Growing cocoa in semi-arid climate and the rhythmicity of stem growth and leaf flushing determined by dendrometers.

This study investigated the performance of cocoa trees within an irrigated cocoa plantation situated in the semi-arid region of Bahia, Brazil. Two treatments were compared: "full sun," where cocoa trees were not shaded, and "shade," where trees were covered with a shading net absorbing 30 % of the radiation. The number of leaves and the leaf area index (LAI) were assessed using destructive method on 8 trees. In addition, new flushing of leaves, categorized into four flushing stages, were assessed visually on a weekly basis during two years. The variation of the stem diameter was measured using dendrometer sensors (n = 12 trees). Yield parameters like dry bean yield and number of fruits (healthy and aborted) were assessed on 40 trees per treatment. Both treatments, performed well in the semi-arid region. Generative parameters, such as dry bean yield (±2,000 kg/ha), fruit healthy and abortion rate per plot, were unaffected by full sun and shade treatments. The treatments showed high fruit abortion rates of (±60 %), showing that there's still much room for yield optimization. Additionally, stem diameter of the trees showed a significant reduction of the stem growth (daily increase of stem diameter) and maximum daily shrinkage (daily variation of stem diameter) during the flushing of new leaves. This implies that the emergence of new leaves significantly influences stem growth, consequently affecting the fruits which are growing on the stem. This assumption was corroborated by the significantly increased fruit abortion rate during the flushing of new leaves (stages 1 & 2). These findings highlight the potential of dendrometers to quantify this effect what can be used in future to optimize management practices. By doing so, more effective strategies can be developed to enhance cocoa yield and overall productivity in semi-arid regions.

Review: Application and Prospective Discussion of Machine Learning for the Management of Dairy Farms.

Dairy farmers use herd management systems, behavioral sensors, feeding lists, breeding schedules, and health records to document herd characteristics. Consequently, large amounts of dairy data are becoming available. However, a lack of data integration makes it difficult for farmers to analyze the data on their dairy farm, which indicates that these data are currently not being used to their full potential. Hence, multiple issues in dairy farming such as low longevity, poor performance, and health issues remain. We aimed to evaluate whether machine learning (ML) methods can solve some of these existing issues in dairy farming. This review summarizes peer-reviewed ML papers published in the dairy sector between 2015 and 2020. Ultimately, 97 papers from the subdomains of management, physiology, reproduction, behavior analysis, and feeding were considered in this review. The results confirm that ML algorithms have become common tools in most areas of dairy research, particularly to predict data. Despite the quantity of research available, most tested algorithms have not performed sufficiently for a reliable implementation in practice. This may be due to poor training data. The availability of data resources from multiple farms covering longer periods would be useful to improve prediction accuracies. In conclusion, ML is a promising tool in dairy research, which could be used to develop and improve decision support for farmers. As the cow is a multifactorial system, ML algorithms could analyze integrated data sources that describe and ultimately allow managing cows according to all relevant influencing factors. However, both the integration of multiple data sources and the obtainability of public data currently remain challenging.

Effect of milking stall dimensions on upper limb and shoulder muscle activity in milkers.

Increasing societal awareness for animal welfare can promote changes in legislation. Some of these changes may also affect the person that interacts with the animal in a shared workspace, such as in milking stalls. Swiss milking stalls were designed many years ago, when cows were smaller than they are today. A recent animal-based study indicated that welfare decreased in cows exposed to restricted space allowance in milking stalls, which had resulted from increasing body size without adjustment of milking stall dimensions. However, changing the milking stall dimensions without considering the milker may be detrimental. For many years, health issues, particularly of the upper limb and shoulders, have affected milking personnel. The current study investigated the effect of large and standard milking stall dimensions on muscle activity in milkers (as a measure of workload) during milking. This assessment is fundamental to ensure that legislation improving animal welfare does not jeopardize human health. The study took place in an experimental milking parlor that allowed for size adjustment of the individual milking stall. Nine milkers performed 2 shifts of milking in a herringbone and 2 shifts in a side-by-side milking parlor. The milking stall dimensions were large on one side and standard on the other side of the parlor; the 2 sides were switched between milking shifts. We used surface electromyography to monitor bilateral muscle activity of forearm (flexor carpi ulnaris), arm (biceps brachii), and shoulder (deltoideus anterior; upper trapezius) muscles. Statistical analysis was performed separately for the herringbone and the side-by-side parlor for each muscle using mean and maximum muscle activity as the target variables in a linear mixed-effects model. The analysis showed that the different milking stall dimensions did not consistently affect activity of the measured muscles. Our results suggest that milking stall dimensions are not a primary risk factor for poor ergonomics in parlor workers.

Lower working heights decrease contraction intensity of shoulder muscles in a herringbone 30° milking parlor.

Musculoskeletal disorders have been a main concern in milkers for many years. To improve posture, a formula was developed in a previous study to calculate ergonomically optimal working heights for various milking parlor types. However, the working height recommendations based on the formula for the herringbone 30° parlor were broad. To clarify the recommendations for the optimal working height, we investigated the effect of working height on upper limb and shoulder muscle contraction intensities. We evaluated 60 milking cluster attachment procedures in a herringbone 30° milking parlor in 7 men and 9 women. Specifically, we examined the effect of working height on muscle contraction intensity of 4 arm and shoulder muscles bilaterally (flexor carpi ulnaris, biceps brachii, deltoideus anterior, and upper trapezius) by using surface electromyography. The working heights (low, medium, and high), which reflect the ratio of the subject's height to the height of the udder base, were used in the milking health formula to determine and fit individual depth of pits. Data were evaluated for each muscle and arm side in the functions holding and attaching. Statistical analysis was performed using linear mixed effects models, where muscle contraction intensity served as a target variable, whereas working height coefficient, sex, subject height, and repetition were treated as fixed effects, and repetition group nested in working height nested in subject was considered a random effect. Contraction intensities decreased with decreasing working height for the deltoideus anterior and upper trapezius, but not for the flexor carpi ulnaris or the biceps brachii muscles in both holding and attaching arm functions. We found that milking at a lower working height reduced muscle contraction intensities of the shoulder muscles. Women showed higher contraction intensities than men, whereas subject height had no effect. The study demonstrated that a lower working height decreased muscular load during milking. These lower working heights should be used within the recommendations made by the milking health formula for the herringbone 30°. Working heights could be adjusted effectively for milkers of varying body height. Future studies should therefore use the milking health formula as a tool to objectively compare and improve the accuracy of the working height coefficients.