Article
Engineering, Environmental
Lena Abu-Ali, Scott C. Maguffin, Jai S. Rohila, Anna M. McClung, Matthew C. Reid
Summary: Rice is a staple food globally, but traditional cultivation methods lead to arsenic accumulation in rice grains. Alternate wetting and drying (AWD) is advocated for reduced arsenic levels, water savings, and decreased methane emissions. However, the effects of AWD on micronutrient element concentrations in rice grains are unclear. This study found that AWD tends to increase cationic element concentrations while decreasing oxyanionic element concentrations. The decrease in total arsenic in rice grains under AWD is mainly driven by changes in dimethylarsinic concentrations. The effects of AWD on grain composition were more significant in 2017 compared to 2018, possibly due to differences in dry-down timing during rice development. Additionally, interannual variability in grain elemental composition was observed in continuously-flooded fields, potentially influenced by warmer temperatures in 2018.
ENVIRONMENTAL GEOCHEMISTRY AND HEALTH
(2023)
Article
Agronomy
Siyu Li, Yun Chen, Tingting Li, Feng Yu, Yajun Zhang, Kun Liu, Hao Zhang, Junfei Gu, Jianchang Yang, Lijun Liu
Summary: This study found that combining alternate wetting and moderate soil drying irrigation (WMD) with low nitrogen fertilizer rates can maintain rice root growth, resulting in comparable grain yields to conventional farming practices but with higher nitrogen use efficiency.
Article
Agronomy
Yajun Zhang, Weilu Wang, Siyu Li, Kuanyu Zhu, Xia Hua, Matthew Tom Harrison, Ke Liu, Jianchang Yang, Lijun Liu, Yun Chen
Summary: Through a global meta-analysis, it was found that alternate wetting and drying irrigation (AWD) can improve water use efficiency, but the effects on soil properties and crop growth are still uncertain. AWD increased water use efficiency by 31%, but resulted in an average yield penalty of 6% compared to continuous flooding. Optimal AWD was achieved with specific water potential and depth conditions during the rice growing season. Changes in soil organic carbon (TOC), pH, and nitrate-nitrogen (NO3-) significantly influenced yield. Combining management practices with AWD can reduce water input while increasing rice yield.
AGRICULTURAL WATER MANAGEMENT
(2023)
Article
Environmental Sciences
Kristine Samoy-Pascual, Sudhir Yadav, Gio Evangelista, Mary Ann Burac, Marvelin Rafael, Romeo Cabangon, Takeshi Tokida, Masaru Mizoguchi, Manuel Jose Regalado
Summary: This study empirically explores the factors influencing the adoption of Alternate Wetting and Drying (AWD) technique in a gravity surface irrigation system. The results show that farmers who practice enforced rotational irrigation scheduling are more likely to adopt AWD. The awareness factor does not play a significant role in the adoption, but the perception of water management as an effective weed control method is positively significant.
Article
Agronomy
Takahiro Kakehashi, Mayumi Kikuta, Daniel Makori Menge, Emily Waringa Gichuhi, Hiroaki Samejima, Daigo Makihara
Summary: The study found that in the rice growing area of Kenya's highlands, implementing an alternate wetting and drying (AWD) system can increase filled grain ratio and mitigate the decrease in grain filling caused by low temperatures. While AWD may reduce above-ground biomass, its positive impact on grain filling outweighs this drawback and can still benefit rice farmers in the tropical highlands.
Article
Chemistry, Applied
Ming-Hsuan Chen, Anna M. McClung, Jai S. Rohila, Jinyoung Y. Barnaby
Summary: The study showed that the AWD irrigation has minimal impact on rice grain quality, while some US varieties are more resilient to warmer temperatures during the grainfill period, affecting milling yield, chalkiness, and functional traits.
Article
Agronomy
Kristian Johnson, Thuong Ti Bach Vo, Duong Van Nha, Folkard Asch
Summary: A study on the effect of alternate wetting and drying (AWD) in rice production in the Vietnamese Mekong Delta (VMD) showed that AWD has the potential to reduce greenhouse gas emissions and freshwater use during the dry season. However, it also led to a significant yield reduction of 7% on average across all varieties. The study highlights the importance of adapting AWD to both environmental conditions and genotype for successful implementation.
