Variability In Production Research Articles

Building Ethiopia’s food security resilience to climate and hydrological change

Abstract Historically Ethiopia’s food security has been sensitive to climatic variability, but changes in future weather and climate could lead to overall reductions and increased variability in agricultural production, without further adaptation. We present an integrated modelling assessment framework which combines climate, crop, and hydrological modelling to quantify future risks to Ethiopia’s food security. We explore the impacts of 2°C and higher climate change scenarios on water availability and crop yields and simulate how future climate shocks may impact Ethiopia’s food. We consider three adaptations to agricultural management practices (improved seed varieties, increased use of nitrogen fertilizer and supplementary irrigation) and quantify their effectiveness in enhancing the resilience of Ethiopia’s food system to climate and hydrological change by 2050. Results show that, without policy intervention, climate change creates a risk of declining Meher season crop yields across Ethiopia. Under the worst climate change scenario, Teff (-12.0%), barley (-6.7%), and wheat (-4.4%) are projected to have the largest decline in average yields, whilst maize (-0.1%) and sorghum (+0.9%) yields are less impacted thanks to more favourable growing conditions. However, the results also indicate that the adaptation options have a bigger beneficial effect than the climate impact. Of the policies evaluated, improved seeds have a relatively greater effect than increased fertilizer use. Supplementary irrigation could help to mitigate increases in crop water requirements under warmer climate conditions and is most effective in drought prone basins and for drought-vulnerable crops. Overall, the results show that locally relevant agricultural policies are necessary to build Ethiopia’s food system resilience to climate and hydrological change by the mid-century.

Using a convection-permitting climate model to assess wine grape productivity: two case studies in Italy

Abstract. The article explores the potential use of climate models to reproduce wine grape productivity at a local scale in Italy. To this end, both single and multiple regression approaches are used to link productivity data provided by two Italian wine consortia with bioclimatic indices. Temperature- and precipitation-based bioclimatic indices are computed using the observational dataset E-OBS, the high-resolution climate reanalysis product SPHERA, the regional climate model CNRM-ALADIN, and the kilometer-scale convection-permitting climate model CNRM-AROME. The multiple regression method outperforms the single regression systematically, enhancing the ability of bioclimatic indices to explain productivity variability. The results show that productivity is strongly tied to temperature-based bioclimatic indices in the area of the Consorzio per la tutela del Franciacorta in northern Italy, while for the Consorzio del Vino Nobile di Montepulciano area in central Italy both temperature- and precipitation-based indices are relevant. Climate models, providing similar results as E-OBS and SPHERA, appear to be a useful tool to explain productivity variance. In particular, the added value of convection-permitting resolution is evident when precipitation-based indices are considered. This assessment shows windows of opportunity for using climate models, especially at a convection-permitting scale, to investigate future climate change impact on wine production.

Meta-analysis of legumes and groundnut production trends and variability in the Global South

