Variability In Production Research Articles

Evaluating MULTIOBS Chlorophyll-a with Ground-Truth Observations in the Eastern Mediterranean Sea

Satellite-derived observations of ocean colour provide continuous data on chlorophyll-a concentration (Chl-a) at global scales but are limited to the ocean’s surface. So far, biogeochemical models have been the only means of generating continuous vertically resolved Chl-a profiles on a regular grid. MULTIOBS is a multi-observations oceanographic dataset that provides depth-resolved biological data based on merged satellite- and Argo-derived in situ hydrological data. This product is distributed by the European Union’s Copernicus Marine Service and offers global multiyear, gridded Chl-a profiles within the ocean’s productive zone at a weekly temporal resolution. MULTIOBS addresses the scarcity of observation-based vertically resolved Chl-a datasets, particularly in less sampled regions like the Eastern Mediterranean Sea (EMS). Here, we conduct an independent evaluation of the MULTIOBS dataset in the oligotrophic waters of the EMS using in situ Chl-a profiles. Our analysis shows that this product accurately and precisely retrieves Chl-a across depths, with a slight 1% overestimation and an observed 1.5-fold average deviation between in situ data and MULTIOBS estimates. The deep chlorophyll maximum (DCM) is adequately estimated by MULTIOBS both in terms of positioning (root mean square error, RMSE = 13 m) and in terms of Chl-a (RMSE = 0.09 mg m−3). The product accurately reproduces the seasonal variability of Chl-a and it performs reasonably well in reflecting its interannual variability across various depths within the productive layer (0–120 m) of the EMS. We conclude that MULTIOBS is a valuable dataset providing vertically resolved Chl-a data, enabling a holistic understanding of euphotic zone-integrated Chl-a with an unprecedented spatiotemporal resolution spanning 25 years, which is essential for elucidating long-term trends and variability in oceanic primary productivity.

Características socioproductivas y económicas de productores de chile criollo de Teticic, Olinalá, Guerrero

The chilli is a crop of cultural, economic and social importance for Mexico, it is produced and consumed throughout the national territory. The objective of analyzing the socio-productive and economic characteristics of criollo chilli producers in the community of Teticic, Olinalá, Guerrero, México, in 2021, an interview with social, economic and productive variables was applied to 39 chilli producers in the community, the information was concentrated in Excel and a hierarchical cluster analysis was carried out in the statistical program SPSS version 21 where a factor analysis was applied for the selection of variables, the Ward method and the Euclidean distance were used, which allowed to obtain five groups of producers. Chilli cultivation is a subsistence agricultural system presided over mainly by men with an average age of 47 years with basic education, dedicated mainly to agriculture with an average of 21 years of experience, using family labor. This crop faces a series of productive, commercial, post-harvest, service and support problems from the government that limit its productivity and could put at risk the conservation of chilli crioles seeds.

Co-mast: Harmonized seed production data for woody plants across US long-term research sites.

Plants display a range of temporal patterns of inter-annual reproduction, from relatively constant seed production to "mast seeding," the synchronized and highly variable interannual seed production of plants within a population. Previous efforts have compiled global records of seed production in long-lived plants to gain insight into seed production, forest and animal population dynamics, and the effects of global change on masting. Existing datasets focus on seed production dynamics at the population scale but are limited in their ability to examine community-level mast seeding dynamics across different plant species at the continental scale. We harmonized decades of plant reproduction data for 141 woody plant species across nine Long-Term Ecological Research (LTER) or long-term ecological monitoring sites from a wide range of habitats across the United States. Plant reproduction data are reported annually between 1957 and 2021 and based on either seed traps or seed and/or cone counts on individual trees. A wide range of woody plant species including trees, shrubs, and lianas are represented within sites allowing for direct community-level comparisons among species. We share code for filtering of data that enables the comparison of plot and individual tree data across sites. For each species, we compiled relevant life history attributes (e.g., seed mass, dispersal syndrome, seed longevity, sexual system) that may serve as important predictors of mast seeding in future analyses. To aid in phylogenetically informed analyses, we also share a phylogeny and phylogenetic distance matrix for all species in the dataset. These data can be used to investigate continent-scale ecological properties of seed production, including individual and population variability, synchrony within and across species, and how these properties of seed production vary in relation to plant species traits and environmental conditions. In addition, these data can be used to assess how annual variability in seed production is associated with climate conditions and how that varies across populations, species, and regions. The dataset is released under a CC0 1.0 Universal public domain license.

