National De La Recherche Agronomique Research Articles

Fast Then Slow: Choice Revisions Drive a Decline in the Attraction Effect

We explore the nature and robustness of the attraction effect. The attraction effect can be seen as a persistent bias or as the result of heuristics that may not persist upon reflection. We provide robust experimental evidence that the attraction effect first rises and then falls over time when participants are incentivized to make a quick choice they can later revise. Participants in two experiments under continuous time pressure make choices among options with the aim to maximize an objective, measurable value. We find that participants disproportionately favor the asymmetrically dominant option in the first seconds and then revise their choices until the effect disappears or is significantly reduced. The effect survives only in the special and often studied case of indifference among options. We develop a tractable extension to the multiattribute linear ballistic accumulator model to allow for choice revisions. That model explains how choice revisions reduce context effects. We estimate its parameters at the individual level and document differences between fast and slow participants that also play a role in explaining the rise-and-fall pattern in the attraction effect. We extend the analysis to similarity and compromise effects. We find a very small similarity effect, which does not exhibit any dynamics, and a significant reverse compromise effect displaying a rise-and-fall pattern. Our findings, although limited to objective-value tasks, are consistent with context effects being short-term heuristics that can be superseded by more reflective cognitive strategies when decision makers have time and incentive to do so. This paper was accepted by Manel Baucells, behavioral economics and decision analysis. Funding: This work was supported by the Institut National de la Recherche Agronomique [Grant SAE2 Jeune Chercheur 2017]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4874 .

Characterizing the accuracy of satellite-based products to detect soil moisture at the global scale

Satellite-based soil moisture (SM) products exhibit distinct error patterns at various timescales. Knowledge of their accuracy characteristics for capturing different SM signals is significant for many real-world applications in soil sciences. This study conducted a comprehensive evaluation of the following eight satellite-based SM products: the Soil Moisture and Ocean Salinity-Institut National de la Recherche Agronomique and Centre d'Etudes Spatiales de la BIOsphere version 2 (SMOS-IC-V2), the Level 3 (L3) Soil Moisture Active Passive V7 (SMAP-V7), the combined European Space Agency Climate Change Initiative V06.1 (ESA CCI-V06.1), the L3 SMOS V3, the L3 Advanced Microwave Scanning Radiometer (AMSR2) V3 from the Japan Aerospace Exploration Agency (JAXA), the L3 Land Parameter Retrieval Model (LPRM) C1- and X- band AMSR2 V001, and the Chinese FengYun-3B V1. By using >1,500 sites from the International Soil Moisture Network and triple collocation analysis, this study aimed to identify not only the relative strengths of the products for detecting original SM signals, short-term SM anomalies, and long-term SM seasonality, but also the impacts of land cover, soil organic carbon (SOC), and soil texture on their retrieval accuracy. In terms of capturing the temporal dynamics of SM anomalies, SMAP-V7 outperformed SMOS-IC-V2 and ESA CCI-V06.1. In arid and semi-arid areas, LPRM C1-band AMSR2 V001 outperformed SMOS-ICV2 and SMAP-V7, in terms of detecting SM seasonality. SMAP-V7, SMOS-ICV2, and ESA CCI-V06.1 effectively captured SM seasonality over most forest zones and effectively detected short-term SM anomalies over croplands and grasslands. The l-band products showed the highest accuracy in terms of capturing the temporal dynamics of all the SM signals when the clay fraction was in the range of 20 %–25 %. Most products had difficulties in detecting SM variations over bare deserts, sandy and clay soils, and soils rich in organic matter (SOC content > 8.72 %).

At the crossroads of fertility and metabolism: the importance of AMPK-dependent signaling in female infertility associated with hyperandrogenism.

