Month Of Harvest Research Articles

Effect of harvesting month and proximity to fish farm sea cages on the lipid profile of cultivated Saccharina latissima

Macroalgae aquaculture is thriving, and kelps such as Saccharina latissima, are now farmed over different production sites across Europe. Macroalgae production in integrated multi-trophic aquaculture setups is gaining relevance due to increased biomass yield and bioremediation potential. Nevertheless, there is a substantiated need to understand how this type of production shapes biomass composition. The present study evaluated the influence of time of harvesting and proximity to nutrient source (fish farm sea cages) on the elemental and biochemical composition of S. latissima, with special emphasis on its lipid content. Overall, the differences recorded for elemental, biochemical and lipid composition of S. latissima occurred consistently with harvesting period rather than with the distance to fish farm sea cages, evidencing that farming kelp in integrated multi-trophic aquaculture setups does not compromise nutritional quality while promoting increased biomass yield. Elemental and biochemical composition differed between kelp biomass harvested in April and those harvested in May and June, with lower C, H and carbohydrates, and higher ash contents in the later. Fatty acid profile analysis revealed an increase in monounsaturated fatty acids along the harvesting period, as well as a decrease in n-3 fatty acids with a concomitant increase of the n-6/n-3 ratio from April to May. Statistical analysis of the polar lipidome identified by liquid chromatography-mass spectrometry revealed differences in specific lipid signatures, displaying a perfect discrimination between harvesting periods. The discrimination between samples from reference and integrated multi-trophic aquaculture sites was only observed for kelp biomass harvested in June. Contributing particularly to these differences are betaine lipids, more abundant in the two later time points, and some lysolipid species, especially abundant in June. These findings will allow a more integrated look at macroalgae production under integrated multi-trophic aquaculture framework, thus promoting the systematization of farming practices that may enhance yield with biochemical quality to match the increasing demands by the food industry and sustainable biorefinary pipeline.

Religious Festivals and Economic Development: Evidence from Catholic Saint Day Festivals in Mexico

Societies worldwide spend substantial resources celebrating religious festivals. How do festivals influence economic and social outcomes? We study Catholic patron saint day festivals in Mexico, exploiting two features of the setting: (i) municipal festival dates vary across the calendar and were determined in the early history of towns after Spanish conquest, and (ii) there is considerable variation in the intra-annual timing of agricultural seasons. We compare municipalities with “agriculturally-coinciding” festivals (those that coincide with peak planting or harvest months) to other municipalities, examining differences in long-run economic development and social outcomes. Agriculturally-coinciding festivals have negative effects on household income and other development outcomes. They also lead to lower agricultural productivity and higher share of the labor force in agriculture, consistent with agriculturally-coinciding festivals inhibiting the structural transformation of the economy. Agriculturally-coinciding festivals also lead to higher religiosity and social capital, potentially explaining why such festivals persist in spite of their negative growth consequences.

The Green Revolution from space: Mapping the historic dynamics of main rice types in one of the world's food bowls

This paper develops a methodology to map the two main rice types in northwest Bangladesh from 1989 to 2016, when Green Revolution technologies and policies resulted in a 300% rice area expansion and localised unsustainable groundwater use. The mapping is performed for the largely irrigated dry season Boro rice (grown from November/December to May/June), and the largely rainfed Aman rice (grown from June/July to October/November).The petabyte archive of Landsat reflectance data available via Google Earth Engine is used to extract monthly time-series of two remotely sensed vegetation indices – the Enhanced Vegetation Index (EVI) and the Global Vegetation Moisture Index (GVMI) – which can capture crop phenological dynamics as they correlate during crop growth stages and can be used to discriminate standing water when EVI is low and GVMI is high. This feature is exploited to detect the effects of flooding before transplanting Boro rice in January and to capture the late phenological phases of Aman rice through harvesting months (October to November).A gap-filled and smoothed EVI and GVMI monthly time-series sequences for both rice cropping months are grouped using machine learning unsupervised K-means clustering into clusters (25 used here), and manually aggregated using crop calendars and local expert knowledge into rice types, other vegetated areas, water, non-permanent water and bare areas. A representative subset of these data are then used to construct a training sample using additional covariates besides the monthly EVI and GVMI values and train a Random Forest (RF) model capable of predicting the land cover types in other years.The resulting RF maps for the two cropping seasons were evaluated against publicly available survey crop statistics (from 1989 to 2016) and published Boro 30 m resolution maps for 2013 to 2016. The maps provide qualitative evidence that unsustainable groundwater extractions can be linked to Boro rice irrigation in some parts of northwest Bangladesh. Further research, using these maps and other hydrological data, is required to quantitatively assess when, where, and how much irrigation contributes to unsustainable groundwater use. The results show that the methodology can accurately (generally within 20% absolute error) capture Boro and Aman rice over the Green Revolution period, and other landscape dynamic characteristics of importance for environmental assessments, such as areas of standing water.