This study examined the production trends and variability of grain legumes in the Global South from 2000 to 2022, with a particular emphasis on groundnut yields and regional differences. From 2000 to 2022, global legume production in the Southern Hemisphere increased by approximately 20-30%, driven by rising demand for plant-based proteins and expanded cropping areas in countries like Brazil and Argentina. Improved agricultural practices have further enhanced yields. In contrast, groundnut production experienced a more moderate growth of around 10-15%, influenced by favourable conditions and expanded cultivation in regions such as Argentina and South Africa. While demand for groundnuts remains strong, market fluctuations and competition with other crops continue to shape its production dynamics. The analysis covered a range of legumes, including common beans (Phaseolus vulgaris), cowpeas (Vigna unguiculata), pigeon peas (Cajanus cajan), groundnuts/peanuts (Arachis hypogaea), soya beans (Glycine max), bambara groundnuts (Vigna subterranea), chickpeas (Cicer arietinum), lentils (Lens culinaris), mung beans (Vigna radiata), black gram (Vigna mungo), faba beans (Vicia faba), lablab beans (Lablab purpureus), tepary beans (Phaseolus acutifolius), African yam beans (Sphenostylis stenocarpa), Kersting's groundnut (Macrotyloma geocarpum), lima beans (Phaseolus lunatus), black beans (Phaseolus vulgaris), adzuki beans (Vigna angularis), moth beans (Vigna aconitifolia), horse gram (Macrotyloma uniflorum), broad beans (Vicia faba), winged beans (Psophocarpus tetragonolobus). Regional data revealed significant differences in legume production. In Sub-Saharan Africa, cowpeas and groundnuts are vital, with cowpeas grown over 11.4 million hectares on average yielding 450 kg ha-1, and groundnuts covering 9.1 million hectares with an average yield of 1,007 kg ha-1. Chickpeas and pigeon peas dominate South Asia's production, whereas Latin America features prominent soya bean and groundnut cultivation. Oceania's legume farming is less extensive, focusing on chickpeas and mung beans. Descriptive statistics revealed that Egypt led in groundnut production with an average yield of 3,279.1 kg ha-1 and a low coefficient of variation (CV) of 4.89%, indicating stable production. Conversely, Mozambique had the lowest average yield at 322.9 kg ha-1, with a high CV of 30.23%, reflecting greater variability. The Principal Component Analysis (PCA) identified five principal components explaining 70.9% of the total variance, with the first two components (PC 1 and PC 2) accounting for 51%. Bangladesh and Brazil were major contributors to PC 1, while Algeria and Senegal influenced PC 2. These findings highlight the considerable regional variability in yields and stability in legume production. Future research should address these disparities and enhance resilience through targeted agricultural practices and policy interventions.

Evaluating the influence of heritable, metabolic, and production variables on the postpartum estrus expression of Holstein cows in a voluntary milking system

Evaluating the influence of heritable, metabolic, and production variables on the postpartum estrus expression of Holstein cows in a voluntary milking system

Evaluating the effect of reclaimed asphalt pavement on rubberized hot mix asphalt in pilot projects

The study goal is to evaluate the use of up to 10 % reclaimed asphalt pavement (RAP) by aggregate replacement in rubberized hot mix asphalt-gap graded RHMA-G mixes to identify any significant potential problems for durability. Five pilot projects were built, each including a control RHMA-G (without RAP) and an RHMA-G with 10 % RAP. The mixes were sampled during production and evaluated using volumetric assessment, and performance related tests including stiffness, four-point bending fatigue resistance, fracture resistance measured with the IDEAL cracking test, and rutting resistance. Mix testing results indicate that the addition of 10 % RAP had minor effects on the mechanical properties. With a few exceptions related to the total binder content of the mixes, the effect of the RAP addition was negligible compared to normal production variability. Modeling with CalME, Caltrans mechanistic-empirical asphalt pavement design software and four-point bending testing results, indicated that RAP addition effects on pavement cracking performance were either negligible or comparable to mix-to-mix RHMA-G variability. Regarding constructability, RAP addition did not create any problems. The life cycle assessment completed in the study indicates that the addition of 10 % RAP to the RHMA-G can reduce the greenhouse gasses emissions associated with the RHMA-G production (cradle-to-gate) by up to 5 %.

Assessing Protein Content and Dimer Formation in the Bevacizumab Reference Product and Biosimilar Versions Marketed in Spain

Background: The manufacture of biologics is a complex, controlled, and reproducible process that results in a product that meets specifications. This should be based on data from batches used to demonstrate manufacturing consistency. Ten batches of originator product (Avastin®) were analyzed over a 10-year period. Methods: The β-expectation tolerance intervals and the process capability analysis were proposed to establish the specification limits for determining the acceptance criteria of the final product from the manufacturing process. Protein concentration and dimer content were utilized as CQAs. The analytical similarity between three biosimilars authorized in Spain since 2021 (Vegzelma®, Alymsys®, and Oyavas®) and the originator product were evaluated for both CQAs using two methods: the quality range (QR) method, based on one sample per batch, and the QRML one, which takes into account the inter- and intra-batch variability of the originator product. Results: The results indicate that the two main sources of variation are under control; even the level of variability observed is close to the capability of the analytical method. The manufacturing process, therefore, continues under statistical control. Similarity is demonstrated for the bevacizumab concentration regardless of the approach used, whereas similarity is demonstrated for the dimer content for only one of the biosimilar products. Conclusions: The proposed methodologies allow for the analysis of the consistency of the manufacturing process and the variability from batch to batch.

