Agricultural and Food Science

Statistical modelling of growth curve for longitudinal data on a feeding trial in goat breeds

Sat, 26 Oct 2024 00:00:00 +0300

The growth curve parameters were estimated extending a linear regression to higher degree polynomial with
attempts to use also the biologically appealing Gombertz function. The data contained monthly weight records from weaning to the age of 14 months of kids in two Omani goat breeds Sahrawi and Jabbali used in a feeding trial assessing the effect of concentrate supplement (14% crude protein). The growth curve parameters were estimated within the fixed effects breed and feed concentrate level (2 or 3% of live body weight) with an extension to mixed models using animals as random effects. The parameters and model contrasting were performed with ML or REML as appropriate with relative comparison relying on AIC and significance testing of estimated parameters. The mixed model analyses were performed with publicly available R software package programs. The fixed effect cubic regression with linear random effect model fitted into the data. The higher level of concentrates improved the immediate post-weaning growth in the same way in the breeds while the subsequent growth curve differed with more pronounced weight increments in the Jabbali breed.

Yield variation and yield potential of organic arable crops in Finland derived from statistical data

Sari Iivonen, Oiva Niemeläinen, Mirva Kokkinen, Lauri Jauhiainen — Sat, 26 Oct 2024 00:00:00 +0300

This study aims to expand and diversify the analysis of crop yields in organic production by utilising the long-term statistical data reported by farmers. We examined the variation of the harvested yields of organic arable crops (season’s ad hoc harvest) on Finnish organic farms and determined the yield potential for different organic crops and in comparison, with conventional counterparts. When comparing median yields per ha, organic yields were on
average 65% of conventional yields. The mean yield difference significantly differed between plant species. Among the analysed crops, faba bean performed best, gaining on average 84% of conventional yields, while organic
cereals attained an average of 54–68% of conventional yields. The ratio of organic and conventional median yields was compared between geographical regions, and significant regional differences were found. The performance of
organic cereals remained stable over the years, but the relative performance of the organic grain legumes, pea and faba bean, depended more on growing conditions. An average yield gap between the best-performing and median
farms was 38% for organic farms and 28% for conventional farms. This indicates that Finnish organic farms have greater potential to improve the yield level than conventional farms.

Improving a dynamic farm level model by coupling empirically estimated pre-crop values with crop rotation optimization

Janne Rämö, Domna Tzemi, Heikki Lehtonen, Taru Palosuo, Pirjo Peltonen-Sainio — Sat, 26 Oct 2024 00:00:00 +0300

The dominance of cereal-based rotations in Finnish agriculture contributes to adverse environmental impacts, and shifting towards diversified cropping systems has been minimal. Since economic viability and profit motives are strong among farmers, there is a need for analysis tools investigating profitability of agronomically feasible, diversified cropping systems and rotations. While there is consensus on pre-crop effects, their impact is unclear and often overlooked in decision-making. We integrate recent empirically estimated pre-crop values into farm models to assess their influence on land use and farm economy and use dynamic optimization to solve the economically optimal crop rotations. The results show that including empirically estimated pre-crop values improves on subjective expert estimates of pre-crop effects and can eliminate the need for additional rotational constraints. Utilizing pre-crop effects consistently over time may lead to significant economic gains. This approach can contribute to sustainable agriculture by encouraging diversification and resilience, even amidst changing climates or novel crops.

Polyphenol composition and antioxidant activity of wine raw materials and pomace from hybrid grapes, aronia, and Japanese quince

Sat, 26 Oct 2024 00:00:00 +0300

Wine pomace contains high amounts of bioactive compounds, mainly polyphenols, with varying concentrations depending on multiple factors. This research aimed to determine differences in the content of polyphenols and antioxidant activity of the wine raw materials and pomace of Japanese quince (‘Rasa’), aronia (seedlings), and grape (‘Hasansky Sladky’) and between harvest years (2021, 2022), as well as between fruits and pomace. Pomace from aronia and Japanese quince was obtained after maceration for 5 and 7 days, respectively, while grape pomace was collected on the day of harvest. The polyphenol content of fruits and pomace varied significantly between harvest years. Aronia had the highest total polyphenol content in fruits (989 mg GAE 100 g^-1) and pomace (1022 mg GAE 100 g^-1), followed by Japanese quince (625 and 722 mg GAE 100 g^-1) and grapes (390 and 481 mg GAE 100 g^-1). Aronia fruits and pomace had higher antioxidant activity. Compared to the fruits, aronia pomace had less chlorogenic acid and neochlorogenic acid. Flavanols were the main polyphenols in the Japanese quince, showing lower content in the pomace when compared to fruits, except catechin content was higher. The content of anthocyanins and flavonols was higher in the rosé wine pomace than in the fruits of grapes.

Time trends of field vegetable yields and yield gaps in northern latitudes using a Bayesian approach

Sat, 26 Oct 2024 00:00:00 +0300

Open-field production of horticultural crops has high economic value in Finland. Profitable production requires sufficiently high yields and good product quality. This study’s objective was to assess the temporal and regional variation in the yield of three field vegetables (carrot, onion, and white cabbage) in Finland. Second, our aim was to quantify the yield gap of these species in their main production regions. The analysis was based on comprehensive statistical data (2012–2021) modelled using a Bayesian approach. Time trends varied between plant species and regions. In carrot, the yield tended to remain similar. In onion, some statistically significant increasing regional time trends were found, whereas in white cabbage the significant time trends were mostly negative, indicating a decreasing yield. The yield gap was largest in onion, but its economic value was highest in carrot. To ensure profitable and sustainable production, it is necessary to reduce the yield variation and yield gaps. More efforts are needed to adapt to climate change and control production risks.