On-farm experimentation of precision agriculture for differential seed and fertilizer management in semi-arid rainfed zones

IF 5.4 2区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Precision Agriculture Pub Date : 2024-10-09 DOI:10.1007/s11119-024-10189-y

M. Videgain, J. A. Martínez-Casasnovas, A. Vigo-Morancho, M. Vidal, F. J. García-Ramos

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引用次数: 0

Abstract

Introduction

This study explores the integration of precision agriculture technologies (PATs) in rainfed cereal production within semi-arid regions.

Methods

utilizing the Veris 3100 sensor for apparent soil electrical conductivity (ECa) mapping, differentiated management zones (MZs) were established in experimental plots in Valsalada, NE Spain. Site-specific variable dose technology was applied for seed and fertilizer applications, tailoring inputs to distinct fertility levels within each MZ. Emphasizing nitrogen (N) management, the study evaluated the impact of variable-rate applications on crop growth, yield, nitrogen use efficiency (NUE), and economic returns. For the 2021/2022 and 2022/2023 seasons, seeding rates ranged from 350 to 450 grains/m², and basal fertilizer dosages varied between high and low levels. Additionally, the total nitrogen units were distributed differently between the two seasons, while maintaining a uniform topdressing fertilizer dose across all treatments.

Results

Results revealed a significant increase in yield in MZ 2 (higher fertility) compared to MZ 1 (lower fertility). NUE demonstrated notable improvement in MZ 2, emphasizing the effectiveness of variable-rate N applications. Economic returns, calculated as partial net income, showed a considerable advantage in MZ 2 over MZ 1, resulting in negative outcomes for low-fertility areas in several of the analyzed scenarios, and highlighting the financial benefits of tailored input management.

Conclusion

This research provides quantitative evidence supporting the viability and advantages of adopting PATs in rainfed cereal production. The study contributes valuable insights into optimizing input strategies, enhancing N management, and improving economic returns in semi-arid regions.

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在半干旱雨水灌溉区开展精准农业试验，促进种子和肥料的差异化管理

方法利用 Veris 3100 传感器绘制表观土壤电导率 (ECa)，在西班牙东北部瓦尔萨拉达的实验地块中建立了不同的管理区 (MZ)。种子和肥料的施用采用了针对具体地点的可变剂量技术，使投入符合每个 MZ 内不同的肥力水平。该研究以氮（N）管理为重点，评估了变剂量施肥对作物生长、产量、氮利用效率（NUE）和经济收益的影响。在 2021/2022 年和 2022/2023 年两季，播种率从 350 粒/平方米到 450 粒/平方米不等，基肥用量在高水平和低水平之间变化。结果结果显示，与肥力较低的 MZ 1 相比，肥力较高的 MZ 2 产量显著增加。氮利用效率在 MZ 2 中也有显著提高，这突出表明了不同施肥量氮肥的有效性。以部分净收入计算的经济收益显示，MZ 2 比 MZ 1 有相当大的优势，导致低肥力地区在几个分析方案中出现负收益，突出了有针对性的投入管理的经济效益。该研究为半干旱地区优化投入策略、加强氮管理和提高经济收益提供了宝贵的见解。

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来源期刊

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.