Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2019
Authors
Jakob GeipelAbstract
No abstract has been registered
Authors
Hilde Margrethe Helgesen Marije Oostindjer Erik K. Arnesen Laila Dufseth Ellen-Margrethe HovlandAbstract
«Nudges» eller såkalte små dytt kan gjøre det lettere for folk å ta bedre valg, som (for eksempel) å spise sunnere, uten å begrense valgfriheten/tilgjengeligheten. Denne studien undersøkte om små endringer eller dytt i en sykehuskantine kunne hjelpe pasienter til å velge sunnere og mer «hjertevennlig mat». Prosjektets mål var å utvikle og teste ut et sett med enkle og lite kostbare «nudging»-metoder som gjør det lettere å velge mer helseriktig mat, å vise om metodene eller tiltakene gav endringer i spiseatferd og lage en praktisk veileder som beskriver resultatene og erfaringene fra prosjektet slik at disse kan brukes av kjøkkenansvarlige på andre spiseplasser.
Authors
Lampros LamprinakisAbstract
Purpose The purpose of this paper is to introduce the concept of embeddedness, highlight its connection with corporate social responsibility (CSR) strategies, and argue for its importance in securing and strengthening organizational resiliency. Design/methodology/approach Embeddedness and CSR are both well-researched topics but have been typically addressed on separate literature streams. The paper draws upon this diverse literature to introduce a conceptual framework for embeddedness in CSR. Findings The paper illustrates the importance of embeddedness and how it can enhance existing CSR strategies. A strongly embedded organization becomes deeply rooted on its socio-economic and natural environments, thus setting a symbiotic relationship that extends beyond any narrowly defined business purposes. Strong embeddedness has the potential to increase and further expand any CSR-related benefits while shielding the firm from economic downturns and thus increasing its resilience. Originality/value The paper builds upon CSR literature by incorporating the concept of embeddedness and then proposing how such an approach can strengthen an organization and increase its resilience.
Abstract
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Authors
Krzysztof KusnierekAbstract
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Authors
Krzysztof KusnierekAbstract
No abstract has been registered
Authors
Krzysztof KusnierekAbstract
No abstract has been registered
Authors
Zhichao Chen Yuxin Miao Junjun Lu Lan Zhou Yue Li Hongyan Zhang Weidong Lou Zheng Zhang Krzysztof Kusnierek Changhua LiuAbstract
Improving nitrogen (N) management of small-scale farming systems in developing countries is crucially important for food security and sustainable development of world agriculture, but it is also very challenging. The N Nutrition Index (NNI) is a reliable indicator for crop N status, and there is an urgent need to develop an effective method to non-destructively estimate crop NNI in different smallholder farmer fields to guide in-season N management. The eBee fixed-wing unmanned aerial vehicle (UAV)-based remote sensing system, a ready-to-deploy aircraft with a Parrot Sequoia+ multispectral camera onboard, has been used for applications in precision agriculture. The objectives of this study were to (i) determine the potential of using fixed-wing UAV-based multispectral remote sensing for non-destructive estimation of winter wheat NNI in different smallholder farmer fields across the study village in the North China Plain (NCP) and (ii) develop a practical strategy for village-scale winter wheat N status diagnosis in small scale farming systems. Four plot experiments were conducted within farmer fields in 2016 and 2017 in a village of Laoling County, Shandong Province in the NCP for evaluation of a published critical N dilution curve and for serving as reference plots. UAV remote sensing images were collected from all the fields across the village in 2017 and 2018. About 150 plant samples were collected from farmer fields and plot experiments each year for ground truthing. Two indirect and two direct approaches were evaluated for estimating NNI using vegetation indices (VIs). To facilitate practical applications, the performance of three commonly used normalized difference VIs were compared with the top performing VIs selected from 59 tested indices. The most practical and stable method was using VIs to calculate N sufficiency index (NSI) and then to estimate NNI non-destructively (R2 = 0.53–0.56). Using NSI thresholds to diagnose N status directly was quite stable, with a 57–59% diagnostic accuracy rate. This strategy is practical and least affected by the choice of VIs across fields, varieties, and years. This study demonstrates that fixed-wing UAV–based remote sensing is a promising technology for in-season diagnosis of winter wheat N status in smallholder farmer fields at village scale. The considerable variability in local soil conditions and crop management practices influenced the overall accuracy of N diagnosis, so more studies are needed to further validate and optimize the reported strategy and consecutively develop practical UAV remote sensing–based in-season N recommendation methods.
Abstract
We examine the origins, implications, and consequences of yield-based N fertilizer management. Yield-based algorithms have dominated N fertilizer management of corn (Zea mays) in the United States for almost 50 yr, and similar algorithms have been used all over the world to make fertilizer recommendations for other crops. Beginning in the mid-1990s, empirical research started to show that yield-based rules-of-thumb in general are not a useful guide to fertilizer management. Yet yield-based methods continue to be widely used, and are part of the principal algorithms of nearly all current “decision tool” software being sold to farmers for N management. We present details of the theoretical and empirical origins of yield-based management algorithms, which were introduced by George Stanford (1966, 1973) as a way to make N fertilizer management less reliant on data. We show that Stanford’s derivation of his “1.2 Rule” was based on very little data, questionable data omissions, and negligible and faulty statistical analysis. We argue that, nonetheless, researchers, outreach personnel, and private-sector crop management consultants were obliged to give some kind of N management guidance to farmers. Since data generation is costly, it is understandable that a broad, “ball park” rule-of-thumb was developed, loosely based on agronomic principles. We conclude by suggesting that technology changes now allow for exciting new possibilities in data-intensive fertilizer management research, which may lead to more efficient N management possibilities in the near future.