The Impact of R&D and Innovation on National Income

In this study we empirically investigate the influence of several indicators of R&D and innovation on GDP for OECD countries by utilizing an unbalanced panel for the years of 1995-2021. Two distinct measures of patent applications, two different measures of trademark applications, researchers in R&D, and technicians in R&D are the proxies for R&D and innovation. We also added inflation, productivity, investment, and education into our model as control variables. Selection between fixed effect model and random effect model is made via Hausman test. According to the estimation results, we identified statistically significant positive impact of two distinct measures of patent applications, two different measures of trademark applications, researchers in R&D, and technicians in R&D variables on gross domestic product for the sample of OECD countries during the period of 1995-2021. Regarding the control variables, whenever they are statistically significant then we observed positive coefficient estimations for the variables of productivity, investment, and education and negative coefficient estimation for the variable of inflation.

Evaluating the impact of climatic factors and variability on rice production over varied seasons in irrigated rice system of peninsular India through Empirical approach

Rice is the principle and staple food crop of peninsular India, and its production is highly sensitive to climatic factors and variability. The climate change may cause considerable negative impact on rice productivity that could jeopardize food security and livelihood of smallholders. The present study investigates how the changes in mean and variability of climatic factors may impact rice yield during various rice seasons throughout the year. Panel data of districts of Cauvery Delta Region (CDR) from 2000-2022 was used for the analysis and fixed-effects regression with Panel-Corrected Standard Errors (PCSE) model was employed for all three seasons viz, Kuruvai, Samba and Navarai. The results of the study showed that temperature and rainfall significantly impacted rice yields directly and demonstrated the existence of nonlinear relationship between climatic factors and yield. It also revealed intricate, season-specific correlations between rice productivity and environmental variables. The time trend used in the study indicated a significant positive increase in yield continuously through adoption of yield improvement technologies such as high yielding, resistant and climate resilient varieties. This study helps researchers and policymakers in devising proper adaptation strategies to ensure food system security in the region when the climate conditions change and helpful for predicting future productivity.

Investigation of the Variation of Ocean Color and Phytoplankton Functional Types in the Bay of Bengal

The monthly and inter annual variability of Ocean color products and Phytoplankton Functional Types (PFTs) are examined in the Bay of Bengal (BoB) from satellite data (2000-2020). Monthly Chlorophyll-a, Color Dissolved Organic Matter (CDOM), Photosynthetic Active Radiation (PAR) and Suspended Particulate Matter (SPM) data of merged satellites are used in this study. Ten PFTs (Microplankton, Nanoplankton, Picoplankton, Diatoms, Green Algae, Dinoflagellates, Prymnesiophytes, prokaryotes, pico-eukaryotes, Prochlorococcus; 3 phytoplankton size classes (PSC), 7 phytoplankton taxonomic compositions (PTC) are derived from individual monthly Chlorophyll-a. All data are averaged over the BoB region. We have found that the average Chlorophyll-a was decreasing (0.35 mg/m3 to .25 mg/m3) from the year of 2000 to 2020; whereas CDOM shows a sinusoidal relation from the year of 2000 to 2020; PAR has showed a decrease until 2014 then increase; SPM shows a rapid exponentially increasing trend from 2013. The highest Chlorophyll-a is found in the monsoon season (August) due to the high load of river discharge, cloudy environment, and associated favorable conditions; the lowest Chlorophyll-a is found in summer (April) due to the increased sunlight and PAR. Diatoms are the most dominant group in the BoB, which is going to be replaced by smaller planktons like Prochlorococcus species. Chlorophyll-a has a strong relationship with CDOM whereas PAR has a negative relationship with Chlorophyll-a and CDOM. Prokaryotes and Prochlorococcus have showed negative correlation with other functional groups. The Dhaka University Journal of Earth and Environmental Sciences, Vol. 13(1), 2024, P 31-45