Genetic diversity and fruit characteristics of new superior hybrid strawberry (Fragaria × ananassa Duchesne ex Rozier) genotypes

The development of strawberry (Fragaria × ananassa Duchesne ex Rozier) genotypes, which have good taste, size and firmness, is among the most important and prioritized issues of today. We aimed to develop new strawberry cultivars having standards of priority issues for strawberry. Eight prominent strawberry genotypes were obtained from the cross of domestic strawberry cultivars (‘Sevgi’, ‘Kaska’, and ‘Ebru’) with the varieties (‘Rubygem’, ‘Festival’, and ‘Amiga’). Pomological (total soluble solids, titratable acidity, pH, and firmness) and physical (fruit width, fruit length, and fruit weight) analyses of eight strawberry genotypes and their parents were performed on active harvest months. In addition, ISSR (Inter Simple Sequence Repeat) markers were used to analyze the genetic diversity of eight prominent strawberry hybrids and their parents. The selected superior hybrid strawberry fruit characteristics exceeded the characteristics of local varieties and reached the point where they can compete with commercial varieties in terms of most of the quality parameters. However, it was determined that the genotypes did not reach the targeted point in terms of fruit firmness. While a good positive correlation among fruit size parameters was found, taste of fruit was negatively affected by increasing these. As it is seen in the molecular results (PCoA), domestic and foreign cultivars were separated from each other, and their progenies were generally between them as most of the examined parameters (fruit firmness, acidity, total soluble solid, fruit weight). In addition, PIC value ranged from 0.17 (UBC816) to 0.86 (UBC824).

Demonstration gardens improve agricultural production, food security and preschool child diets in subsistence farming communities in Panama.

To explore impacts of a demonstration garden-based agricultural intervention on agricultural knowledge, practices and production, food security and preschool child diet diversity of subsistence farming households. Observational study of households new to the intervention or participating for 1 or 5 years. Variables measured were agricultural techniques learned from the intervention and used, agricultural production, household food insecurity (FIS) and child diet diversity (DDS), over one agricultural cycle (during land preparation, growing and harvest months). Fifteen rural subsistence farming communities in Panama. Households participating in intervention (n 237) with minimum one preschool child. After 1 year, participants had more learned and applied techniques, more staple crops produced and lower FIS and higher DDS during land preparation and growing months compared with those new to the intervention. After 5 years, participants grew more maize, chickens and types of crops and had higher DDS during growing months and, where demonstration gardens persisted, used more learned techniques and children ate more vitamin A-rich foods. Variables associated with DDS varied seasonally: during land preparation, higher DDS was associated with higher household durable asset-based wealth; during growing months, with greater diversity of vegetables planted and lower FIS; during harvest, with older caregivers, caregivers working less in agriculture, more diverse crops and receiving food from demonstration gardens. The intervention improved food production, food security and diets. Sustained demonstration gardens were important for continued use of new agricultural techniques and improved diets.