An Integrated Lean and Six Sigma Framework for Improving Productivity Performance: A Case Study in a Spanish Chemicals Manufacturer

In the pursuit of operational excellence and enhanced competitiveness, a wide range of industries have turned to methodologies such as Lean and Six Sigma; however, in the chemical sector, their application is very limited. This paper presents a Lean Six Sigma framework to identify and reduce sources of variability occurring in the final product composition of a Spanish SME fertilizer manufacturer. The company faced important challenges related to product variability, adversely affecting overall productivity. A real-life case of the Lean Six Sigma implementation was conducted over two years, and its applicability and ability to improve productivity performance were thoroughly assessed. The proposed framework successfully integrated Lean and Six Sigma methodologies, i.e., process mapping (value stream mapping), root cause analysis (Ishikawa cause–effect diagram), project management (SIPOC and DMAIC), and statistical process control, and demonstrated practical benefits for the case company by identifying the key variables affecting product variability and determining their optimal levels. A substantial 50% reduction in the variability of several products and a 42% reduction in material preparation time were achieved. These reductions resulted in a 40% reduction in costs associated with product losses and a 54% reduction in costs from raw material losses.

Exploration of the potential impact of batch-to-batch variability on the establishment of pharmacokinetic bioequivalence for inhalation powder drug products.

Batch-to-batch variability in inhalation powder has been identified as a potential challenge in the development of generic versions. This study explored the impact of batch-to-batch variability on the probability of establishing pharmacokinetic (PK) bioequivalence (BE) in a two-sequence, two-period (2 × 2) crossover study. A model-based parametric simulation approach was employed, incorporating batch-to-batch variability through the relative bioavailability (RBA) ratio. In the absence of batch variability, recruiting a total of 48 subjects in a 2 × 2 crossover study with the reference formulation resulted in a 95% probability of concluding BE. However, this probability decreased to 80% with a 5% batch difference in RBA and further declined to 30% with a 10% batch difference. With a 10% batch difference, the required number of subjects to achieve an 80% probability of concluding BE increased to 84. When considering product differences between the reference and the test formulations, an additional 10% batch difference reduced the study power from 97% to 30% for a T/R bioavailability ratio of 100% in a 2 × 2 crossover study with 48 subjects. As a result, the substantial impact of batch-to-batch variability on the study power and type I error of the PK BE study may pose significant challenges for the development of generic Advair Diskus due to its degree of PK batch-to-batch variability. Therefore, alternative PK BE study designs and guidelines are needed to adequately address the influence of batch-to-batch variability in products like Advair Diskus.

Spatial and temporal variation in crop productivity and relation with soil fertility within upland agroforestry

Agroforestry can be an option of sustainable farming practices for upland communities. However, information of spatial and temporal variation in soil fertility and crop productivity along slopes, which can guide e.g. effective management, such as application of fertilizers, is limited. This study evaluated spatial and temporal variability in crop productivity and soil fertility along slopes in two different fruit tree agroforestry systems in upland areas of north-west Vietnam: (1) longan-mango agroforestry integrating longan (Dimocarpus longan L.), mango (Mangifera indica L.), maize (Zea mays L.), and guinea grass (Panicum maximum Jacq.), and (2) plum agroforestry integrating plum (Prunus salicina L.), maize, and guinea grass. The two systems were established on relatively steep slopes, 37 % and 65 % slope, respectively. Crop performance and soil fertility were measured in different positions relative to the fruit tree-grass rows over 4–5 years and compared with sole-crop maize. The results showed that maize height, grain yield, and leaf nitrogen (N) concentrations were significantly higher at the upslope than downslope side of tree-grass rows. For example, the grain yields were 30–35 % higher at the upslope than downslope side. Regarding soil fertility, there was a tendency that SOC, total N, total phosphorus (P), available P, and available potassium (K) were higher at the upslope than downslope side of tree-grass rows. Thus, the forage grass strips played an important role in trapping N and other nutrients, and enhanced nutrient use efficiency within agroforestry at the steeply sloping study sites. The maize performance and soil fertility in the areas mid-way between two tree-grass rows were comparable to those in sole-crop maize. The results of this study can provide guidance for farmers managing fruit tree agroforestry in north-west Vietnam or other regions with similar cropping, climate, and biophysical characteristics to implement more effective plot management practices on sloping land.