Impact of planting density and nitrogen on the productivity of warm-climate onion in the Mexican pacific

O Objective: To evaluate three population density and nitrogen supply in onion. Design/methodology/approach: An experiment was developed in the dry tropics of Mexico. Seedlings were produced in nursery and transplanted on 0.9 m planting beds. In addition to crop management with drip irrigation, nitrogen nutrition was planned according to the rational form of supply. Density/nitrogen factors were evaluated in factorial design 32. Developmental, productive and qualitative bulb variables were recorded and statistically analyzed. Results: The interaction of factors was varied, but in the productive, only the density factor was consistent; bulb weight excelled in the low density (14.8 plants m2) but did not lead to the highest yield, on the other hand, the highest density together with N supply, presented the highest yield per area of 2.14 and 2.17 kg m2. Limitations on study/implications: Onions are favored by the Mexican population as they are among the most consumed vegetables due to their bulbs, and they are attributed with various health benefits. Approximately 52 thousand hectares are harvested in the country and Michoacan participates with 8.3% of production. However, yields are lower than their potential, due to the lack of adaptation to current environmental conditions. This leads to consider the exploration of alternative locations and the implementation of strategies to improve yields, where nutrition and spacing are key factors. Findings/conclusions: The density of 26.9 plants m2 with N addition produced the highest yield.

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

Reconstruction of Araucaria araucana cone production reveals warming intensifies regionally synchronized masting

AbstractThe reproduction of many long‐lived plants is highly variable and synchronized, known as masting. Masting is a key driver of plant regeneration dynamics and has cascading effects on food webs and carbon and nutrient fluxes through ecosystems. Masting patterns can respond to changes in climate, but natural long‐term variability in masting behavior (i.e., baseline variability) is poorly understood. Here we use tree‐rings to create a four‐century reconstruction of annual cone production to uncover centennial‐scale evolution in masting of Araucaria araucana, a dioecious masting species in South America. Over the last four decades, direct observations of annual cone production in this species revealed remarkable range‐wide synchrony of masting. Our tree‐ring‐based reconstruction places this in a long‐term context, revealing that intense regional masting is not a consistent feature of A. araucana reproduction. For extensive periods over the last four centuries, masting has been a site‐specific phenomenon, with variability in cone production that was not regionally synchronized. Comparison with regional climate reconstructions indicates that regional synchrony of masting varies with regional temperature trends, including during recent decades. During warmer periods, synchrony is enhanced, and during cooler periods, regional synchrony breaks down. These dynamics have implications for understanding the reproduction of this iconic and endangered tree species and provide evidence of long‐term linkages between climate change and masting behavior. Our study demonstrates the potential for novel tree‐ring‐based reconstructions of masting to reveal crucial insights into baseline variability and the response of masting to climate change.

Effects of raw and roasted high oleic soybeans on milk production of high-producing dairy cows

Processing method of soybeans has the potential to influence dairy cow production performance, therefore we determined the effect feeding raw or roasted, ground high oleic acid soybeans (HOSB) on production responses of high-producing dairy cows. Thirty-six multiparous Holstein cows (45.6 ± 6.22 kg/d of milk; 110 ± 61 DIM) were randomly assigned to treatment sequences in a 4 × 2 Truncated Latin square design with 35-d periods. Treatments were: 1) control diet containing soybean meal and soybean hulls (CON), 2) 16% roasted and ground HOSB (RST), 3) 16% raw and ground HOSB (RAW-D), and 4) 16% raw and ground HOSB + additional rumen by-pass protein (RAW-U). High oleic acid soybeans replaced conventional soybean meal and hulls in the control diet and rumen by-pass protein replaced soybean meal in RAW-U to maintain diet nutrient composition (%DM) of ∼28.0% NDF, 21.3% forage NDF, 27.3% starch, and 17.8% CP. Fatty acid content of CON, RST, RAW-D, and RAW-U was 1.60, 4.30, 4.36, and 4.34%DM, respectively. Pre-planned contrasts included the overall effect of HOSB inclusion {CON vs. HOSOY [1/3 (RST + RAW-D + RAW-U)]}, the effect of soybean processing {RST vs. RAW [1/2 (RAW-D + RAW-U)]}, and the effect of increasing RUP content within the raw HOSB treatments (RAW-D vs RAW-U). For most variables tested, there were significant interactions between treatment and week, as HOSOY increased production variables compared with CON and RST increased production responses compared with RAW, with only the magnitude of difference varying between weeks. Overall, HOSOY increased DMI and yields of milk, 3.5% FCM, ECM, and milk fat, but did not affect milk protein yield. RST did not impact DMI but increased yields of milk, 3.5% FCM, ECM, milk fat, and milk protein. Compared with RAW-D, RAW-U increased yields of milk and milk protein and tended to increase ECM. Overall, HOSB inclusion of 16% DM increased production responses in high-producing dairy cows, but roasted HOSB had a greater impact than raw HOSB, and the addition of rumen-bypass protein positively affected milk protein response.

