Mechanized wet direct seeding for increased rice production efficiency and reduced carbon footprint

IF 5.4 2区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY
Nguyen Van Hung, Tran Ngoc Thach, Nguyen Ngoc Hoang, Nguyen Cao Quan Binh, Dang Minh Tâm, Tran Tan Hau, Duong Thi Tu Anh, Trinh Quang Khuong, Vo Thi Bich Chi, Truong Thi Kieu Lien, Martin Gummert, Tovohery Rakotoson, Kazuki Saito, Virender Kumar
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引用次数: 0

Abstract

Crop establishment is one of the major rice production operations that strongly affects rice production, productivity, and environmental impacts. This research introduced a new technology and provided scientific evidence for the benefits of mechanized wet direct seeding (mDSR) of rice as compared with the other crop establishment practices commonly applied by farmers for wet direct seeded rice in Mekong River Delta in Vietnam, such as seeding in line using drum-seeder (dDSR) and broadcast seeding (bDSR). The experiment was implemented across two consecutive rice cropping seasons that are Winter-Spring season and Summer-Autumn season in 2020–2021. Treatments included (1–3) mDSR with seeding rates of 30, 50, and 70 kg ha− 1, (4) dDSR with 80 kg ha− 1 seed rate, and (5) bDSR as current farmer practice with seeding rate of 180 kg ha− 1. The fertilizer application was adjusted as per seeding rate with 80:40:30 kg ha− 1 N: P2O5: K2O with lower seed rate 30 and 50 kg ha− 1 in mDSR; 90:40:30 kg ha− 1 N: P2O5: K2O with medium seed rate of 70 to 80 kg ha− 1; and 115:55:40 kg ha− 1 N: P2O5: K2O with high seed rate of 180 kg ha− 1 in bDSR. Mechanized wet direct seeding rice with a lower seed rate of 30 to 70 kg ha− 1 and fertilizer rate by 22–30% reduced variation in seedling density by 40–80% and in yield by 0.1 to 0.3 t ha− 1 and had similar yield to bDSR. In consequence, N productivity was 27 and 32% higher in mDSR as compared to bDSR during the Winter-Spring season and Summer-Autumn seasons, respectively. The use of lower seed rate and fertilizer in mDSR also led to higher income and lower carbon footprint (GHGe per kg of paddy grains) of rice production than the currently used practices of bDSR. Net income of mDSR was comparable to that of dDSR and higher by 145–220 and 171–248 $US than that of bDSR in Winter-Spring season and Summer-Autumn, respectively. The carbon footprint of mDSR rice production compared to bDSR was lower by 22–25% and 12–20% during the Winter-Spring and Summer-Autumn seasons, respectively. Given the above benefits of farming efficiency, higher income, and low emission, mDSR would be a technology package that strongly supports sustainable rice cultivation transformation for the Mekong River Delta of Vietnam.

Abstract Image

机械化湿直播,提高水稻生产效率,减少碳足迹
作物整地是水稻生产的主要作业之一,对水稻产量、生产率和环境影响都有很大影响。本研究引进了一项新技术,与越南湄公河三角洲地区农民通常采用的其他湿直播水稻育秧方法(如使用滚筒播种机条播(dDSR)和直播(bDSR))相比,为水稻机械化湿直播(mDSR)的效益提供了科学依据。试验在 2020-2021 年连续两个水稻种植季节进行,即冬春季节和夏秋季节。处理包括:(1-3)mDSR,播种量为 30、50 和 70 千克/公顷;(4)dDSR,播种量为 80 千克/公顷;(5)bDSR,按照目前农民的做法,播种量为 180 千克/公顷。根据播种量调整肥料施用量,mDSR 为 80:40:30 kg ha- 1 N: P2O5: K2O,播种量为 30 和 50 kg ha- 1;90:40:30 kg ha- 1 N: P2O5: K2O,播种量为 70 至 80 kg ha- 1;bDSR 为 115:55:40 kg ha- 1 N: P2O5: K2O,播种量为 180 kg ha- 1。机械化湿直播水稻的用种量减少了 30 至 70 kg ha-1,施肥量减少了 22 至 30%,秧苗密度变化减少了 40 至 80%,产量变化减少了 0.1 至 0.3 t ha-1,产量与 bDSR 相似。因此,在冬春季节和夏秋季节,mDSR 的氮生产率分别比 bDSR 高 27% 和 32%。与目前使用的 bDSR 相比,mDSR 使用较低的种子率和肥料也能提高水稻生产的收入并降低碳足迹(每公斤稻谷的温室气体排放量)。在冬春季节和夏秋季节,mDSR 的净收入与 dDSR 相当,分别比 bDSR 高 145-220 美元和 171-248 美元。在冬春季节和夏秋季节,mDSR 水稻生产的碳足迹比 bDSR 分别低 22-25% 和 12-20%。鉴于上述耕作效率高、收入高和排放低的优势,mDSR 将成为有力支持越南湄公河三角洲可持续水稻种植转型的一揽子技术。
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来源期刊
Precision Agriculture
Precision Agriculture 农林科学-农业综合
CiteScore
12.30
自引率
8.10%
发文量
103
审稿时长
>24 weeks
期刊介绍: Precision Agriculture promotes the most innovative results coming from the research in the field of precision agriculture. It provides an effective forum for disseminating original and fundamental research and experience in the rapidly advancing area of precision farming. There are many topics in the field of precision agriculture; therefore, the topics that are addressed include, but are not limited to: Natural Resources Variability: Soil and landscape variability, digital elevation models, soil mapping, geostatistics, geographic information systems, microclimate, weather forecasting, remote sensing, management units, scale, etc. Managing Variability: Sampling techniques, site-specific nutrient and crop protection chemical recommendation, crop quality, tillage, seed density, seed variety, yield mapping, remote sensing, record keeping systems, data interpretation and use, crops (corn, wheat, sugar beets, potatoes, peanut, cotton, vegetables, etc.), management scale, etc. Engineering Technology: Computers, positioning systems, DGPS, machinery, tillage, planting, nutrient and crop protection implements, manure, irrigation, fertigation, yield monitor and mapping, soil physical and chemical characteristic sensors, weed/pest mapping, etc. Profitability: MEY, net returns, BMPs, optimum recommendations, crop quality, technology cost, sustainability, social impacts, marketing, cooperatives, farm scale, crop type, etc. Environment: Nutrient, crop protection chemicals, sediments, leaching, runoff, practices, field, watershed, on/off farm, artificial drainage, ground water, surface water, etc. Technology Transfer: Skill needs, education, training, outreach, methods, surveys, agri-business, producers, distance education, Internet, simulations models, decision support systems, expert systems, on-farm experimentation, partnerships, quality of rural life, etc.
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