What biological processes are linked to the signaling of the energy sensor 5'-AMP-activated protein kinase (AMPK) in mouse and human granulosa cells (GCs)? The lack of α1AMPK in GCs impacted cell cycle, adhesion, lipid metabolism and induced a hyperandrogenic response. AMPK is expressed in the ovarian follicle, and its activation by pharmacological medications, such as metformin, inhibits the production of steroids. Polycystic ovary syndrome (PCOS) is responsible for infertility in approximately 5-20% of women of childbearing age and possible treatments include reducing body weight, improving lifestyle and the administration of a combination of drugs to improve insulin resistance, such as metformin. AMPK signaling was evaluated by analyzing differential gene expression in immortalized human granulosa cells (KGNs) with and without silencing α1AMPK using CRISPR/Cas9. In vivo studies included the use of a α1AMPK knock-out mouse model to evaluate the role of α1AMPK in folliculogenesis and fertility. Expression of α1AMPK was evaluated in primary human granulosa-luteal cells retrieved from women undergoing IVF with and without a lean PCOS phenotype (i.e. BMI: 18-25 kg/m2). α1AMPK was disrupted in KGN cells and a transgenic mouse model. Cell viability, proliferation and metabolism were evaluated. Androgen production was evaluated by analyzing protein levels of relevant enzymes in the steroid pathway by western blots, and steroid levels obtained from in vitro and in vivo models by mass spectrometry. Differential gene expression in human GC was obtained by RNA sequencing. Analysis of in vivo murine folliculogenesis was performed by histology and immunochemistry, including evaluation of the anti-Müllerian hormone (AMH) marker. The α1AMPK gene expression was evaluated by quantitative RT-PCR in primary GCs obtained from women with the lean PCOS phenotype (n = 8) and without PCOS (n = 9). Silencing of α1AMPK in KGN increased cell proliferation (P < 0.05 versus control, n = 4), promoted the use of fatty acids over glucose, and induced a hyperandrogenic response resulting from upregulation of two of the enzymes involved in steroid production, namely 3β-hydroxysteroid dehydrogenase (3βHSD) and P450 side-chain cleavage enzyme (P450scc) (P < 0.05, n = 3). Female mice deficient in α1AMPK had a 30% decrease in their ovulation rate (P < 0.05, n = 7) and litter size, a hyperandrogenic response (P < 0.05, n = 7) with higher levels of 3βHSD and p450scc levels in the ovaries, and an increase in the population of antral follicles (P < 0.01, n = 10) compared to controls. Primary GCs from lean women with PCOS had lower α1AMPK mRNA expression levels than the control group (P < 0.05, n = 8-9). The FastQ files and metadata were submitted to the European Nucleotide Archive (ENA) at EMBL-EBI under accession number PRJEB46048. The human KGN is a not fully differentiated, transformed cell line. As such, to confirm the role of AMPK in GC and the PCOS phenotype, this model was compared to two others: an α1AMPK transgenic mouse model and primary differentiated granulosa-lutein cells from non-obese women undergoing IVF (with and without PCOS). A clear limitation is the small number of patients with PCOS utilized in this study and that the collection of human GCs was performed after hormonal stimulation. Our results reveal that AMPK is directly involved in steroid production in human GCs. In addition, AMPK signaling was associated with other processes frequently reported as dysfunctional in PCOS models, such as cell adhesion, lipid metabolism and inflammation. Silencing of α1AMPK in KGN promoted folliculogenesis, with increases in AMH. Evaluating the expression of the α1AMPK subunit could be considered as a marker of interest in infertility cases related to hormonal imbalances and metabolic disorders, including PCOS. This study was financially supported by the Institut National de la Recherche Agronomique (INRA) and the national programme « FERTiNERGY » funded by the French National Research Agency (ANR). The authors report no intellectual or financial conflicts of interest related to this work. R.K. is identified as personnel of the International Agency for Research on Cancer/World Health Organization. R.K. alone is responsible for the views expressed in this article and she does not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer/World Health Organization. N/A.

A fine-resolution soil moisture dataset for China in 2002–2018

Abstract. Soil moisture is an important parameter required for agricultural drought monitoring and climate change models. Passive microwave remote sensing technology has become an important means to quickly obtain soil moisture across large areas, but the coarse spatial resolution of microwave data imposes great limitations on the application of these data. We provide a unique soil moisture dataset (0.05∘, monthly) for China from 2002 to 2018 based on reconstruction model-based downscaling techniques using soil moisture data from different passive microwave products – including AMSR-E and AMSR2 (Advanced Microwave Scanning Radiometer for Earth Observing System) JAXA (Japan Aerospace Exploration Agency) Level 3 products and SMOS-IC (Soil Moisture and Ocean Salinity designed by the Institut National de la Recherche Agronomique, INRA, and Centre d’Etudes Spatiales de la BIOsphère, CESBIO) products – calibrated with a consistent model in combination with ground observation data. This new fine-resolution soil moisture dataset with a high spatial resolution overcomes the multisource data time matching problem between optical and microwave data sources and eliminates the difference between the different sensor observation errors. The validation analysis indicates that the accuracy of the new dataset is satisfactory (bias: −0.057, −0.063 and −0.027 m3 m−3; unbiased root mean square error (ubRMSE): 0.056, 0.036 and 0.048; correlation coefficient (R): 0.84, 0.85 and 0.89 on monthly, seasonal and annual scales, respectively). The new dataset was used to analyze the spatiotemporal patterns of soil water content across China from 2002 to 2018. In the past 17 years, China's soil moisture has shown cyclical fluctuations and a slight downward trend and can be summarized as wet in the south and dry in the north, with increases in the west and decreases in the east. The reconstructed dataset can be widely used to significantly improve hydrologic and drought monitoring and can serve as an important input for ecological and other geophysical models. The data are published in Zenodo at https://doi.org/10.5281/zenodo.4738556 (Meng et al., 2021a).