Effect of planting time and harvest on yield and quality of ginger (Zingiber officinale Rosc.) cv. Nadia

In the present study, the effect of different planting time and harvest on yield and quality of ginger (Zingiber officinale Rosc.) cv. Nadia were evaluated. The experiment was laid out in Split Plot Design with dates of planting as main treatment (30th March, 30th April and 30th May) and five harvesting time as sub-treatments (6 MAP, 7 MAP, 8 MAP, 9 MAP and 10 MAP) with three replications. The study revealed that harvesting time effectively influenced on the quality of ginger. Planting time showed significant effect on almost all the characters except for fibre content. The quality of ginger rhizome such as oil content, dry recovery and oleoresin content had significant influence on both the planting time and the harvesting time. Planting of rhizomes on 30th April resulted better yield and yield attributing characters. Among different harvesting time, harvesting at 8 MAP recorded significantly higher fresh weight of ginger and quality characters. The treatment (M2H3) i.e. April planting time and harvesting at 8 MAP exhibited higher yield and yield attributing characters viz. length of finger (8.69 cm), girth of finger (8.09 cm), fresh weight of rhizome plant-1 (1310.03 g), yield plot-1 (11.98 kg), and yield ha-1 (31.53 t). Planting in the month of April and harvesting at 9 MAP (M2H4) recorded better quality rhizome with high oil (2.83%), oleoresin (15.74%) and dry recovery (23.83%) with less fibre content (4.9%) followed by planting in April and harvest at 8 MAP (M2H3).

Time-varying impact of climate on maize and wheat yields in France since 1900

Climate services that can anticipate crop yields can potentially increase the resilience of food security in the face of climate change. These services are based on our understanding of how crop yield anomalies are related to climate anomalies, yet the share of global crop yield variability explained directly by climate factors is largely variable between regions. In Europe, France has been a major crop producer since the beginning of the 20th Century. Process based and statistical approaches to model crop yields driven by observed climate have proven highly challenging in France. This is especially due to a high regional diversity in climate but also due to environmental and agro-management factors. An additional level of uncertainty is introduced if these models are driven by seasonal-to-decadal surface climate predictions due to their low performances before the harvesting months of both wheat and maize in western Europe. On the other hand, large scale circulation patterns can possibly be better predicted than the regional surface climate, which offers the opportunity to rely on large scale circulation patterns as an alternative to local climate variables. This method assumes a certain degree of stationarity in the relationships between large scale patterns, surface climate variables, and crop yield anomalies. However, such an assumption was never tested, because of the lack of suitable long-term data. This study uses a unique dataset of subnational crop yields in France covering more than a century. By calibrating and comparing statistical models linking large scale circulation patterns and observed surface climate variables to crop yield anomalies, we can demonstrate that the relationship between large scale patterns and surface variables relevant for crop yields is not stationary. Therefore, large scale circulation pattern based crop yield forecasting methods can be adopted for seasonal predictions provided that regression parameters are constantly updated. However, the statistical crop yield models based on large-scale circulation patterns are not suitable for decadal predictions or climate change impact assessments at even longer time-scales.

Effect of meteorological variables on crawfish harvest in Louisiana, USA

This study examines the effect of meteorological variables, such as temperature, precipitation, cloud cover, and relative humidity on average monthly crawfish (Procambarus spp.) harvests at 6 research ponds located at the Aquaculture Research Station in Baton Rouge, Louisiana, USA, operated by the Louisiana State University Agricultural Center. Eight years (2006-2013) of harvest data were collected spanning February, March, and April of each year. Using multiple regression and model selection processes, the effect of meteorological variables was assessed at 3 different monthly lags (lag 0, 1, and 2) to determine which combination of variables best explained variance in average monthly crawfish pounds per trap (AMPT). The final model selected for lag 0 (adj-rsq = 0.73, p < 0.01), lag 1 (adj-rsq = 0.71, p < 0.01), and lag 2 (adj-rsq = 0.69, p < 0.01) generally included the same variables: monthly average low temperature, precipitation, and the preceding October/November precipitation (ON). Both monthly average low temperature and ON exhibited a statistically significant (p ≤ 0.05) positive effect on AMPT while controlling for other variables in the model, revealing the importance of warm temperatures and precipitation during October/November for crawfish harvests. Precipitation during the harvest month was not significant, but increased precipitation 1 and 2 mo before harvest significantly decreased AMPT. The number of hours with temperatures ≤0°C was also a significant variable negatively associated with AMPT 1 and 2 mo before harvest and, along with precipitation, could potentially be an early indicator for AMPT before harvests begin in southern Louisiana.