JOURNAL OF AGRONOMY AND CROP SCIENCE
(2023)
Article
Agriculture, Multidisciplinary
Guangyan Liu, Junlin Zheng, Taotao Chen, Xuda Chen, Wei Chen, Yidi Sun, Poul Erik Laerke, Yinglong Chen, Kadambot H. M. Siddique, Daocai Chi, Ji Chen
Summary: Studies have shown that alternate wetting and drying irrigation (I-AWD) can improve water use efficiency in paddy fields, but also increase nitrous oxide (N2O) emissions. This study found that using zeolite as a soil conditioner can effectively reduce N2O emissions and increase rice grain yield under I-AWD. The combination of zeolite and urea is a sustainable approach for mitigating N2O emissions and improving rice grain yield in paddy fields.
AGRICULTURE ECOSYSTEMS & ENVIRONMENT
(2022)
Article
Agronomy
Komlavi Akpoti, Elliott R. Dossou-Yovo, Sander J. Zwart, Paul Kiepe
Summary: This study used machine learning models and water balance assessment to evaluate potentially irrigable lands for rice cultivation in Burkina Faso, and analyzed the climatic suitability for alternate wetting and drying (AWD) in the region.
AGRICULTURAL WATER MANAGEMENT
(2021)
Article
Environmental Sciences
Yidi Sun, Jigan Xie, Huijing Hou, Min Li, Yitong Wang, Xuetao Wang
Summary: The use of zeolite in rice production can improve yield, quality, and water and nutrient use efficiency.
Article
Agronomy
Richard L. Atwill, G. Dave Spencer, Jason A. Bond, Timothy W. Walker, J. Mike Phillips, Brian E. Mills, L. Jason Krutz
Summary: The long-term viability of rice production in the midsouthern United States could be affected by irrigation management strategy, and manipulating the irrigation threshold can improve rice sustainability.
Article
Environmental Sciences
Yan Sha, Daocai Chi, Taotao Chen, Shu Wang, Qing Zhao, Yinghao Li, Yidi Sun, Ji Chen, Poul Erik Laerke
Summary: This study found that alternate wetting and drying irrigation (AWD) reduced methane (CH4) emissions and increased nitrous oxide (N2O) emissions compared to continuous flooding irrigation (CF). Under the AWD regime, adding zeolite at 5 t ha(-1) further reduced CH4 emissions and improved grain yield, water productivity, and net ecosystem economic profit (NEEP). Zeolite addition at 5 t ha(-1) coupled with AWD could be an eco-economic strategy to mitigate greenhouse gas emissions and optimize grain yield in rice fields.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Environmental Sciences
MD. Rokonuzzaman, Zh Ye, C. Wu, Wc Li
Summary: The occurrence of arsenic in groundwater and its accumulation in rice grains is a global health concern. This study found that utilizing alternate wetting and drying (AWD) irrigation with temporarily stored groundwater (TSG) can effectively reduce arsenic content in rice grains. The research also highlights the importance of irrigation management and rice variety selection in minimizing arsenic accumulation in rice grains.
ENVIRONMENTAL POLLUTION
(2022)
Article
Green & Sustainable Science & Technology
Ai Leon, Kazunori Minamikawa, Taro Izumi, Nguyen Huu Chiem
Summary: In An Giang Province, Vietnam, the introduction of AWD technology has been shown to reduce LC-GHG emissions, lower the use of fertilizers and seeds, without significantly decreasing rice yields. Careful straw management is required to avoid an increase in LC-GHG emissions.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Environmental Sciences
Suneeporn Suwanmaneepong, Kulachai Kultawanich, Lampan Khurnpoon, Phatchara Eamkijkarn Sabaijai, Harry Jay Cavite, Christopher Llones, Norden Lepcha, Chanhathai Kerdsriserm
Summary: Rice farmers in Thailand who practice good agricultural practices (GAP) are more likely to adopt alternate wetting and drying (AWD) as a water-saving technology compared to non-GAP farmers. However, there is limited understanding among GAP farmers about the integration of AWD. To promote the adoption of AWD, farmers' knowledge about its safe and proper application, as well as assistance with crop insurance in case of failure, are crucial.