Energy Requirements of Beef Cattle: Current Energy Systems and Factors Influencing Energy Requirements for Maintenance.

Simple SummaryThe accurate estimation of energy requirements for present-day genotypes under current feeding conditions is crucial for improving profitability and reducing the environmental impact of the beef industry. Equations for predicting energy requirements of beef cattle according to the Agricultural and Food Research Council (AFRC) are outdated and require an urgent update. The results from literature review confirmed previous reports on the under prediction of energy requirements for maintenance by the AFRC, especially for growing animals. This may have consequences on the efficiency of use of the dietary energy on productive functions. Although much less research has been conducted over the last decade on energy metabolism for suckler cows, the existing data appears to be relevant as a valid reference for updating AFRC recommendations. The present review also revealed the lack of data on the contribution of both animal and diet-related factors influencing on energy requirements for beef cattle and thus conclusions on this regard are difficult to draw.The present review compared features of the UK system for predicting energy requirements in beef cattle with a number of feeding systems developed from research institutes consortiums around the world. In addition, energy requirements for maintenance calculated from studies conducted at the Agri-Food and Biosciences Institute (AFBI) in Northern Ireland since the 1990s were compared with compiled data from recent peer-review papers published over the last decade (2009–2020). The mean metabolisable energy requirement for the maintenance (MEm) of growing cattle was 0.672 MJ/kg0.75 according to values obtained from calorimetry studies conducted at AFBI. This value is respectively 8.2 and 19.5% greater than the MEm values obtained by the Agricultural and Food Research Council (AFRC), and the National Academies of Sciences, Engineering and Medicine (NASEM) equations, but it is in close agreement with the Institut National de la Recherche Agronomique (INRA) approach, when assuming a Bos taurus bull (300 kg LW) and an efficiency for converting energy for maintenance (km) of 0.65. Most of the literature data on energy requirements for the maintenance for this animal category were obtained from studies conducted with Bos indicus animals and their crossbreds in Brazilian conditions with this confirming lower requirements of these animals when compared to pure Bos taurus cattle. A simulation of the total ME requirements calculated for an Angus × Friesian steer (LW = 416 kg) offered good quality grass silage, indicated that both AFRC and NASEM systems overestimate (38.5 and 20.5%, respectively) the observed efficiency of converting ME for growth (kg). When the total ME requirements (maintenance + growth) were assessed, both systems underpredicted total ME requirement in 15.8 and 22.1 MJ/d. The mean MEm requirements for suckler cows obtained from the literature (0.596 MJ/kg0.75) is on average 19.1% greater than predictions given by both AFRC and INRA (lactation) equations when considering a 550 kg cow and a km value of 0.72. Although no differences in net energy requirements for maintenance (NEm) were detected between dry and lactating suckler cows, as expected the later displayed greater variation as a result of differences in milk production. On this regard, the INRA model recognise increased NEm requirements for lactating animals compared to dry cows. The re-evaluation of the concept of diet metabolisability and the analysis of existing data on compensatory growth responses are recommended for future updates of the British system (AFRC) having in to account the particularities of grass-based systems in the UK.

Evaluation of SMAP, SMOS, and AMSR2 Soil Moisture Products Based on Distributed Ground Observation Network in Cold and Arid Regions of China

