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使用纸质分析设备的低成本精准农业实现可持续耕作

Low-cost precision agriculture for sustainable farming using paper-based analytical devices.

作者信息

Albuquerque Jéssica Rodrigues de Paula, Makara Cleyton Nascimento, Ferreira Vinícius Guimarães, Brazaca Laís Canniatti, Carrilho Emanuel

机构信息

Instituto de Química de São Carlos, Universidade de São Paulo 400, Trabalhador São-carlense Ave. São Carlos SP 13566-590 Brazil

Instituto Nacional de Ciência e Tecnologia de Bioanalítica - INCTBio Campinas SP 13083-970 Brazil.

出版信息

RSC Adv. 2024 Jul 25;14(32):23392-23403. doi: 10.1039/d4ra02310b. eCollection 2024 Jul 19.

DOI:10.1039/d4ra02310b
PMID:39055267
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11270003/
Abstract

The United Nations estimates that by 2030, agricultural production must increase by 70% to meet food demand. Precision agriculture (PA) optimizes production through efficient resource use, with soil fertility being crucial for nutrient supply. Traditional nutrient quantification methods are costly and time-consuming. This study introduces a rapid (15 min), user-friendly, paper-based platform for determining four essential macronutrients-nitrate, magnesium, calcium, and ammonium-using colorimetric methods and a smartphone for data reading and storage. The sensor effectively detects typical soil nutrient concentrations, showing strong linearity and adequate detection limits. For nitrate, the RGB method resulted in an of 0.992, a detection range of 0.5 to 10.0 mmol L, and an LOD of 0.299 mmol L. Calcium quantification using grayscale displayed an of 0.993, a detection range of 2.0 to 6.0 mmol L, and an LOD of 0.595 mmol L. Magnesium was best quantified using the hue color space, with an of 0.999, a detection range of 1.0 to 6.0 mmol L, and an LOD of 0.144 mmol L. Similarly, ammonium detection using the hue color space had an of 0.988, a range of 0.5 to 2.5 mmol L, and an LOD of 0.170 mmol L. This device enhances soil fertility assessment accessibility, supporting PA implementation and higher food production.

摘要

联合国估计,到2030年,农业产量必须增长70%才能满足粮食需求。精准农业(PA)通过高效利用资源来优化生产,土壤肥力对于养分供应至关重要。传统的养分定量方法成本高且耗时。本研究引入了一种快速(15分钟)、用户友好的纸质平台,使用比色法和智能手机进行数据读取与存储,以测定四种必需的大量营养素——硝酸盐、镁、钙和铵。该传感器能有效检测典型的土壤养分浓度,具有很强的线性和足够的检测限。对于硝酸盐,RGB方法的R²为0.992,检测范围为0.5至10.0 mmol/L,检测限为0.299 mmol/L。使用灰度进行钙定量时,R²为0.993,检测范围为2.0至6.0 mmol/L,检测限为0.595 mmol/L。镁使用色调颜色空间进行定量效果最佳,R²为0.999,检测范围为1.0至6.0 mmol/L,检测限为0.144 mmol/L。同样,使用色调颜色空间检测铵时,R²为0.988,范围为0.5至2.5 mmol/L,检测限为0.170 mmol/L。该设备提高了土壤肥力评估的可及性,支持精准农业的实施和提高粮食产量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7095/11270003/2de37579f8f9/d4ra02310b-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7095/11270003/57f8765b90b0/d4ra02310b-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7095/11270003/5c35ffab485e/d4ra02310b-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7095/11270003/5be147da1543/d4ra02310b-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7095/11270003/42a3ab65f62f/d4ra02310b-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7095/11270003/7742efd41bc5/d4ra02310b-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7095/11270003/2de37579f8f9/d4ra02310b-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7095/11270003/57f8765b90b0/d4ra02310b-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7095/11270003/5c35ffab485e/d4ra02310b-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7095/11270003/5be147da1543/d4ra02310b-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7095/11270003/42a3ab65f62f/d4ra02310b-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7095/11270003/7742efd41bc5/d4ra02310b-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7095/11270003/2de37579f8f9/d4ra02310b-f6.jpg

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