Maintaining forage availability is challenging for managers of grazing systems, especially in spatially heterogeneous swards. Remote sensing may help to overcome this problem. The objectives of this study were to (i) determine a method by which NDVI may be calibrated to estimate biomass, (ii) determine if NDVI can be used to assess spatial variability of yield in extensive grasslands, and (iii) to determine if NDVI can be used to evaluate grazing systems. We found that the calibration of NDVI values for the estimation of biomass was better correlated with the destructive harvesting procedure (R2 = 0.68) but far more laborious and time-consuming than estimation of biomass from the rising plate meter (R2 = 0.54). Semivariograms revealed that sampling at a 0.76 m distance provided information about the spatial variability structure of NDVI values from grazed swards. Frequency distributions of sward biomass derived from NDVI reflected foraging strategies of cattle. Negative skewness and high kurtosis of histograms indicated selective grazing, while positive skewness and low kurtosis indicated the opposite. Histograms also allowed for estimation of available forage within each field. We concluded that grassland biomass may be derived from high resolution NDVI and RPM data and used to evaluate condition of grassland landscapes and aid decision-making of managed grazing systems.

O objetivo deste estudo foi desenvolver e validar modelos preditores para a fitomassa epigéa da mata atlântica, formação vegetal que cobre a Serra do Mar no estado de São Paulo. Em duas parcelas de 100m2, 82 árvores foram cortadas, ao nível do solo, e anotadas suas medidas de altura e diâmetro. As folhas foram separadas dos ramos para determinação do peso fresco da porção foliar e lenhosa. Amostras de cada fração foram secas em estufa a 80o C, até peso constante, para determinação do peso seco. As árvores foram distribuídas em duas amostras aleatórias, sendo uma utilizada para o desenvolvimento das equações de regressão, e a outra para validá-las. Os modelos foram desenvolvidos através da análise de regressão linear simples e múltipla, tendo como variável dependente o peso seco (PS) e, como variáveis independentes a altura (h), o diâmetro (d) e o (d2h). A análise de validação foi feita através do coeficiente de correlação de Pearson, teste t-Sudent pareado e através do erro padrão da estimativa. As melhores equações para estimar o peso seco das árvores foram: lnPS = -4,1519 + 1,06068 ln d2h (r2=0,82; sy/x= 0,42; ricc=0,92); lnPS = -6,7171 + 1,30308 ln d2h (r2=0,88; sy/x= 0,44; ricc=0,93) e lnPS = -6,80067 + 3,77738 ln d (r2=0,92; sy/x =0,37; ricc=0,87). / The purpose of this study was develop and validate equations to estimative the aboveground phytomass of the Atlantic Forest, at the Serra do Mar, São Paulo, Southeast Brazil. In two available plots of 100m2, 82 trees were cut down at ground level. From each tree height and diameter was determined. Leaves and woody material were separated in order to determine their fresh weights in field conditions. Samples of each fraction were oven dried at 80o C to constant weight to determine their dry weight. The trees data were divided into two random samples. One sample was used for the development of the regression equations, and the validation was done using other one. The models were developed using single and multiple linear regression analysis, where the dependent variable was the dry mass and the independent variables were height (h), diameter (d) and d2h. The validation was done using Pearson correlation coefficient, paired t-Student test and standard error of estimation. The best equations to estimate aboveground phytomass were: lnPS = -4,1519 + 1,06068 ln d2 h (r2=0,82; sy/x= 0,42; ricc=0,92); lnPS = -6,7171 + 1,30308 ln d2h (r2=0,88; sy/x= 0,44; ricc=0,93) and lnPS = -6,80067 + 3,77738 ln d (r2=0,92; sy/x =0,37; ricc=0,87).

