbacks.

This work is licensed under a Creative Commons Attribution 4.0 International License.

This site is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Editor-in-Chief

Prof. Zhengjun Qiu

Zhejiang University, China

Honorary Editor-in-Chief

Cheng Sun

Academician of World Academy of Productivity Science; Executive Chairman, World Confederation of Productivity Science China Chapter, China

Processing Speed (2023)

- - - ＜7 days: submission to initial review decision;
  - - 56 days: received to online

News & Announcements

2024-09-11

Smart agriculture is becoming a reality!

Modern agricultural technology is evolving rapidly, with scientists collaborating with leading agricultural enterprises to develop intelligent management practices. These practices utilize advanced systems that provide tailored fertilization and treatment options for large-scale land management.

2024-05-01

Notice on the prohibition of using AI techniques to generate papers!

This journal values human initiative and intelligence, and the employment of AI technologies to write papers that replace the human mind is expressly prohibited. When there is a suspicious submission that uses AI tools to quickly piece together and generate research results, the editorial board of the journal will reject the article, and all journals under the publisher's umbrella will prohibit all authors from submitting their articles.

Readers and authors are asked to exercise caution and strictly adhere to the journal's policy regarding the usage of Artificial Intelligence Generated Content (AIGC) tools.

2024-01-14

We are recruiting Editorial Team Members

Advances in Modern Agriculture (AMA) is looking for members of the Editorial Board.

2023-12-28

Notice on the change of publication frequency

The publication frequency of Advances in Modern Agriculture is Quarterly since 2024, that means the journal will publish 4 issues per year from 2024 onwards.

More Announcements...

Journal Center

Asia Pacific Academy of Science Pte. Ltd. (APACSCI) specializes in international journal publishing. APACSCI adopts the open access publishing model and provides an important communication bridge for academic groups whose interest fields include engineering, technology, medicine, computer, mathematics, agriculture and forestry, and environment.

more

Article Tools

Indexing metadata

How to cite item

Review policy