The use of phosphorus (P) fertilizers in arable crop and pastoral systems is expected to change as modern agriculture is challenged to produce more food with fewer inputs. Agricultural systems models offer a dual purpose to support and integrate recent scientific advances and to identify strategies for farmers to improve nutrient efficiency. However, compared with nitrogen and carbon, advances in P modeling have been less successful. We assessed the potential opportunity of P modeling to increase P efficiency for modern agriculture and identified the current challenges associated with modeling P dynamics at the field scale. Three major constraints were (i) a paucity of detailed field datasets to model strategies aimed at increasing P use efficiency, (ii) a limited ability to predict P cycling and availability under the local effects of climate change, and (iii) a restricted ability to match measured soil P fractions to conceptual and modelable pools in soils with different mineral properties. To improve P modeling success, modelers will need to walk a tightrope to balance the roles of assisting detailed empirical research and providing practical land management solutions. We conclude that a framework for interdisciplinary collaboration is needed to acquire suitable datasets, continually assess the need for model adjustment, and provide flexibility for progression of scientific theory. Such an approach is likely to advance P management for increased P use efficiency.
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http://dx.doi.org/10.2134/jeq2019.05.0201 | DOI Listing |
Front Microbiol
December 2024
Guangdong Laboratory for Lingnan Modern Agriculture, National Risk Assessment Laboratory for Antimicrobial Resistance of Animal Original Bacteria, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China.
Introduction: The emergence of the wide variety of novel tigecycline resistance (X) variants, including (X3), (X4), (X5), and (X6), has raised a serious threat to global public health and posed a significant challenge to the clinical treatment of multidrug-resistant bacterial infections.
Methods: In this study, we evaluated the synergism of tigecycline combining with other antibiotics as a means of overcoming the (X)-mediated resistance in spp. Antibiotic synergistic efficacy was evaluated through chequerboard experiments, time-kill assays and dose-response curves.
J Anim Sci Biotechnol
January 2025
Department of Animal Science, University of Arkansas, Fayetteville, AR, USA.
Background: Sow longevity and reproductivity are essential in the modern swine industry. Although many studies have focused on the genetic and genomic factors for selection, little is known about the associations between the microbiome and sows with longevity in reproduction.
Results: In this study, we collected and sequenced rectal and vaginal swabs from 48 sows, nine of which completed up to four parities (U4P group), exhibiting reproductive longevity.
BMC Plant Biol
January 2025
Dazhou Academy of Agricultural Sciences, Dazhou, 635000, China.
Background: Stemona tuberosa, a vital species in traditional Chinese medicine, has been extensively cultivated and utilized within its natural distribution over the past decades. While the chloroplast genome of S. tuberosa has been characterized, its mitochondrial genome (mitogenome) remains unexplored.
View Article and Find Full Text PDFNat Plants
January 2025
Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
Soc Stud Sci
January 2025
Amity Institute of Social Sciences, Amity University, Noida, Uttar Pradesh, India.
The size of India's food deficit became a pressing question for the Indian state in the early years of independence. As different organizations, government bodies, and individuals debated over the ways, means, and expertise needed to tide over the food crisis, policymakers realized that the primary requirement was to have a numerical understanding of the problem. Data became crucial to accurately assess production trends and compare them with requirements.
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