O objetivo do presente estudo é avaliar a possibilidade de utilizar o sensoriamento remoto óptico e o sensoriamento remoto por microondas de modo complementar na estimativa de biomassa vegetal aérea em áreas de cerrado no estado de São Paulo. A metodologia proposta visa quantificar biomassa de forma não destrutiva, rápida e a baixo custo. O trabalho foi desenvolvido em uma área com remanescentes de cerrado ao Sudoeste do estado de São Paulo. Utilizaram-se imagens Índice de Vegetação Diferença Normalizada – IVDN e Índice de Vegetação Realçado - IVR, produzidas a partir de imagens do sensor Enhanced Thematic Mapper - ETM+ a bordo do satélite Landsat7 para estimar Índice de Área Foliar - IAF em áreas de vegetação aberta de cerrado. Também foi utilizada uma imagem de radar, banda L, do satélite Japanese Earth Resources Satellite - JERS-1. Os resultados de estimativa de IAF através de imagens IVDN e IVR não foram satisfatórios, devido à inadequabilidade da técnica de amostragem no campo para as áreas abertas. A estimativa de biomassa lenhosa aérea por imagens de radar forneceu resultados significativos. Estes resultados permitiram determinar uma equação que descreve o comportamento do sinal de radar em função da quantidade de biomassa lenhosa aérea em fisionomias florestais do bioma cerrado. Esta equação pode ser útil na estimativa de biomassa em outras áreas de cerrado. / The objective of this study is to evaluate the feasibility of using radar and optical remote sensing in a complementary way to estimate above ground vegetal biomass. Two non destructive, fast and low cost methodologies for biomass quantification of different physiognomies of cerrado were proposed. The work was carried out in an area with remnants of cerrado in the Southwest of São Paulo State. Normalized Difference Vegetation Index - NDVI and Enhanced Vegetation Index - EVI images from Enhanced Thematic Mapper ETM+ sensor on board of Landsat7 satellite were used to estimate Leaf Area Index - LAI in open cerrado areas. A L band radar image was also used for dense woody biomass estimation. The sampling technique used in the field shown to be unsuitable for the open physiognomies of cerrado. As a consequence, results of LAI estimation through IVDN and IVR images were not satisfactory. Aboveground woody biomass estimation through radar image yield significant results. Based on those data, as equation that describes the behavior of the of radar signal as a function of the amount of aboveground woody biomass in cerradão was found. This equation can be useful to estimate aboveground woody biomass in other cerrado areas.

O objetivo do presente estudo é avaliar a possibilidade de utilizar o sensoriamento remoto óptico e o sensoriamento remoto por microondas de modo complementar na estimativa de biomassa vegetal aérea em áreas de cerrado no estado de São Paulo. A metodologia proposta visa quantificar biomassa de forma não destrutiva, rápida e a baixo custo. O trabalho foi desenvolvido em uma área com remanescentes de cerrado ao Sudoeste do estado de São Paulo. Utilizaram-se imagens Índice de Vegetação Diferença Normalizada – IVDN e Índice de Vegetação Realçado - IVR, produzidas a partir de imagens do sensor Enhanced Thematic Mapper - ETM+ a bordo do satélite Landsat7 para estimar Índice de Área Foliar - IAF em áreas de vegetação aberta de cerrado. Também foi utilizada uma imagem de radar, banda L, do satélite Japanese Earth Resources Satellite - JERS-1. Os resultados de estimativa de IAF através de imagens IVDN e IVR não foram satisfatórios, devido à inadequabilidade da técnica de amostragem no campo para as áreas abertas. A estimativa de biomassa lenhosa aérea por imagens de radar forneceu resultados significativos. Estes resultados permitiram determinar uma equação que descreve o comportamento do sinal de radar em função da quantidade de biomassa lenhosa aérea em fisionomias florestais do bioma cerrado. Esta equação pode ser útil na estimativa de biomassa em outras áreas de cerrado. / The objective of this study is to evaluate the feasibility of using radar and optical remote sensing in a complementary way to estimate above ground vegetal biomass. Two non destructive, fast and low cost methodologies for biomass quantification of different physiognomies of cerrado were proposed. The work was carried out in an area with remnants of cerrado in the Southwest of São Paulo State. Normalized Difference Vegetation Index - NDVI and Enhanced Vegetation Index - EVI images from Enhanced Thematic Mapper ETM+ sensor on board of Landsat7 satellite were used to estimate Leaf Area Index - LAI in open cerrado areas. A L band radar image was also used for dense woody biomass estimation. The sampling technique used in the field shown to be unsuitable for the open physiognomies of cerrado. As a consequence, results of LAI estimation through IVDN and IVR images were not satisfactory. Aboveground woody biomass estimation through radar image yield significant results. Based on those data, as equation that describes the behavior of the of radar signal as a function of the amount of aboveground woody biomass in cerradão was found. This equation can be useful to estimate aboveground woody biomass in other cerrado areas.