Seasonal resin production in Pinus pinaster Ait. plantations: Dendrometric and meteorological influences

The relationship between dendrometric and meteorological parameters and resin production in Pinus pinaster plantations was studied using data from 90 trees collected between June and October. Resin production was measured every 15 days over a five-month period to explore how environmental factors influence resin production rates. The correlation between diameter at breast height (DBH) ranging from 20 cm to 49 cm and total and average resin production was examined, with the goal to optimize resin harvesting practices and to understand the ecological significance of resin in these plantations. The bi-monthly resin production was tested using the open wound tapping method over a five-month period beginning in June. Through regression models, significant seasonal variability in resin production was observed. Specifically, higher resin yields were recorded in June (354 g) and lower yields in October (53.5 g). The impact of DBH, tree height, basal area, and volume on resin yield were also assessed. Descriptive statistics, correlation, and regression analyses elucidated the relationships between tree metrics, meteorological factors, and resin production. This study contributes new insights into how tree characteristics influence resin production and how this relationship is modulated by seasonal changes. Such findings can inform sustainable forest management practices and improve resin harvesting methods.

Interacción entre la densidad poblacional y fertilización para café robusta en Isidro Ayora, Guayas

The objective of the research was to establish the influence of population density in robusta coffee in relation to chemical and organic fertilization, conducted in the locality of Isidro Ayora, Guayas Province, characterized by a tropical very dry forest life zone over a period of 48 months. The study evaluated the factors of population density (1,333; 1,666; 2,222, and 2,500 plants per hectare) and fertilization plan (chemical and organic) in robusta coffee. The experiment was set up using a Randomized Complete Block Design in a 4 x 2 factorial arrangement (densities x fertilization plan), in a Split-Plot layout, with 8 replications. The results defined that a density of 1,666 plants per hectare, combined with adequate chemical fertilization, proved to be the most efficient factors in terms of robusta coffee production, considering both agronomic and health variables. It is also indicated that the study recommends that higher densities require a more rigorous resource management and more intensive agronomic management in areas similar to the study site.

Application of Machine Learning to Predict the Capacity of Fractured Horizontal Wells in Shale Reservoirs

Shale oil wells typically have numerous volume fracturing segments in their horizontal sections, resulting in significant variability in productivity across these segments. Conventional productivity prediction and fracturing effect evaluation methods are challenging to apply effectively. Establishing a stable and efficient intelligent productivity prediction method using machine learning is a promising approach for the effective development of shale oil reservoirs. This study is based on geological data, fracturing records, and a production database of 91 production wells in a shale oil reservoir in a specific area. Fourteen key parameters affecting productivity were selected from geological and engineering perspectives, and the recursive feature elimination method based on support vector machines identified five optimal main controlling factors. Three machine learning methods—decision tree, random forest, and gradient boosting decision tree (GBDT)—were used to model productivity prediction, with root mean square error (RMSE) employed to evaluate model performance. The study results indicate that formation coefficient, cluster spacing, treatment volume, sand volume, and fracturing segment length are the main controlling factors influencing productivity in fractured horizontal wells. Among the models, the random forest algorithm with bootstrap sampling produced the most stable prediction results, achieving a prediction accuracy of 94% and an RMSE of 0.934 on the test set, outperforming the decision tree and GBDT models in terms of minimum RMSE on the test set.

