3 research outputs found
Technology transfer, policies, and the role of the private sector in the global poultry revolution:
Get PDF"With the Biotech Revolution, questions are being asked about what role the government should play in the process—does public research in developing countries play a role? Can governments speed the spread of technology by offering complementary services? Unlike the public investment–driven Green Revolution in cereals, the “Poultry Revolution” in developing countries was driven by the successful transfer of biological technology developed by the private sector in the developed world to developing countries. This paper uses a supply response function to measure the importance of different types of private technology and of public investments on poultry productivity. The findings confirm that imported private technology was important to the growth of the poultry industry but also emphasize the importance of complementary government investments such as veterinary services." from authors' abstractsupply response function, private sector research, Technology transfer, Poultry, Public investment,
Testing a global standard for quantifying species recovery and assessing conservation impact
Get PDFRecognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a “Green List of Species” (now the IUCN Green Status of Species). A draft Green Status framework for assessing species’ progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species’ viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species’ recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard.
Inclusive author list: Molly K. Grace • H. Resit Akçakaya • Elizabeth L. Bennett • Thomas M. Brooks • Anna Heath • Simon Hedges • Craig Hilton-Taylor • Michael Hoffmann • Axel Hochkirch • Richard Jenkins • David A. Keith • Barney Long • David P. Mallon • Erik Meijaard • E.J. Milner-Gulland • Jon Paul Rodriguez • P.J. Stephenson • Simon N. Stuart • Richard P. Young • Pablo Acebes • Joanna Alfaro-Shigueto • Silvia Alvarez-Clare • Raphali Rodlis Andriantsimanarilafy • Marina Arbetman • Claudio Azat • Gianluigi Bacchetta • Ruchi Badola • Luís M.D. Barcelos • Joao Pedro Barreiros • Sayanti Basak • Danielle J. Berger • Sabuj Bhattacharyya • Gilad Bino • Paulo A.V. Borges • Raoul K. Boughton • H. Jane Brockmann • Hannah L. Buckley • Ian J. Burfield • James Burton • Teresa Camacho-Badani • Luis Santiago Cano-Alonso • Ruth H. Carmichael • Christina Carrero • John P. Carroll • Giorgos Catsadorakis • David G. Chapple • Guillaume Chapron • Gawsia Wahidunnessa Chowdhury • Louw Claassens • Donatella Cogoni • Rochelle Constantine • Christie Anne Craig • Andrew A. Cunningham • Nishma Dahal • Jennifer C. Daltry • Goura Chandra Das • Niladri Dasgupta • Alexandra Davey • Katharine Davies • Pedro Develey • Vanitha Elangovan • David Fairclough • Mirko Di Febbraro • Giuseppe Fenu • Fernando Moreira Fernandes • Eduardo Pinheiro Fernandez • Brittany Finucci • Rita Földesi • Catherine M. Foley • Matthew Ford • Michael R.J. Forstner • Néstor García • Ricardo Garcia-Sandoval • Penny C. Gardner • Roberto Garibay-Orijel • Marites Gatan-Balbas • Irene Gauto • Mirza Ghazanfar Ullah Ghazi • Stephanie S. Godfrey • Matthew Gollock • Benito A. González • Tandora D. Grant • Thomas Gray • Andrew J. Gregory • Roy H.A. van Grunsven • Marieka Gryzenhout • Noelle C. Guernsey • Garima Gupta • Christina Hagen • Christian A. Hagen • Madison B. Hall • Eric Hallerman • Kelly Hare • Tom Hart • Ruston Hartdegen • Yvette Harvey-Brown • Richard Hatfield • Tahneal Hawke • Claudia Hermes • Rod Hitchmough • Pablo Melo Hoffmann • Charlie Howarth • Michael A. Hudson • Syed Ainul Hussain • Charlie Huveneers • Hélène Jacques • Dennis Jorgensen • Suyash Katdare • Lydia K.D. Katsis • Rahul Kaul • Boaz Kaunda-Arara • Lucy Keith-Diagne • Daniel T. Kraus • Thales Moreira de Lima • Ken Lindeman • Jean Linsky • Edward Louis Jr. • Anna Loy • Eimear Nic Lughadha • Jeffrey C. Mangel • Paul E. Marinari • Gabriel M. Martin • Gustavo Martinelli • Philip J.K. McGowan • Alistair McInnes • Eduardo Teles Barbosa Mendes • Michael J. Millard • Claire Mirande • Daniel Money • Joanne M. Monks • Carolina Laura Morales • Nazia Naoreen Mumu • Raquel Negrao • Anh Ha Nguyen • Md. Nazmul Hasan Niloy • Grant Leslie Norbury • Cale Nordmeyer • Darren Norris • Mark O’Brien • Gabriela Akemi Oda • Simone Orsenigo • Mark Evan Outerbridge • Stesha Pasachnik • Juan Carlos Pérez-Jiménez • Charlotte Pike • Fred Pilkington • Glenn Plumb • Rita de Cassia Quitete Portela • Ana Prohaska • Manuel G. Quintana • Eddie Fanantenana Rakotondrasoa • Dustin H. Ranglack • Hassan Rankou • Ajay Prakash Rawat • James Thomas Reardon • Marcelo Lopes Rheingantz • Stephen C. Richter • Malin C. Rivers • Luke Rollie Rogers • Patrícia da Rosa • Paul Rose • Emily Royer • Catherine Ryan • Yvonne J. Sadovy de Mitcheson • Lily Salmon • Carlos Henrique Salvador • Michael J. Samways • Tatiana Sanjuan • Amanda Souza • dos Santos • Hiroshi Sasaki • Emmanuel Schutz • Heather Ann Scott • Robert Michael Scott • Fabrizio Serena • Surya P. Sharma • John A. Shuey • Carlos Julio Polo Silva • John P. Simaika • David R. Smith • Julia L.Y. Spaet • Shanjida Sultana • Bibhab Kumar Talukdar • Vikash Tatayah • Philip Thomas • Angela Tringali • Hoang Trinh-Dinh • Chongpi Tuboi • Aftab Alam Usmani • Aída M. Vasco-Palacios • Jean-Christophe Vié • Jo Virens • Alan Walker • Bryan Wallace • Lauren J. Waller • Hongfeng Wang • Oliver R. Wearn • Merlijn van Weerd • Simon Weigmann • Daniel Willcox • John Woinarski • Jean W.H. Yong • Stuart Young
Glucose Lowering Effect of Brown Pigmented Rice (oryza sativa l) in Diet-Induced Hyperglycemic Sprague Dawley Rats
Get PDFThe study investigated the dietary fiber and glycemic index of the three varieties of brown pigmented rice, namely, Inpari 24, Mawar, and Segreng, and the hypoglycemic effect of the rice variety with the highest dietary fiber and low glycemic index in hyperglycemic Sprague Dawley rats. Study phases included: 1) chemical analysis such as dietary fiber and amylose content, and proximate analysis of brown pigmented rice, 2) intervention phase 1: determination of effective dose of brown pigmented rice; and 3) intervention phase 2: in vivo evaluation of hypoglycemic effects of brown pigmented rice. Segreng variety contained the highest dietary fiber and lowest glycemic index. At the end of the intervention period, the effective dose to lower the blood glucose level was 75% cooked brown pigmented rice and 25 % commercial rodent feed combination with a reduction of 54.57 %. And its reduction was comparable to the blood glucose level of rats given glibenclamide treatment (58.24 %). A significant positive correlation for blood glucose with calorie, carbohydrate, and fat was also observed. Therefore, the consumption of cooked brown pigmented rice can lower blood glucose levels in hyperglycemic Sprague Dawley rats. Furthermore, the glucose-lowering could be due to the dietary fiber and amylose content of brown pigmented rice. Further study is recommended using human subjects, and it may also be replicated using other grains like corn, adlai, sorghum, and root crops