Long-term surface soil moisture (SM) data are increasingly needed in water budget and energy balance analysis of watersheds. The performance of nine remotely sensed SM products from Advanced Microwave Scanning Radiometer 2 (AMSR2), Soil Moisture and Ocean Salinity (SMOS), and Soil Moisture Active Passive (SMAP) missions are evaluated based on observations collected from distributed observation networks in the Heihe River Basin (HRB) of China during 2013 to 2017. Results show that the SMAP Level 3 dual channel algorithm SM retrievals reflect the seasonal SM variations well with high temporal correlations of ∼0.7 and high accuracy within 0.04 m3/m3 in terms of unbiased root mean squared error (ubRMSE) over the grassland in the HRB. The SMOS level 3 SM retrievals present increased underestimation and ubRMSE of ∼0.10 m3/m3 as the vegetation increases. The newly published SMOS Institut National de la Recherche Agronomique–Centre d'Etudes Spatiales de la BIOsphere product in version 2 outperforms the SMOS level 3 product with improved temporal correlation coefficient above 0.4 and lower ubRMSE of ∼0.05 m3/m3. AMSR2 Land Parameter Retrieval Algorithm SM products show extremely large overestimation over the vegetated regions in HRB, especially the C-band products. Drastically high underestimation biases are observed in the Japan Aerospace Exploration Agency AMSR2 SM product. Parameter uncertainty analyses indicate that the different parameterization schemes of vegetation optical depth inputs could be one of the main reasons resulting in the systematic overestimation/underestimation biases in the AMSR2/SMOS/SMAP SM retrievals. The findings aim to provide insights into studies on algorithms refinements and data fusions of SM products in HRB.

Prediction of the metabolisable energy content of forages and mixed diets for horses: validation and comparison of two evaluation systems

The metabolisable energy (ME) content of feeds is a better estimate of their ‘true’ energy value than their digestible energy (DE) content, because ME takes account of the gross energy of methane (GEgas) and the gross energy of urine (GEurine) losses. The accuracy and precision of the Gesellschaft für Ernährungsphysiologie (GfE) and Institut National de la Recherche Agronomique (INRA) systems for predicting the DE and ME contents of diets for horses were compared using the results of a study comprising 15 mixed diets. The INRA system was more accurate than the GfE system for predicting DE, GEurine and ME: the biases between the predicted and the measured values were −0.26 vs –0.46 MJ/kg DM for DE (P < 0.05), −0.03 vs 0.13 MJ/kg DM for GEurine (P < 0.05) and −0.09 vs –0.62 MJ/kg DM for ME (P < 0.05). The biases for GEgas were not significantly different (P > 0.05) between systems. In addition, a study was carried out with 24 forages to compare the ME value of permanent meadow and lucerne hays predicted with the GfE and the INRA systems. The INRA system gave higher prediction values of DE than the GfE system (P < 0.001) and lower estimates of GEgas (0.34 vs 0.63 MJ/kg DM for permanent meadow hays and 0.38 vs 0.63 MJ/kg DM for lucerne hays) (P < 0.001) and GEurine (0.85 vs 0.93 MJ/kg DM for grassland hays and 1.08 vs 1.37 MJ/kg DM for lucerne hays) (P < 0.001). The INRA system thus gave higher estimates of ME (7.57 vs 6.77 MJ/kg DM for permanent meadow hays and 8.80 vs 6.46 MJ/kg DM for lucerne hays, P < 0.001) in agreement with the results obtained with mixed diets. The ME values of permanent meadow hays and legume hays should therefore be predicted separately using specific equations as previously established for the DE value.

Challenges in flood modeling over data-scarce regions: how to exploit globally available soil moisture products to estimate antecedent soil wetness conditions in Morocco

Abstract. The Mediterranean region is characterized by intense rainfall events giving rise to devastating floods. In Maghreb countries such as Morocco, there is a strong need for forecasting systems to reduce the impacts of floods. The development of such a system in the case of ungauged catchments is complicated, but remote-sensing products could overcome the lack of in situ measurements. The soil moisture content can strongly modulate the magnitude of flood events and consequently is a crucial parameter to take into account for flood modeling. In this study, different soil moisture products (European Space Agency Climate Change Initiative, ESA-CCI; Soil Moisture and Ocean Salinity, SMOS; Soil Moisture and Ocean Salinity by the Institut National de la Recherche Agronomique and Centre d'Etudes Spatiales de la Biosphère, SMOS-IC; Advanced Scatterometer, ASCAT; and ERA5 reanalysis) are compared to in situ measurements and one continuous soil-moisture-accounting (SMA) model for basins located in the High Atlas Mountains, upstream of the city of Marrakech. The results show that the SMOS-IC satellite product and the ERA5 reanalysis are best correlated with observed soil moisture and with the SMA model outputs. The different soil moisture datasets were also compared to estimate the initial soil moisture condition for an event-based hydrological model based on the Soil Conservation Service curve number (SCS-CN). The ASCAT, SMOS-IC, and ERA5 products performed equally well in validation to simulate floods, outperforming daily in situ soil moisture measurements that may not be representative of the whole catchment soil moisture conditions. The results also indicated that the daily time step may not fully represent the saturation state before a flood event due to the rapid decay of soil moisture after rainfall in these semiarid environments. Indeed, at the hourly time step, ERA5 and in situ measurements were found to better represent the initial soil moisture conditions of the SCS-CN model by comparison with the daily time step. The results of this work could be used to implement efficient flood modeling and forecasting systems in semiarid regions where soil moisture measurements are lacking.