Quantification and histochemical localization of secondary metabolites during development in Annona muricata L. (Annonaceae)

Histolocalization and quantification of secondary metabolites established the occurrence of alkaloids, phenols and acetogenins in various plant organs of A. muricata at different stages of plant growth.Annona muricata L. possesses broad assemblage of ethno-pharmaceutical and therapeutic upsides ascribed to biosynthesis of secondary metabolites. Currently, the bioactivity is characterized by the production of acetogenins (ACGs), and also by the biosynthesis of alkaloids, primarily benzylisoquinolines derived from tyrosine and phenolic compounds. As a result of high variability of metabolite production in A. muricata, the present study evaluated the histochemical analysis of various plant parts at different developmental stages of growth. Presences of phytometabolites were determined using in-situ histochemical localization of alkaloids, phenolic compounds and acetogenins, while its estimation employing spectroscopic quantification techniques to understand structure, development, time-course deposition, content and distribution of secondary phytoconstituents. Study revealed distinct presence of secondary metabolites in cells and tissues of all plant organs in various intensities and patterns. Alkaloids and acetogenins occurred mostly in secretory cavities or idioblast cells while sparsely associated with other cells or tissues. Phenolic compounds emerged widely, with no confined distribution patterns occurring in storage cells and tissues. Quantitative analysis revealed highest accumulation of alkaloids, phenols and acetogenins in mature root-barks, mature unripe fruit rind and mature leaf respectively. Secondary metabolites generally occurred in young stages at low concentrations as compared to matured growth stages of plant parts. Such in-situ histochemical and biochemical approach will help in identifying the cells and tissues responsible for synthesis, storage and biological effects of potential secondary metabolites which could be further used for culturing and enhancing its production with biotechnological aids.

Dynamics of CO2 fluxes and environmental responses in a Poplar plantation

Forest plantations cover a large percentage of global forest landscapes contributing significantly to carbon sequestration. By using continuous eddy covariance technique, we observed net ecosystem CO2 exchange (NEE), gross primary production (GPP), ecosystem respiration (ER), and meteorological variables from August 2018 to December 2019 in a Poplar plantation. The Poplar plantation ecosystem was a carbon sink overall, with high carbon uptake in growing season and limited uptake/emission in non-growing season. The annual cumulative NEE, GEP, and ER were −763.61, 1542.19, and 778.58 g C m−2 yr−1, respectively. Photosynthetically active radiation (PAR) significantly influenced NEE both at half-hourly and daily scale (P < 0.01 for both), while relative humidity (RH) and vapor pressure deficit (VPD) only significantly affected NEE at half-hourly scale (P < 0.01). The prevailing wind direction throughout 2019 was southeast and it varied between seasons. Southeast wind was the prevailing wind direction in summer and winter, while southwest and northeast wind were the dominant wind direction in spring and autumn, respectively. Our results highlight that polar plantations play an important role in storing carbon, and that understanding meteorological conditions is crucial in investigating ecosystem-atmosphere interactions and their impacts on carbon cycling.

Sensory dimensions of typicality and association with affective-related responses: A study on local multifloral honey

Local foods offer benefits for the sustainability of the food supply chain, yet they face challenges due to variability in production and market saturation. This highlights the importance of strategies to enhance their value. Among local foods, multifloral honey is one of the products most closely tied to the territory. A comprehension of how multifloral honey is structured from a sensory standpoint can prove advantageous in enhancing its recognition and valorization among consumers. The present study aimed to promote multifloral honey in the case of a local area, identifying typical examples of multifloral honey and their sensory determinants, and identifying the association among sensory attributes and affective-related responses of consumers. Thirty samples of multifloral honey were collected from a target local area (Trento province - Italy). Experts in honey sensory evaluation (n = 47) performed a rapid descriptive task (check-all-that-apply questions) and a categorization task (typicality evaluation). Six samples representative of the category sensory space were selected for consumer evaluation. Consumers recruited from the local area (n = 131) rated liking and elicited post-consumption emotional product associations. The results unveiled the sensory representation of the multifloral honey category, with samples arrangement in accordance with category typicality. The study defined the sensory characteristics associated with typicality of the multifloral honey from the target local area and identified local consumers' affective-related responses to the features that define the typicality. Beyond the honey realm, this approach can represent a model of a methodological approach for studying the enhancement of local foods that exhibit relevant sensory variability.