Investigation of Aerosol Climatology, Optical Characteristics and Variability over Egypt Based on Satellite Observations and In-Situ Measurements

Egypt experiences high rates of air pollution, which is a major threat to human health and the eco-environment and therefore needs to be tackled by defining major causes to hinder or mitigate their impacts. The major driving forces of air pollution are either of local and/or regional origin. In addition, seasonal aerosols may be natural, such as dust particles transported from the western desert, or anthropogenic aerosols which are transported from industrial areas and smoke particles from seasonal biomass burning. Monitoring the optical properties of aerosols and their pattern in the atmosphere on a daily basis requires a robust source of information and professional analytical tools. This research explored the potential of using time series of Moderate Resolution Imaging Spectroradiometer (MODIS) and Aerosol Robotic Network (AERONET) data to comprehensively investigate the aerosol optical depth (AOD) and variability for the period 2012–2018 on a daily basis. The data show that spring, summer and autumn seasons experienced the highest anomaly originating from regional and national sources. The high AOD in spring associated with a low Ångström exponent (AE) indicates the presence of coarse particles which naturally originate from desert dust or sea spray. In contrast, the high AE in summer and autumn demonstrated the dominance of fine anthropogenic aerosols such as smoke particles from local biomass burning. The observation of a high number of fire incidents over Egypt in October and November 2018, during the months of rice crop harvesting, showed that these incidents contribute to the presence of autumn aerosols across the country. In-situ measurements of Particulate Matter (PM10) from local stations from an environmental based network as well as the AERONET AOD were used to validate the MODIS AOD, providing a high correlation coefficient of r = 0.73.

Physiological Stress Reactions in Red Deer Induced by Hunting Activities.

Simple SummaryGame hunting is an activity largely practiced all over the world. Understanding its consequences on wildlife is crucial for the proper management and development of hunting directives. In this study, we examined stress levels in hunted wild red deer by assessing cortisol levels and its metabolites in multi-temporal biological samples. Overall, we found evidence for an influence on stress levels of red deer caused by repeated exposure to hunting events, which could have important implications on the sustainability and conservation of wild populations. Furthermore, our results highlight the use of hair samples as a useful long-term stress indicator.Hunting activity is usually seen as a factor capable of causing an intense stress response in wildlife that may lead to short but also long-term stress. In the Lousã Mountain, Portugal, the population of red deer (Cervus elaphus) is the target of intensive seasonal hunting. We collected and measured cortisol (and its metabolites) in three tissues types (blood, feces and hair) from red deer hunted during two hunting seasons to evaluate the stress levels at different time windows. We also assessed the immunological and physical condition of the animals. We predicted that the hunting activity would act as a stressor inducing increased short and long-term stress levels in the population. Results showed an increase in hair cortisol levels during the months of harvesting. Surprisingly, the tendency for plasma cortisol levels was to decrease during the hunting season, which could be interpreted as habituation to hunting activity, or due to the hunting duration. Contrary to our predictions, fecal cortisol metabolites did not show any clear patterns across the months. Overall, our results suggest an influence of hunting activities on the physiological stress in red deer. In addition, hair seems to be useful to measure physiological stress, although more studies are required to fully understand its suitability as an indicator of long-term stress. Methodologically, our approach highlights the importance of simultaneously using different methods to assess short and long-term effects in studies on physiological stress reactions.

Comparison Between Machine Learning Models for Yield Forecast in Cocoa Crops in Santander, Colombia

The identification of influencing factors in crop yield (kg·ha-1) provides essential information for decision-making processes related to the prediction and improvement of productivity, which gives farmers the opportunity to increase their income. The current study investigates the application of multiple machine learning algorithms for cocoa yield prediction and influencing factors identification. The Support Vector Machines (SVM) and Ensemble Learning Models (Random Forests, Gradient Boosting) are compared with Least Absolute Shrinkage and Selection Operator (LASSO) regression models. The considered predictors were climate conditions, cocoa variety, fertilization level and sun exposition in an experimental crop located in Rionegro, Santander. Results showed that Gradient Boosting is the best prediction alternative with Coefficient of determination (R2) = 68%, Mean Absolute Error (MAE) = 13.32, and Root Mean Square Error (RMSE) = 20.41. The crop yield variability is explained mainly by the radiation one month before harvest, the accumulated rainfall on the harvest month, and the temperature one month before harvest. Likewise, the crop yields are evaluated based on the kind of sun exposure, and it was found that radiation one month before harvest is the most influential factor in shade-grown plants. On the other hand, rainfall and soil moisture are determining variables in sun-grown plants, which is associated with the water requirements. These results suggest a differentiated management for crops depending on the kind of sun exposure to avoid compromising productivity, since there is no significant difference in the yield of both agricultural managements.