Evaluation of predicted ration nutritional values by NRC (2001) and INRA (2018) feed evaluation systems, and implications for the prediction of milk response

Net energy and protein systems (hereafter called feed evaluation systems) offer the possibility to formulate rations by matching feed values (e.g., net energy and metabolizable protein) with animal requirements. The accuracy and precision of this approach relies heavily on the quantification of various animal digestive and metabolic responses to dietary changes. Therefore, the aims of the current study were, first, to evaluate the predicted responses to dietary changes of total-tract digestibility (including organic matter, crude protein, and neutral detergent fiber) and nitrogen (N) flows at the duodenum (including microbial N and undigested feed N together with endogenous N) against measurements from published studies by 2 different feed evaluation systems. These feed evaluation systems were the recently updated Institut National de la Recherche Agronomique (INRA, 2018) and the older, yet widely used, National Research Council (NRC, 2001) system. The second objective was to estimate the accuracy and precision of predicting milk yield responses based on values of net energy (NEL) and metabolizable protein (MP) supply predicted by the 2 feed evaluation systems. For this, published studies, with experimentally induced changes in either NEL or MP content, were used to calibrate the relationship of NEL and MP supply, with milk component yields. Based on the slope, root mean square prediction error, and concordance correlation coefficient (CCC), the results obtained show that total nonammonia nitrogen flow at the duodenum was predicted with similar accuracy and precision, but considerably better prediction was achieved when the INRA model was used to predict organic matter and neutral detergent fiber digestibility responses. The average NEL and MP content predicted by both models was similar, but NEL and MP content of individual diets differed substantially between both models as indicated by determination coefficients of 0.45 (NEL content) and 0.50 (MP content). Despite these differences, this work shows that when response equations are calibrated with NEL and MP values either from the INRA model or from the NRC model, the accuracy and precision (slope, root mean square prediction error, and CCC) of the predicted milk component yields responses is similar between the models. The lowest accuracy and precision were observed for milk fat yield response, with CCC values in the range of 0.37 to 0.40, compared with milk lactose and protein yields responses for which CCC values were in the range of 0.75 to 0.81.

Análisis bibliométrico de la modelación de bosques templados manejados: una perspectiva global en las herramientas de manejo forestal sustentable

Introduction: Bibliometric analysis is a quantitative tool for recognizing trends and research gaps in topics of scientific interest. Objective: To identify progress in scientific production, collaborative networks, research issues and application of models of temperate forest management (MTFM), on a global scale, in relation to management, productivity, carbon storage and nutrient cycling. Materials and methods: The review focused on the collection of data from the Web of Science Core Collection platform in the period 2005-2019. Results and discussion: The bibliometric analysis made possible to collect 960 specialized scientific articles on the topic, from journals indexed in Journal Citation Reports (JCR). The institutions with the greatest academic authority in forest management studies were Natural Resources of Canada (NRCan), Institut National de la Recherche Agronomique (INRA) and US Forest Service. MTFM topics focused on forest plantation growth, effects of forest practices on structure, productivity, carbon sequestration and, to a lesser extent, nutrient availability. Mexico showed low collaboration with other institutions and a forest approach in the application of models. Conclusions: The analysis helped to guide research on MTFM in Mexico. The implementation of models is recommended to achieve forest harvesting based on an integrated understanding of the system and thus provide sustainability.

Evolve Roundup Ready® high erucic acid, low glucosinolate hybrid summer rape

Evolve is the world’s first ogu INRA (Institut national de la recherche agronomique) CMS (cytoplasmic male sterility) hybrid summer rape (Brassica napus L.) Roundup Ready® high erucic acid, low glucosinolate cultivar. On average, Evolve yielded 12.4% more seed, 6 g kg−1 more seed oil, and 5 g kg−1 less meal protein than Red River 1861, an open-pollinated Roundup Ready® high erucic acid, low glucosinolate summer rape. Evolve has an erucic acid content of 52.3% in isolated field trials of high erucic acid rapeseed genotypes and is adapted to the southern B. napus growing regions of western Canada.