Assessing the Climatological Characteristics of Observed and Simulated Seasonal Onset of Precipitation Over Southern and Eastern Africa

ABSTRACTPrediction of seasonal onset is crucial to agriculture in southern and eastern Africa. Here, we applied two definitions of onset, namely meteorological and agricultural (crop‐germination), to evaluate CMIP6 models through the lens of rainfall onset over representative maize agricultural regions of South Africa, Tanzania, Malawi and Zambia. We use the ERA5 reanalysis as a proxy for observations, and robust regression to calculate a statistical comparison of the onset definitions for the period 1979–2021. Evaluation of ERA5 reanalysis shows similar magnitude and pattern as gauge based MSWEP. Our results show that, for meteorological onset, Johannesburg, with a subtropical highland climate, experienced earliest onset after 23 December; and an increasing trend (later onset) but not statistically significant (p = 0.2). Over Bethlehem, which has continental climate, the earliest onset date was after October 9 and an increasing interannual variability since 2000 is noted. The standard deviation of onset dates across the regions shows an East‐Central‐South gradient. We also found that the crop‐germination onset definition shows earlier onset of seasonal rains, it differs considerably across regions, and has higher interannual variability, in comparison with the meteorological definition. Over Lilongwe, Mbeya and Lusaka, late meteorological onset with a weak positive and insignificant trend is observed. The CMIP6 model's representation of onset trend differs from reanalysis data, with inter‐model differences. Late meteorological onset is underestimated by GFDL‐CM4 and MPI while INM5, MPI and NorESM overestimate the observed earliest onset. The largest bias is shown by INM and MPI which simulate earliest and latest onset as 190 (07 January) and 206 (23 January) respectively. In addition, models often fail to simulate sufficient precipitation to produce onset for seed germination and crop development. The ACCESS model showed an insignificant trend (p value = 2) and later onset over Lilongwe, an insignificant trend (p value = 0.9) over Lusaka, and an earlier onset over Mbeya. Using the agricultural onset definition, over Bethlehem, all the models and the ERA5 reanalysis did not produce enough precipitation to meet onset conditions. We suggest that rainfall onset studies use several definitions or metrics of onset and that the choice of metric be informed by the research question. Using such an ensemble of onset metrics contributes to a better understanding of variability and uncertainties in agricultural productivity.

Associations between a range of enteric methane emission traits and performance traits in indoor-fed growing cattle.

Despite the multiple definitions currently used to express enteric methane emissions from ruminants, no consensus has been reached on the most appropriate definition. The objective of the present study was to explore alternative trait definitions reflecting animal level differences in enteric methane emissions in growing cattle. It is likely that no single methane trait definition will be best suited to all intended use cases, but at least, knowing the relationships between the different traits may help inform the selection process. The research aimed to understand the complex interrelationships between traditional and novel methane traits and their association with performance traits across multiple breeds and sexes of cattle; also of interest was the extent of variability in daily enteric methane emissions independent of performance traits like feed intake, growth and live-weight. Methane and carbon dioxide data were collected using the Greenfeed system on 939 growing crossbred cattle from a commercial feedlot. Performance traits including feed intake, feeding behavior, liveweight, live animal ultrasound, subjectively scored skeletal and muscular traits, and slaughter data were also available. A total of 13 different methane traits were generated, including (average) daily methane production, five ratio traits and seven residual methane (RMP) traits. The RMP traits were defined as methane production adjusted statistically for different combinations of the performance traits of energy intake, liveweight, average daily gain and carcass weight; terms reflecting systematic effects were also included in the fixed effects linear models. Of the performance traits investigated, liveweight and energy intake individually explained more of the variability in methane production than growth rate or fat. All definitions of RMP were strongly phenotypically correlated with each other (>0.90) as well as with methane production itself (>0.86); the RMP traits were also moderately correlated with the methane ratio traits (>0.57). The dataset included heifers, steers and bulls; bulls were either fed a total mixed ration or ad lib concentrates. When all sexes fed total mixed ration were compared, bulls, on average, emitted the most enteric methane per day of 269.53g, while heifers and steers produced 237.54g and 253.26g, respectively. Breed differences in the methane traits existed, with Limousins, on average, producing the least amount of methane of the breeds investigated. Herefords and Montbéliardes produced 124.50g and 130.77g more methane per day, respectively, than Limousins. The most efficient 10% of test-day records, as defined by daily methane independent of both energy intake and liveweight emitted, on average, 54.60g/d less methane than animals that were average for daily methane independent of both energy intake and liveweight. This equates to 6.5kg less methane production per animal over a 120-day finishing period for the same feed intake and liveweight.

