植物化学物影响研究-营养物、生物刺激剂以及杀虫剂

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植物化学物影响研究-营养物、生物刺激剂以及杀虫剂

发表时间:2021-05-21 10:48:18点击:1127

来源:北京欧亚国际科技有限公司

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化肥、生物刺激剂、微生物、药物以及植保产品会影响植物发育、生长以及产量。对农业组学以及环境来说,配合浇水策略(例如干旱条件)测定不同处理优化浓度是个巨大挑战。例如,化肥的有效应用可优化植物性能,但过度施肥会污染土壤以及临近水体(地下水、湖波等)。

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Plant植物生理表型平台的软硬件使用简单,用户可控制任意基于灌溉的处理浓度以及持续时间,对每个阵列中的花盆使用,适合大多数土壤类型(例如,沙、田间土壤或花盆介质)。

软件可分析对处理的植物反馈,以直观、易用界面形式展示数据。根据其对不同处理应用的绝对以及相对反馈对植物进行评级,测定矩阵中每株植物的浓度反馈曲线。

Plantarray可对不同化学品对植物的影响进行监测和评估,介绍人力物力,减少非必要实验,并为新产品提供即时概念验证。

Plantarray系统的优点:

通过灌溉系统自动、轻松实施多化学品施用

植物生长潜力不同化学品配方快速有效预田间筛查(3-4 周内) (备选组合不同胁迫条件)

测量生长速率、基于土壤-环境-大气-水平衡来预测生产力 (田间实验支撑)

植物性能即时反馈和实时深度统计分析、清晰图标展示  (无需生理学背景)

植物动态表型生理研究的文章-生物刺激剂处理辣椒

植物生理表型研究广泛应用于干旱、渍涝、盐碱等引起作物产量损失等领域,以色列在节水农业领域走在世界前沿,以色列科学家开发了植物高通量生理学表型监测系统,实时监控植株生长情况,并广泛应用植物表型组学研究、作物耐旱相关遗传、分子育种等科学研究等领域。

Dynamic Physiological Phenotyping of Drought-Stressed Pepper Plants Treated With “Productivity-Enhancing” and “Survivability-Enhancing” Biosestimulants

Dalal et. al. (2019) Front. Plant Sci. DOI:10.3389/fpls.2019.00905

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Figure1.Experimental setup.(A)View of the randomized experimental setup array consisting of 72 measuring units loaded with Capsicum annuum.(B)Block diagram of the system. Solid circles – well-irrigated plants; empty circles – plants subjected to the drought-recovery scenario. Green – ICL-SW-treated plants, orange – ICL-NewFo1-treated plants, blue – control (no biosestimulants) plants. Note that all pot surfaces were covered to reduce evaporation, and irrigation was injected into the soil via multi-outlet drippers to ensure even distribution of fertigation and biosestimulants (see Supplementary Figure 1). 

The improvement of crop productivity under abiotic stress is one of the biggest challenges faced by the agricultural scientific community. Despite extensive research, the research-to-commercial transfer rate of abiotic stress-resistant crops remains very low. This is mainly due to the complexity of genotype × environment interactions and in particular, the ability to quantify the dynamic plant physiological response profile to a dynamic environment. Most existing phenotyping facilities collect information using robotics and automated image acquisition and analysis. However, their ability to directly measure the physiological properties of the whole plant is limited. We demonstrate a high-throughput functional phenotyping system (HFPS) that enables comparing plants’ dynamic responses to different ambient conditions in dynamic environments due to its direct and simultaneous measurement of yield-related physiological traits of plants under several treatments. The system is designed as one-to-one (1:1) plant–[sensors+controller] units, i.e., each individual plant has its own personalized sensor, controller and irrigation valves that enable (i) monitoring water-relation kinetics of each plant–environment response throughout the plant’s life cycle with high spatiotemporal resolution, (ii) a truly randomized experimental design due to multiple independent treatment scenarioses for every plant, and (iii) reduction of artificial ambient perturbations due to the immobility of the plants or other objects. In addition, we propose two new resilience-quantifying-related traits that can also be phenotyped using the HFPS: transpiration recovery rate and night water reabsorption. We use the HFPS to screen the effects of two commercial biosestimulants (a seaweed extract –ICL-SW, and a metabolite formula – ICL-NewFo1) on Capsicum annuum under different irrigation regimes. Biosestimulants are considered an alternative approach to improving crop productivity. However, their complex mode of action necessitates cost-effective pre-field phenotyping. The combination of two types of treatment (biosestimulants and drought) enabled us to evalsuate the precision and resolution of the system in investigating the effect of biosestimulants on drought tolerance. We analyze and discuss plant behavior at different stages, and assess the penalty and trade-off between productivity and resilience. In this test case, we suggest a protocol for the screening of biosestimulants’ physiological mechanisms of action.

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