TFP Bioeconomy Impact post Covid-19 on the agricultural economy.

BACKGROUND: This research was focused on measuring the TFP bioeconomy post-Covid-19 in six regions of the world. METHODS: The panel data was organized with FAO Statistics data. Linear programming with an enveloping data analysis (DEA) approach was used to measure the Malmquist TFP indices to determine the inter-annual productivity and technical efficiency changes by region. RESULTS: The results show that the effect of Covid-19 on the bioeconomy productivity during the period 2012-2021 on average decreased by 11.6%. This effect was explained by the decomposition of the productivity change into the changes in technical efficiency. The workers decreased their efficiency by 11.7%. In the Northern American region, it decreased by 21.6%, in the Southern European region by 10.1, and in Western Europe by 11.7%. CONCLUSION: The results show a downward trend that was affected in the year 2019 by Covid-19, however, it was possible to recover in the following year. One of the conclusions of these results is the effect of the immediate strategies that the governments of the region implemented. This effect was a little slower in the North American, Southeastern, and Eastern European regions. Finally, it is concluded that the measures implemented by the governments in the studied regions had an increasing effect in conditions of variable scale returns. In other words, the companies that remained on a constant scale decreased.

Periodical crossing of the laboratory population with the natural population would improve fitness in S. sunia ( Lepidoptera: Noctuidae).

Background: The research focused on evaluating the biological and reproductive parameters of the species Spodoptera sunia with the introduction of field genetic material, in the Noctuid Insect Breeding Laboratory. Methods: The experiment consisted of three treatments and three repetitions involving 30 individuals each. Field-collected S. sunia population was reared in the laboratory under semi-controlled conditions of temperature and humidity for three generations. The progeny of the third generation was crossed with the laboratory population and the resulting progeny was observed for growth and reproductive fitness. Results: The results revealed that the hybrid progeny (T3) has a sex ratio (F: M) of 0.82, as against 1.22 and 0.76 observed in the field (T1) and lab populations (T2) respectively. The T1 females oviposited 196 egg masses as against 160 and 59 egg masses by T3 and T2 females respectively. The larval growth was more in hybrid progeny with shorter larval duration. However, no variation was observed in the incubation and pupal periods. Conclusions: Since the most optimal results were obtained in T2 and T3, it is recommended to introduce genetic material every six months to maintain a good laboratory population of the insect host under study and better breeding of its natural enemies.

Inputs-Oriented VRS DEA in dairy farms.

Background: This paper aims to examine the efficiency of Mexico's dairy farms within its four regions of Tlaxcala Stated. Methods: The Envelopment Data Analysis (DEA) applied to the variable returns to a scale model (VRS) for the year 2020. Also, Examine the statistical accuracy of efficiency estimation using bootstrap resampling techniques. The results reveal that Tlaxcala's dairy farm efficiency, on the other hand, was adversely influenced by three inputs (costs): cost of investment in livestock, the total annual cost for feeding, reproduction, diseases and treatments, preventive medicine, sanitation, milking, fuel, and total labor. Results: The efficiency distribution among farms using VRS, CRS, and FDH technologies reveals varying patterns. Under VRS and CRS, the majority of farms exhibit high efficiency within the 0 to less than 0.2 range, while FDH displays a broader distribution, with notable efficiency at 1 and across various ranges. These findings highlight the diverse landscape of efficiency levels across different technological approaches within the agricultural sector, offering valuable insights for optimization strategies and resource allocation. Conclusions: The utilization of Bootstrap methodology enhances the reliability of efficiency assessments by providing robust statistical techniques that accommodate non-normal data distributions. By incorporating Bootstrap, decision-makers can obtain more accurate estimates of efficiency levels and confidence intervals, thereby making informed decisions regarding resource allocation and optimization strategies within the agricultural sector. As part of the study, provided The Policy suggestions.

Frontier model of the environmental inefficiency effects on livestock bioeconomy.

Background: This work was focused on measuring environmental inefficiency in Mexican dairy farms, considering climate change variables related to the emission of greenhouse gases (GHG) and planetary geomagnetic activity. Methods: The applied methodology measures the eco-efficiency of Mexican dairy farms using the empirical application of a stochastic frontier model of the bioeconomy. The productive sector of the bioeconomy studied was the eco-intensification of the livestock production system (dairies). The environmental inefficiency effect was assumed to be a distribution-independent truncation of a normal distribution with constant variance, while the mean was a linear environmental function of the observable variable. Results: The results showed that the coefficients of the frontier model were highly significant, highlighting the investment in livestock (50%). The inefficiency model had an impact on climate variation with greenhouse gas emissions CH4 (1.96%). The results of the environmental technical efficiency in geometric average were 81.28%. The producers that reached the border with a technical efficiency equal to 1 are the references for the rest, marking the relative technical efficiency. Conclusions: It was concluded that the coefficients in the model were very significant, showing the level of investment in livestock (50%). The low-performance model estimates the impact of climate change on GHG emissions CH4 (1.96%) explaining the trend of increasing GHG emissions, keeping in view that the management of food and cattle during the study period were affected by summer feeding, which allowed considering the activity of GHG emissions. According to the results, the geometric mean environmental performance of engineering is 81.28%.

Diversity of functional edaphic macrofauna in Musa acuminata x Musa balbisiana (AAB) agroecosystems.

Background: This study focused on evaluating the diversity and richness of the edaphic macrofauna in eight banana farms in the western zone of Nicaragua. Methods: The sampling design was random and descriptive, it was divided into two phases, the first was the collection of the sample, and the second was the classification, coding, and storage of the extracted macrofauna populations. The sampling method employed included the extraction of soil and litter samples. Soil samples were collected using a wooden frame (monolith), with each sample weighing approximately 1 kilogram and taken from a depth of 0.20 cm. Litter samples were collected from the soil surface. A total of 80 samples were collected, with 40 soil samples and 50 litter samples obtained across the 8 plantain farms. Results: The results showed that the relative abundance of biodiversity was higher in the 0-20 cm soil depth stratum than in the branch and leaf biomass strata. The values of the diversity indices of Simpson's Dominance, Shanon, Margalef, and Equity were in the normal range, with a tendency towards low diversity. Likewise, in the richness of species, the Dominance or most abundant genus were earthworms (Oligochaeta) and Hymenoptera ( Solenopsis, Leptothorax, Camponotus, Pheidole), indicating the directly proportional relationship, that is to say, that the greater the number of earthworms the production increases and the greater the number of Hymenoptera it decreases, confirmed with the Pearson correlation coefficient with a reliability of 95%. Conclusions: It was concluded that based on the estimates of the diversity indicators, two detritivore genus (earthworms and Hymenoptera) were the ones with the more dominance, being important in the production of the banana agrosystem due to the decomposition of organic matter and its nutritional contribution to the plant. We observed a direct correlation with earthworms and an indirect relationship with Hymenoptera.