Productivity of grafted papaya growing under open environment in the Mexican pacific

ABSTRACT The phytosanitary problems and the complex floral biology influence the fruit quality and productivity of papaya. Use of grafting mitigates adverse aspects, becoming a complementary activity of crop. The objective of this study was to evaluate the agronomic behaviour of grafted papaya plants. Two experiments were carried out. In the first experiment, the treatments were derived from six rootstock/scion combinations and four controls, based on commercial genotypes. In the second experiment, four rootstocks and two genotypes formed eight rootstock/scion treatments, and two controls were used. The morphological variables as well as the qualitative and productive variables of fruits were recorded. Results showed that plant height was maintained or reduced in some treatments, whereas stem girth and leaf numbers in grafted treatments were increased. The fruit quality was not influenced by grafting. In the productivity, the grafted plants showed higher fruit production. For an example, the Rootstock 'MSXJ' × Scion 'Maradona' and the Rootstock 'BS2' × Scion 'Maradol'>40 kg · plant−1 and almost 9 kg · m–2, respectively; and the Rootstock 'Robusta' × Scion 'Maradol' treatment was higher than the other treatments, reaching 38.39 kg · plant–1 and 8.53 kg · m–2, in Experiments 1 and 2, respectively. Grafting on papaya positively changed the morphological variables, increased the number of fruits per plant in grafted plant treatments, as well as yield per area, surpassing controls by 25% and 22% in both experiments, respectively.

Assessment of the Production Variability and Composite Performance Index for Conventional and High Reclaimed Asphalt Pavement Balanced Mix Design Mixtures

The balanced mix design (BMD) concept enables the design of engineered mixtures containing conventional and high reclaimed asphalt pavement (HRAP) contents, moving beyond the constraints of traditional volumetric design methodologies. During production, the designed mixture undergoes verification and potential modifications at the plant to accommodate actual production and field circumstances, regardless of the mix design method. This study assessed the impact of production and associated performance variability on a volumetrically designed control mixture and five mixtures designed with the BMD concept. This investigation showed relatively precise gradation control, but exceedances of volumetric property tolerances were observed in BMD-optimized mixtures during production. Performance, including durability, cracking, and rutting susceptibility, was evaluated using the Cantabro test, indirect tensile cracking test (IDT-CT), and asphalt pavement analyzer (APA) test, respectively. Test results uncovered that produced mixtures may become unbalanced. Observations from the Cantabro test and IDT-CT highlighted the necessity and effectiveness of employing the BMD for HRAP mixtures. The potential aging effect introduced during the reheating process may compromise durability and cracking resistance. In addition, a three-dimensional plot with a revised composite performance index (CPIR) was used to optimize the process of evaluating the mixture “balance” status among multiple primary performances. It revealed that almost all produced HRAP mixtures demonstrated a well-balanced status. Finally, agencies can use the CPIR as part of their acceptance program for BMD mixtures to determine a pay factor for possible bonuses or penalties.

An Investigation of Indoor Environment Quality on Occupants’ Thermal Responses, Health, and Productivity: A Study Based on Physiological Data in Occupied Office Space

This study explores the impact of Indoor Environment Quality (IEQ) on the health and productivity of office workers in an office building in Fujisawa, Kanagawa, Japan. Previous studies have shown that IEQ can affect the physiological responses of occupants, such as of skin temperature, heart rate, and metabolic rate, which are indicators of health and productivity. However, most studies took place in controlled laboratory environments, which may not accurately represent real-life experiences. The study collected subjective and objective data from actual occupied office space, including on perceptions of IEQ, health, and productivity, and measurements of IEQ parameters such as on the thermal environment, light environment, indoor air quality, and acoustics. The study used correlation and linear regression methods to examine the relationship between IEQ, physiological data, and subjective responses to health and productivity. The stable thermal environment and low physical intensity of office work may contribute to the weak correlation between physiological data, thermal responses, and health–productivity variables. The results of this study can provide insights into how IEQ affects the psychological responses, well-being, and performance of office workers in real-world settings.