Determinants of the retail price of illegal drugs in New Zealand

IntroductionNew Zealand has a number of unusual geographical features that may influence the price of illegal drugs including international isolation, numerous rural communities, and two separate islands (North and South Islands). Aims(1) Collect data on the prices of different drug types from all regions of New Zealand; (2) Identify independent predictors of the reported prices. MethodAn online drug survey was promoted via a targeted Facebook™ campaign. A total of 6331 respondents completed the survey. Normal regression models were constructed to identify predictors of the reported price of an ounce of cannabis, gram of methamphetamine, pill of ecstasy and tab of LSD using demographics, drug use frequency, drug market indicators, region, community size, type of seller, and location of purchase as predictor variables. ResultsHigher availability was a predicator of lower prices for cannabis (-3% per higher availability category), methamphetamine (-4%) and ecstasy (-5%). Those living in the North Island (-26%) and buying from gangs (-5%) paid lower prices for methamphetamine. Those living in rural communities reported higher prices for methamphetamine (+5%) but lower prices for cannabis (-3%). Daily cannabis users (+4%) and those on social welfare (+2%) paid higher prices for cannabis. ConclusionLower prices for methamphetamine in the North Island may reflect the concentration of methamphetamine manufacture there. The fact that gangs offer lower prices for methamphetamine suggests they do not have monopoly control of this market. Gangs may be able to offer lower prices for methamphetamine due to scale of production/trafficking and lower risk of victimisation. Higher prices for methamphetamine in rural areas may reflect less competitive markets. Lower prices for cannabis in rural communities may be due to proximity to growing locations. Daily cannabis users and those on social welfare may be less able to delay their cannabis purchases to low price harvest months.

Evaluation of the morphological and quality characteristics of new varieties of Papaya Agri Solinda

The availability of new varieties with high productivity, pest and disease resistance, environmental stress tolerance, and accordance with consumer needs are requirements for the papaya to be accepted in the market. This study was conducted to evaluate the new varieties of papaya Agri Solinda with superior characteristics such as a high number of fruits per plant, high productivity, medium fruit size, and a thick, sweet, slightly chewy texture, with a good fragrant fruit flesh. The plants were planted in a pairwise comparison design with three replications with 30 plants each at the Sumani Experimental Garden belongs to the Indonesian Tropical Fruit Research Institute on 2014-2015. The result showed that papaya Agri Solinda has better characteristics compared to the comparison such as medium fruit size, bright yellow color, chewy texture, and sweet taste of fruit flesh [TDS: 12-14o Brix] with productivity over 80 tons/ha on 7-8 months of the first harvest. The morphological characteristics, a unique or new, that Agri Solinda has a sweeter taste and higher of total dissolved solids [TDS] than the comparison varieties [Sari Gading].

Chemical composition and anti-complement activity of Glechomae Herba collected in different months.

Glechomae Herba (GH) is derived from the dried aerial part of Glechoma longituba (Nakai) Kupr., which is harvested from spring to autumn. It has the effects of clearing heat and detoxification. The aim of this paper was to study the chemical composition and the anti-complement activity of GH collected in different months. Ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight tandem mass spectrometry based on predicted compounds screening and diagnostic ion filter strategy was developed for identifying the chemical composition of GH collected in different months. A total of 102 compounds-40 chlorogenic acids (CGAs), 32 phenolic acids, and 30 flavonoids-were reasonably identified in GH. Thirty-four CGAs were discovered in GH for the first time. The correlations between chemical compositions and anti-complement activities of GH collected in different months were analyzed. Phenolic acids and flavonoids were found to be negatively correlated with anti-complement activity, and CGAs were positively correlated with anti-complement activity. At the same time, six CGA standards had obvious anti-complement activity. It was demonstrated that different harvest months had a significant impact on the difference in chemical composition and anti-complement activity of GH. And CGAs might play an important role in the anti-complement activity of GH.