Comparison of three systems for predicting the digestible energy value of natural grassland and lucerne hays for horses

The accuracy and precision of the National Research Council (NRC), Gesellschaft für Ernährungsphysiologie (GfE) and Institut National de la Recherche Agronomique (INRA) systems for predicting the digestible energy (DE) value of hays were determined from the results of 15 digestibility trials with natural grassland hays and 9 digestibility trials with lucerne hays that all met strict experimental and a tight corpus of methods. The hays were harvested in the temperate zone. They covered broad ranges of chemical composition and DE value. The INRA system was more accurate than the other two systems, with the bias between the predicted and measured DE values of natural grassland and lucerne hays averaging −0.11 and −0.04 MJ/kg DM with the INRA system, 0.34 and −0.70 MJ/kg DM with the NRC system and −0.50 and −1.69 MJ/kg DM with the GfE system (P < 0.05). However, the precision of the three systems was similar; the standard error of prediction corrected by bias was not significantly different (P > 0.05). The GfE system underestimated the DE value of hays, especially of lucerne hays. The differences between the predicted and measured DE values resulted mainly from the errors in the prediction of organic matter digestibility and energy digestibility for both natural grassland and lucerne hays. Discrimination according to botanical family (grassland v. lucerne) can help improve the prediction of the DE value of hays. The choice of appropriate predictive variables is discussed in the light of differences in chemical composition and digestibility of the various cell wall components of grassland and lucerne hays. Neutral detergent fiber (NDF) may thus be preferable to ADF in the prediction equation of the DE value of lucerne hays, whereas ADF and NDF may both be relevant for natural grassland hays.

Development of a Database to Collect Emission Values for Livestock Systems

Growing demand for animal products has contributed to an increase in biogeochemical fluxes, leading particularly to gaseous ammonia, methane, and nitrous oxide emissions into the atmosphere. Developing accurate knowledge on the sources and magnitude of gas emissions from the livestock sector is essential to reducing emissions, while meeting other societal expectations, and to implementing effective regulations. To this end, a database called ELFE (ELevage et Facteurs d’Emission; i.e., Livestock and Emission Factors) was recently developed. It currently contains ∼5200 gas emission measurements extracted from 345 publications of the international literature published from 1964 to 2018 from 37 countries. One of its innovative aspects is the structured and comprehensive description of both the livestock system and the measurement method associated with emission data. Ammonia emitted by livestock systems represents 40 to 80% of emission values and 45 to 81% of the values concern production systems with slurry, depending on the animal produced. This database will contribute to improved emission factors for national inventories by more thoroughly considering factors influencing emission levels and data quality. It highlights the need for shared and standardized reporting protocols for both the livestock system itself and the measurement conditions, to allow for thorough comparisons and to reduce uncertainty in unit conversions. The database is available online on the Institut national de la recherche agronomique (INRA) platform (https://data.inra.fr/dataset.xhtml?persistentId=doi:10.15454/MHJPYT) and will be updated annually with new gas emissions.Core Ideas A new database includes about 5200 emission values from 345 publications. Of these emission values, 62% were related to NH3, 41% to CH4, 29% to N2O, and 29% to CO2. The database includes a detailed description of production systems and measurement methods. Complete data for system description and unit conversion increase potential uses.

Abstracts of the 18th French Rabbit Days

&lt;p&gt;The 18&lt;sup&gt;th&lt;/sup&gt; edition of the French Rabbit Days (Journées de la Recherche Cunicole) was organized by the association CUNICULTURE, in association with the INRA (Institut National de la Recherche Agronomique) and the ASFC (French Branch of the WRSA), in Nantes, during one and a half days 27-28 May 2019. A total of 32 peer reviewed communications, including 3 synthesis, were orally presented to about 90 attendants. The 2 most relevant subjects were 1/ studies on and possibilities of control of the viral haemorrhagic disease caused by the new RHDV2, and 2/ control of digestive disorders, particularly coccidiosis, with nonchemical feed additives or diet formulation. One part of the communications was also devoted to the efforts made for the promotion of rabbit meat in France and to the comportment of consumers in relation with rabbit meat. The full texts of the communications, in French, are available on the WRSA website at the URL : &lt;a href="http://world-rabbit-science.com/Other-Proceedings/2019-18th%20Rabbit%20Days/000-E-Book-JRC2019.pdf"&gt;http://world-rabbit-science.com/Other-Proceedings/2019-18th%20Rabbit%20Days/000-E-Book-JRC2019.pdf&lt;/a&gt;&lt;/p&gt;