Article
Agronomy
Tao Liu, Chengxin Ji, Wei Wu, Wen Chen, Bingzhen Yang, Chen Chen, Chengming Sun, Xinkai Zhu, Wenshan Guo
Article
Plant Sciences
Yunji Xu, Weiyang Zhang, Chenxin Ju, Yinyin Li, Jianchang Yang, Jianhua Zhang
PLANT GROWTH REGULATION
(2016)
Article
Agronomy
Kuanyu Zhu, Qun Zhou, Yong Shen, Jiaqian Yan, Yunji Xu, Zhiqin Wang, Jianchang Yang
Article
Chemistry, Applied
Tianyang Zhou, Qun Zhou, Enpeng Li, Limin Yuan, Weilu Wang, Hao Zhang, Lijun Liu, Zhiqin Wang, Jianchang Yang, Junfei Gu
CARBOHYDRATE POLYMERS
(2020)
Article
Agronomy
Chengxin Ju, Tao Liu, Chengming Sun
Summary: The study compared the effects of controlled soil drying and continuous flooding irrigation on rice yield and nutritional quality, showing that controlled soil drying increased rice yield and protein content, but decreased the relative content of protein and essential amino acids, and increased As residues during the process.
Article
Agronomy
Chengxin Ju, Tao Liu, Chengming Sun
Summary: This study investigated the agronomic and physiological traits of N-efficient rice varieties and management strategies under moderate N rates. The results indicated that applying a larger amount of N at panicle initiation led to higher rice yield and N-use efficiency. NEVs exhibited improved root and shoot functions and higher C and N transport characteristics at the moderate N rate compared to NIVs.
Article
Agronomy
Chengxin Ju, Yiwen Zhu, Tao Liu, Chengming Sun
Summary: This study investigated the impact of different nitrogen reduction stages on rice yields and NUE in NEVs. Basal reduction and promoting-spikelet reduction were found to be the most effective in decreasing yield and NUE at the same reduction rate. It is suggested to reduce nitrogen at specific stages during rice growth when adopting moderate nitrogen application rates.
Article
Agricultural Engineering
Yuanyuan Zhao, Wei Wu, Yuzhuang Zhou, Bo Zhu, Tianle Yang, Zhaosheng Yao, Chengxin Ju, Chengming Sun, Tao Liu
Summary: This study utilized image-analysis-based methods to count rapeseed seeds, and found that rapeseed images obtained under 18,600 lx light intensity were most conducive to seed segmentation. The DeepLabV3 thorn method demonstrated the best accuracy under this condition, with Recall and F1-score exceeding 91% and 94%, respectively.
BIOSYSTEMS ENGINEERING
(2022)
Article
Agronomy
Xiaoxin Song, Fei Wu, Xiaotong Lu, Tianle Yang, Chengxin Ju, Chengming Sun, Tao Liu
Summary: In this study, a new method for the classification of farming progress types using unmanned aerial vehicle (UAV) RGB images and the proposed regional mean (RM) model is presented. The method combines optimal color indices and the RM model to improve classification accuracy. Experimental results demonstrate that the proposed method achieves higher accuracy in identifying farming progress types compared to traditional machine learning methods.
Article
Environmental Sciences
Fei Wu, Junchan Wang, Yuzhuang Zhou, Xiaoxin Song, Chengxin Ju, Chengming Sun, Tao Liu
Summary: Tiller number is an important characteristic of wheat, but estimating it accurately is challenging due to factors like leaf cover. This study introduced a gradual change feature to improve the accuracy of prediction models for tiller number in wheat. The optimized models showed improved accuracy and R2 values for three varieties of winter wheat were 0.7044, 0.7060, and 0.7357.
Article
Agriculture, Multidisciplinary
Tao Liu, Yuanyuan Zhao, Fei Wu, Junchan Wang, Chen Chen, Yuzhuang Zhou, Chengxin Ju, Zhongyang Huo, Xiaochun Zhong, Shengping Liu, Chengming Sun
Summary: Wheat is an essential crop with tiller density being an important factor affecting its yield. Currently, there is no effective high-throughput measurement method for tiller number estimation. In this study, multispectral images of wheat were obtained using unmanned aerial vehicles (UAV) and a gradual change features (GCFs) approach was proposed to accurately estimate tiller number. The results provide important insights for tiller number measurement and estimation of other agronomic parameters.
PRECISION AGRICULTURE
(2023)
Article
Agronomy
Chengxin Ju, Chen Chen, Rui Li, Yuanyuan Zhao, Xiaochun Zhong, Ruilin Sun, Tao Liu, Chengming Sun
Summary: In this study, multispectral imagery of wheat canopy obtained by an unmanned aerial vehicle was used to establish a wheat leaf rust monitoring model based on the backpropagation neural network method. The models constructed using variable dimensionality reduction methods and complex machine learning algorithms showed higher accuracy.
FOOD AND ENERGY SECURITY
(2023)
Article
Agronomy
Jianchang Yang, Qun Zhou, Jianhua Zhang