Effect of Harvest Date on Technological Yield and Evolution of Hydrocyanic Acid Loss Rate after Transformation of Cassava Root (Manihot Esculenta CRANTZ) from Yacé Variety by Placali and Attiéké Consumed in Côte d'Ivoire

In order to contribute to their better utilization and valorization, tuberous roots of cassava (Manihot esculenta CRANTZ) of the yace variety consumed in Cote d’Ivoire have drawn our attention. Four different harvest periods of these tuberous roots were used in the study. Cassava tubers were harvested at 11th, 12th, 13th and 14th months after planting. The hydrocyanic acid loss rate and technological yield after the transformation of cassava roots (harvested at the 11th, 12th, 13th and 14th months after planting) into placali and attieke were investigated. The results showed that the products obtained with the 11 th month of harvest had the greatest losses. Peeling (29.59 % for attieke and 36.68 % for placali) and pressing (33.32 % for attieke and 34.56 % for placali) are the stages causing the most significant losses during the transformation of cassava roots into placali and attieke. The technological yield increases with the harvest period and falls after the twelfth month. The maximum corresponding to the 12th month of harvest is 81.65 % for attieke and 70.83 % for placali. Regarding the rate of loss of hydrocyanic acid, it was moreimportant at the eleventh month of harvest for placali and attieke with respective values of 95.85 % and 94.11 %. Cassava tubers harvested at the 12th month after planting are therefore ideal for the production of attieke and placali.

It's Not Just About the Worm: Social and Economic Impacts of Harvesting Imbrasia Belina larvae (Kruger National Park, South Africa)

A mopane worm (Imbrasia belina) harvesting project in the Kruger National Park (KNP) was used as a case study to test whether conservation related benefit sharing has a net positive impact on multiple dimensions of human well-being. Furthermore, the study assessed whether and to what degree, sharing such benefits influenced local perceptions of conservation, a requirement for the sustainability of protected areas across the globe. The project involved 263 people from 16 villages, adjacent to the KNP, harvesting 4,688 L worms contributing the equivalent of over half of the average household income during the months of harvest. Despite paying for transport, the participants gained from the experience; instilling the feeling that the park is opening up to them, and as a result seeing the park differently. For most participants the project provided them their first opportunity to visit the park, and participants perceived this to have further contributed positively to their wellbeing as a result of the associated learning experiences. Furthermore, participants enjoyed meeting and getting to know the park staff, with these new social connections contributing positively to social wellbeing. Respondents perceived their relationship with the park to be positive and expressed hope for building on this in the future. We conclude that measuring the multiple dimensions of human wellbeing in impact assessments is beneficial, and that the social connections that are built between neighbours, protected area staff and the natural and cultural resources within protected areas as a result of such projects can have mutually beneficial outcomes both for people and conservation.

Browning Treatment in Tissue Culture of ‘Miliang 1’ Delicious Kiwifruit

Explant browning is a common problem in tissue culture and has become a limiting factor in the development of kiwifruit tissue culture. The effects of different sampling time and disinfection conditions on tissue culture browning of ‘Miliang 1’ delicious kiwifruit stem segments were studied in this study. Finally, the best months of harvest and the best disinfection conditions were screened out. The results showed that the browning rate of ‘Miliang 1’ taken in April was significantly lower than other time periods, and the browning rate gradually increased with time, reaching a maximum of 33.3% in September, significantly higher than other times. There was no significant difference in the browning rate among May, June, July and August. When the disinfection treatment was 75% alcohol 10s + 0.1% mercury liter for 2 min, the number of pollution was much higher than other treatments, the disinfection treatment time was obviously insufficient. Whatmore, the longer the disinfection time, the less the number of pollution, but the more the number of browning was increased. When the disinfection treatment was 75% alcohol 30s+0.1% mercury 5min, the number of browning was significantly higher than other treatments. With the increase of alcohol and mercury treatment time, the number of explant contamination decreased, but the number of death increased significantly. Generally speaking, the final survival rate of callus induction in the treatment of 75% alcohol 20s + 0.1% mercury for 5min was significantly higher than other treatments, which was more suitable for the callus induction culture and disinfection of ‘Miliang 1’ kiwifruit.