Low Protein/low Methionine/high Carbohydrate Diets Induce Hyperphagia, Increase Energy Expenditure and FGF21, but Modestly Affect Adiposity in Female BalbC Mice (OR09-01-19)

ObjectivesLow-protein diets are reported to induce hyperphagia to fulfil protein needs but at the expense of energy balance with a risk to gain in adiposity. However, different studies did not show body fat gain because an increased energy expenditure partly compensated the increase in energy intake and prevents the gain in adiposity. The present study evaluated in mice the consequence of protein restricted diets combined with protein quality (milk protein versus soy protein with slight methionine deficiency) on energy balance and adiposity and the role of FGF21 in the response to the protein restricted diets. MethodsThe study investigated in female BalbC mice the behavioural, metabolic and phenotypic responses to 8 weeks feeding a very low (3% energy - P3), moderately low (6% - P6) or adequate (20% - P20) dietary protein diet and evaluated if methionine scarcity, using soy protein (S) vs casein (C), affected these responses. Food intake, body weight, adiposity (assessed by DEXA), were measured throughout the study and body composition determined at the end of the study. Plasma, liver, muscle, adipose tissue and hypothalamus samples were collected for nutrient, hormones and gene expression measurements. ResultsDecreasing dietary casein from 20% to 3% increased energy intake, slightly increased adiposity, and this was exacerbated with methionine-deficient soy protein (figure 1). Lean body mass was reduced in 3% casein fed mice but preserved in all 6% fed mice. The effect on fat mass was limited because energy expenditure was also increased (figure 2). In plasma, low protein diets decreased IGF-1 and increased FGF21 that was related to protein level, protein to carbohydrate ratio and methionine content in the diet (figure 3). Insulin response to an oral glucose test was reduced in soy and low-protein fed mice. Low-protein diets did not affect Ucp1 but increased Fgf21 in brown adipose tissue and Fgf21, Fas, and Cd36 in the liver. In the hypothalamus, Npy was increased and Pomc was decreased only in 3% casein fed mice. ConclusionsReducing dietary protein and protein quality increases both energy intake and energy expenditure resulting only in slight increase in adiposity. In this process FGF21 is probably a signal that responds to a combination of protein restriction and carbohydrate content of the diet. Funding SourcesInstitut National de la Recherche Agronomique, AgroParisTech. Supporting Tables, Images and/or Graphs▪▪▪

Contribuições da pesquisa agropecuária pública para as Indicações Geográficas: estudo de caso do Institut National de la Recherche Agronomique (INRA)

A Indicação Geográfica (IG) é uma forma de proteger o uso do nome geográfico de origem de bens diferenciados. Sua evolução institucional e disseminação no mundo teve a França como protagonista. Esse é um tipo de inovação organizacional, de mercado e institucional, de natureza distinta daquela que geralmente envolve a pesquisa agropecuária pública. O objetivo deste trabalho é analisar como a pesquisa agropecuária, na França, vem interagindo com as IGs. O estudo de caso do Institut National de la Recherche Agronomique (INRA) analisa sua interação com a evolução das IGs (AOC e IGP) na França e em seus rebatimentos internacionais. Procedeu-se a análises dos projetos executados, das parcerias e da produção de CT&amp;I gerada pelo instituto no tema. Distinguiram-se as contribuições do INRA em diferentes domínios institucionais relevantes para o desenvolvimento das IGs. A análise baseada em dados secundários identifica a evolução e o tipo de conhecimentos gerados pela pesquisa agropecuária que contribuem aos fatores de desempenho dos domínios institucionais relacionados às IGs. Os resultados mostram interações do INRA com diversos processos de evolução dos domínios institucionais, revelando o papel da pesquisa agropecuária pública no processo de inovação organizacional relacionado aos sinais de qualidade de bens territoriais.

Meta-analysis of spineless cactus feeding to meat lambs: performance and development of mathematical models to predict dry matter intake and average daily gain

