Milk losses and dynamics during perturbations in dairy cows differ with parity and lactation stage

ABSTRACT Milk yield dynamics during perturbations reflect how cows respond to challenges. This study investigated the characteristics of 62,406 perturbations from 16,604 lactation curves of dairy cows milked with an automated milking system at 50 Belgian, Dutch and English farms. The unperturbed lactation curve representing the theoretical milk yield dynamics was estimated with an iterative procedure fitting a Wood model on the daily milk yield data not part of a perturbation. Each perturbation was characterized and split in a development and a recovery phase. Based hereon, we calculated both the characteristics of the perturbation as a whole, and the duration, slopes and milk losses in the phases separately. A two-way analysis of variance followed by a pairwise comparison of group means was carried out to detect differences between these characteristics in different lactation stages (early, mid-early, mid-late and late) and parities (first, second and third or higher). On average, 3.8 ± 1.9 (mean ± standard deviation) perturbations were detected per lactation in the first 305 days after calving, corresponding to an estimated 92.1 ± 135.8 kg of milk loss. Only 1% of the lactations had no perturbations. The average development and recovery rates were respectively −2.3 and 1.5 kg per day, and these phases lasted on average 10.1 and 11.6 days. Perturbation characteristics were significantly different across parity and lactation stage groups, and early and mid-early perturbations in higher parities were found to be more severe, with faster development rates, slower recovery rates and higher milk losses. The method to characterize perturbations can be used for precision phenotyping purposes looking into the response of cows to challenges, or for monitoring applications, for example to evaluate the development and recovery of diseases and how these are affected by preventive actions or treatments.status: publishe

Milk losses and dynamics during perturbations in dairy cows differ with parity and lactation stage

Milk yield dynamics during perturbations reflect how cows respond to challenges. This study investigated the characteristics of 62,406 perturbations from 16,604 lactation curves of dairy cows milked with an automated milking system at 50 Belgian, Dutch, and English farms. The unperturbed lactation curve representing the theoretical milk yield dynamics was estimated with an iterative procedure fitting a model on the daily milk yield data that was not part of a perturbation. Perturbations were defined as periods of at least 5 d of negative residuals having at least 1 day that the total daily milk production was below 80% of the estimated unperturbed lactation curve. Every perturbation was characterized and split in a development and a recovery phase. Based hereon, we calculated both the characteristics of the perturbation as a whole, and the duration, slopes, and milk losses in the phases separately. A 2-way ANOVA followed by a pairwise comparison of group means was carried out to detect differences between these characteristics in different lactation stages (early, mid-early, mid-late, and late) and parities (first, second, and third or higher). On average, 3.8 +/- 1.9 (mean +/- standard deviation) perturbations were detected per lactation in the first 305 d after calving, corresponding to an estimated 92.1 +/- 135.8 kg of milk loss. Only 1% of the lactations had no perturbations. On average, 2.3 kg of milk was lost per day in the development phase, while the recovery phase corresponded to an average increase in milk production of 1.5 kg/d, and these phases lasted an average of 10.1 and 11.6 d, respectively. Perturbation characteristics were significantly different across parity and lactation stage groups, and early and mid-early perturbations in higher parities were found to be more severe with faster development rates, slower recovery rates, and higher milk losses. The method to characterize perturbations can be used for precision phenotyping purposes that look into the response of cows to challenges or that monitor applications (e.g., to evaluate the development and recovery of diseases and how these are affected by preventive actions or treatments)

EU COST Action MP1307 - Unravelling the degradation mechanisms of emerging solar cell technologies

Organic and hybrid perovskite based solar cells have a huge potential to significantly contribute to a clean electricity supply of the future. However, so far they exhibit complex and hierarchical degradation paths and their understanding can only be acquired through the application of complementary chemical and physical characterization techniques. This limited device stability is the main hurdle for a successful and large scale market introduction of these emerging solar cell technologies. Our StableNextSol Action has created a highly interdisciplinary network of laboratories, as well as corresponding industry, overall more than 120 partners, with complementary analytical techniques for the study and understanding of the degradation mechanisms occurring in state-of-the-art devices. Our Action integrates and generates fundamental knowledge and expertise to foster disruptive innovations targeted to mitigate device failure and to propose and develop new concepts for more stable solar cells. Value is added to the entire value chain of photovoltaic research at European and international level, as well as variety decision makers in the public sector by supporting specialisation policy and standards still lacking in this research field. The outcome of the Action will contribute to resolve the global challenges facing the industry and this COST Action initiative has brought together all these expertises and resources to promote the cooperation between different sectors, academia, public authorities and industry

Bifacial Four-Terminal Perovskite/Silicon Tandem Solar Cells and Modules

Ten years after the first paper(1) on the properties of metal halide perovskite solar cells, their efficiency and stability have increased tremendously.(2) It was quickly realized that their application goes beyond the single-junction use. Indeed, perovskite cell technology, by virtue of its tunable bandgap and low sub-bandgap absorption, offers new opportunities for stacking solar cells of different bandgap in a multijunction device to overcome the fundamental Shockley–Queisser (SQ) efficiency limit of a single-junction device. Under AM1.5 irradiation, this limit is 33.7% for the optimal bandgap, and for perovskite with a normally somewhat higher bandgap of 1.55 eV it drops to 31%.(3,4) It is not expected that perovskite will exceed 26% single-junction efficiency.(5) For crystalline silicon solar cells (c-Si), including Auger recombination, the theoretical SQ limit is 29.4%.(6,7) Currently, single-junction silicon solar cells reached an efficiency in the lab of 26.7%;(8,9) while in mass production, solar cells are produced with efficiencies up to about 25%,(10) with main stream efficiencies of about 22%. The latter have been increasing by 0.4%/year, and this trend is expected to continue for a number of years, but it will likely become overly costly to go beyond 24–25%. This efficiency increase has contributed significantly to the steep learning rate, which is the average reduction of Si PV module selling price for every doubling of cumulative shipment, of 39.8%(11) that has been experienced since 2006. Although the manufacturing cost reduction also plays a major role, we expect that when the practical efficiency limits are being approached, the silicon PV industry will not be able anymore to maintain such a learning rate. Aside from module price, the further PV system costs (like installation) to a large extent depend on area and are reduced per unit of power output simply by higher module efficiency. It is because of the possibility that it can help overcome both these performance and cost limitations that metal halide perovskite-on-silicon tandem devices have been under development since 2015(12) and today lead to power conversion efficiencies of over 29%.(13,14