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.

Evaluation of Alley-cropping Agroforestry System and Conventional System of Agriculture on the Productivity of Cabbage (<i>Brassica oleracea </i>L.) in Dschang, West Region of Cameroon

Cabbage is one of the main vegetable crops grown in Cameroon. However, production is limited by rising prices and the scarcity of chemical fertilisers on the market. The rise in cost of fertilizers leaves some farmers reluctant to use fertilisers and as a result leads to lower yields, hence, low crop profitability. The aim of this study was to compare the two systems of agriculture; agroforestry system with the conventional system on the growth of cabbage (<i>Brassica oleracea</i> L.). Research plots were established on the campus of the University of Dschang, in the West Region of Cameroon. The comparisons were made on the basis of productivity, pest abundance and economic profitability. Data on yield and pest susceptibility variables were collected during the field trials. It was realised that the slug (<i>Deroceras reticulatum</i>) population was higher in the agroforestry system (4.62±2.41 slugs) than in the conventional system (1.03±0.55 slugs). The aphid population (<i>Brevicoryne brassicae</i>) was higher in the conventional cropping system (25.31±38.94 aphids) compared with the alley-cropping agroforestry system (0.71±0.62 aphids). Productivity variables showed that cabbage yield did not vary between the two production methods. It was 66.08 t/ha and 66.76 t/ha respectively for the agroforestry system and the conventional system. The economic analysis showed that the agroforestry system was more profitable than the conventional system. Thus, growing cabbage in an agroforestry system is an ecological and profitable strategy for agriculture that is more resilient to climatic variations.

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.

Agroclimatic and spectral regionalization for soybean in different agricultural settings in the state of Paraná, Brazil

Abstract Information related to the climate, sowing time, harvest, and crop development is essential for defining appropriate strategies for agricultural activities, which helps both producers and responsible bodies. Paraná, the second largest soybean producer in Brazil, has high climatic variability, which greatly influences planting, harvesting, and crop productivity periods. Therefore, the objective of this study was to regionalize the state of Paraná, considering decennial metrics associated with climate variables and the enhanced vegetation index (EVI) during the soybean cycle. Individual and global analyses of these metrics were conducted performed using multivariate techniques. These analyses were carried out in agricultural scenarios with low, medium, and high precipitation, corresponding to harvest years 2011/2012, 2013/2014, and 2015/2016, respectively. The results obtained from the scores of the retained factors and the cluster analysis were the profile of the groups, with Group 1 presenting more favourable climatic and agronomic conditions for the development of soybean crops for the three harvest years. The opposite occurred for Groups 2 (2011/2012 and 2013/2014) and Group 3 (2015/2016). During the soybean reproductive phases (R2 – R5), precipitation values were inadequate, especially for Group 2 (2011/2012 and 2013/2014) with high water deficit, resulting in a drop in soybean productivity. The climatic and agronomic regionalization of Paraná made it possible to identify the regions most suitable for growing soybeans, the effect of climatic conditions on phenological stages, and the variability of soybean productivity in the three harvest years.