Spineless cactus is a useful feed for various animal species in arid and semiarid regions due to its adaptability to dry and harsh soil, high efficiency of water use and carbohydrates storage. This meta-analysis was carried out to assess the effect of spineless cactus on animal performance, and develop and evaluate equations to predict dry matter intake (DMI) and average daily gain (ADG) in meat lambs. Equations for predicting DMI and ADG as a function of animal and diet characteristics were developed using data from eight experiments. The dataset was comprised of 40 treatment means from 289 meat lambs, in which cactus was included from 0 to 75% of the diet dry matter (DM). Accuracy and precision were evaluated by cross-validation using the mean square error of prediction (MSEP), which was decomposed into mean bias, systematic bias and random error; concordance correlation coefficient, which was decomposed into accuracy (Cb) and precision (ρ); and coefficient of determination (R2). In addition, the data set was used to evaluate the predicting accuracy and precision of the main lamb feeding systems (Agricultural and Food Research Council, Small Ruminant Nutritional System, National Research Council and Institut National de la Recherche Agronomique) and also two Brazilian studies. The DMI, CP intake (CPI), metabolizable energy (ME) intake and ADG increased when cactus was included up to 499 g/kg DM (P<0.001). In contrast, animals fed high levels of cactus (>500 g/kg DM) had a decreased DMI, CPI and NDF intake, but increased feed efficiency (P<0.001) and similar ADG compared with those without cactus addition. The DMI was positively correlated with initial BW, final BW, concentrate and ADG, while it was negatively correlated with cactus inclusion and ME of the diet. On other hand, ADG was positively correlated with DMI, initial and mean BW and concentrate, and it was negatively correlated with cactus inclusion. The two developed equations had high accuracy (Cb of 0.95 for DMI and 0.94 for ADG) and the random error of MSEP was 99% for both equations. The precision of both equations was moderate, with R2 values of 0.53 and 0.50 and ρ values of 0.73 and 0.71 for DMI and ADG, respectively. In conclusion, the developed equation to predict DMI had moderate precision and high accuracy, nonetheless, it was more efficient than those reported in the literature. The proposed equations can be a useful alternative to estimate intake and performance of lambs fed cactus.

Editorial introductions

Editorial introductions

Centennial Fertilization-Induced Soil Processes Control Trace Metal Dynamics. Lessons from a Long-Term Bare Fallow Experiment

Long-term bare fallow (LTBF) experiments with historical sample archives offer unique opportunities to study long-term impacts of anthropogenic activities on mineral soil fractions. In natural agro- and ecosystems, such impacts are often masked by organic matter due to its buffering action and rapid turnover. The 42-plot LTBF trial of INRA (Institut National de la Recherche Agronomique) started in Versailles (France) in 1928 to assess the impacts of prolonged application of fertilizers and amendments on the composition and properties of loamy soils. Here, we established geochemical budgets of major and trace elements on surface samples from 1929 and 2014 for four groups of treatments relevant for developed soil processes. We considered accompanying effects of soil compaction or decompaction due to changing physicochemical conditions over 85 years. Element losses from the surface horizon were quantified via fertilization-induced or -amplified soil processes: clay leaching favored by Na- or K-based fertilization, and lixiviation of major and trace elements in acidic or alkaline soil conditions. Enhanced mineral weathering was shown for acidified and nonamended plots. Conclusions on trace metal migration were confirmed by selected analyses on subsurface horizons. Additional information was provided on specific element inputs via fertilizers and/or diffuse inputs via atmospheric deposition.

An analytical four-component directional brightness temperature model for crop and forest canopies

Measurements of surface thermal infrared (TIR) radiance that are made to extract temperatures display strong directional anisotropy effects. Directional brightness temperature (BT) models that describe this anisotropic behavior of TIR emissions can be applied to separate component temperatures using multi-angle observations. The surface temperature differences that occur between sunlit and shaded areas and the leaf clumping phenomenon jointly affect the directional signatures of out-of-canopy directional BTs. However, these factors are not fully considered in existing directional BT models. This paper therefore extends the FR97 analytical model to 1) a four-component scene containing sunlit and shaded soil and leaves by incorporating the effective emissivity values of the sunlit and shaded parts and 2) row-planted crop and forest canopies by introducing a leaf clumping index. The proposed model was assessed using a synthetic dataset that was generated by the Thermal Radiosity-Graphics Combined Model (TRGM) under various conditions. The evaluation results indicated that the proposed model performed as well as the Scattering by Arbitrarily Inclined Leaves (4SAIL) model over continuous canopies with root mean squared errors (RMSEs) lower than 0.3 °C. Over non-continuous crops and forests, the behavior of the proposed model displayed improved agreement with the TRGM with RMSEs lower than 0.65 °C. The proposed model also displayed a robust performance over both the maize and pine canopies, which was evaluated against the directional anisotropy of measured datasets that were collected at the Huailai remote sensing test site and the Institut National de la Recherche Agronomique (INRA), respectively. From these points, the proposed model has potential for component temperature inversion and rapid assessment of TIR angular effects.