Proposing a More Efficient Maintenance Scheduling for an Overhaul Maintenance Project in Engineering Asset Management

In maintenance activity, scheduling planning is an important step to improve the performance of maintenance department. In some cases, the data to support the process to develop the maintenance schedule is unavailable. In this research, it is argued that Genetic Algorithm (GA) is an appropriate tool to support the decision maker in order to develop the schedule. The data required in this research is obtained from the maintenance data in the sugar milling company in Yogyakarta. The company run the production of sugar and spirits/alcohol. The Production process (milling seasin) is usually performed within the harvesting months of the raw material: the sugar cane. It is approximately in the month of February to August. On the other hand, the overhaul maintenance process is performed after the milling season. The overhaul maintenance planning is created by the manager of the maintenance department, and usually is done using the manager qualitative approach without any sciencetific approach. To get a more efficient schedule of maintenance, several parameters are set in this research. The parameters are then applied as the paramenters in GA. Those are: The number of manpower required and the duration of operation each activity. To run the GA model, Python programming is used. Before start the GA process, the parent chromosom and its fitness are determined. The date of maintenance activity start per each activity is set as the parent chromosome and the fitness is determined using a formula. The process of finding the better maintenance schedule is then performed based on the procedures in GA. It is indicated from the result that the proposed schedule generated in GA required less number of manpower.

DURATION AND CONCENTRATION OF 1-METHYLCYCLOPROPENE TREATMENT: IMPACT ON RIPENING AND SHELF LIFE OF PARTIALLY RIPENED BANANAS

In order to improve the quality and extend the shelf life of bananas after gassing with ethylene at commercial treatment during transportation and storage the simultaneous application of ethylene and 1-methylcyclopropene were examined. Fruit were treated with 100 µL L-1 of ethylene for two consecutive days as a control, followed by 20 min ventilation each day, or simultaneously exposed to 1-MCP at different concentrations (30, 100 or 300 nL L-1 on the first day or second day, or treated with 1-MCP alone on the third day at 22ºC. Fruit from each treatment were used to evaluate external and internal quality parameters and shelf life. The results showed that shelf life increased significantly, compared to the control when 1-MCP was applied coincidently with ethylene in the second day and reapplied alone in the third day. The highest increase in shelf life (125%) was obtained when 1-MCP was applied on the second day at 30 nL L-1 simultaneously with ethylene and at 300 nL L-1 alone on the third day, compared to the control in both harvest months. We conclude that simultaneous application of 1-MCP is more effective than the more common method of extending banana shelf life through application of 1-MCP after ethylene treatment.

Effects of harvest month on biochemical composition of alligator weed for biohydrogen and biomethane cogeneration：Identifying critical variations in microbial communities

To determine the optimal harvest period for alligator weed used in fermentation-based gaseous biofuel production, the effects of harvest months on the biochemical composition and fermentative hydrogen and methane co-production from alligator weed were evaluated. Compositional analysis indicates that alligator weed harvested in September was most suitable for fermentative hydrogen production because it exhibited an appropriate carbon to nitrogen molar ratio (26.75), the highest cellulose content (20.34%) and the lowest weight ratio of ash to volatiles (0.09). Biohydrogen production was significantly affected by the harvest month, peaking at 48.4 mL/g VS in September. Microbial community analysis suggests that the abundance of Clostridium sensu stricto, the dominating hydrogen producer in dark fermentation reactors, was greatly enriched with feedstock harvested in September. Moreover, the expression levels of functional genes involved in carbohydrate metabolism and microbial proliferation were highest in the reactor fed with feedstock harvested in September. During the second-stage anaerobic digestion (AD), biomethane yield mainly depended on the soluble COD content in the hydrogenogenic effluent and was highest in August (214.6 mL/g VS). A maximum total energy conversion efficiency of 44.8% was obtained in September through two-stage process combining dark fermentation and AD.