O objetivo deste estudo foi desenvolver e validar modelos preditores para a fitomassa epigéa da mata atlântica, formação vegetal que cobre a Serra do Mar no estado de São Paulo. Em duas parcelas de 100m2, 82 árvores foram cortadas, ao nível do solo, e anotadas suas medidas de altura e diâmetro. As folhas foram separadas dos ramos para determinação do peso fresco da porção foliar e lenhosa. Amostras de cada fração foram secas em estufa a 80o C, até peso constante, para determinação do peso seco. As árvores foram distribuídas em duas amostras aleatórias, sendo uma utilizada para o desenvolvimento das equações de regressão, e a outra para validá-las. Os modelos foram desenvolvidos através da análise de regressão linear simples e múltipla, tendo como variável dependente o peso seco (PS) e, como variáveis independentes a altura (h), o diâmetro (d) e o (d2h). A análise de validação foi feita através do coeficiente de correlação de Pearson, teste t-Sudent pareado e através do erro padrão da estimativa. As melhores equações para estimar o peso seco das árvores foram: lnPS = -4,1519 + 1,06068 ln d2h (r2=0,82; sy/x= 0,42; ricc=0,92); lnPS = -6,7171 + 1,30308 ln d2h (r2=0,88; sy/x= 0,44; ricc=0,93) e lnPS = -6,80067 + 3,77738 ln d (r2=0,92; sy/x =0,37; ricc=0,87). / The purpose of this study was develop and validate equations to estimative the aboveground phytomass of the Atlantic Forest, at the Serra do Mar, São Paulo, Southeast Brazil. In two available plots of 100m2, 82 trees were cut down at ground level. From each tree height and diameter was determined. Leaves and woody material were separated in order to determine their fresh weights in field conditions. Samples of each fraction were oven dried at 80o C to constant weight to determine their dry weight. The trees data were divided into two random samples. One sample was used for the development of the regression equations, and the validation was done using other one. The models were developed using single and multiple linear regression analysis, where the dependent variable was the dry mass and the independent variables were height (h), diameter (d) and d2h. The validation was done using Pearson correlation coefficient, paired t-Student test and standard error of estimation. The best equations to estimate aboveground phytomass were: lnPS = -4,1519 + 1,06068 ln d2 h (r2=0,82; sy/x= 0,42; ricc=0,92); lnPS = -6,7171 + 1,30308 ln d2h (r2=0,88; sy/x= 0,44; ricc=0,93) and lnPS = -6,80067 + 3,77738 ln d (r2=0,92; sy/x =0,37; ricc=0,87).

Solid state fermentation (SSF) refers to the microbial fermentation, which takes place in the absence or near absence of free water, thus being close to the natural environment to which the selected microorganisms, especially fungi, are naturally adapted. The current status of SSF research globally was discussed in terms of articles publication. This was followed by discussion of the advantages of SSF and the reason for interest in SSF as a notable bioprocessing technology to be investigated and compared to submerged fermentation (SmF) for the production of various added-value products. SSF also proved to be a potential technology to treat solid waste produced from food and agricultural industry and to provide environmental benefits with solid waste treatment. A summary was made of the attempts at using modern SSF technology for future biorefineries for the production of chemicals. Many works were carried out in the Satake Centre for Grain Process Engineering (SCGPE), University of Manchester, to prove the strategy of using SSF for the production of hydrolysate rich in nutrients for sequel microbial fermentation with or without adding any commercial nutrients. The research findings presented in this thesis are based on a series of SSF experiments carried out on systems varying in complexity from simple petri dishes to our own design of bioreactor systems. They were conducted to assess a solution for biomass estimation, enzymes production, and successful mass and heat transfer. A proper technique for inoculum transfer prior to the start of the fermentation process was developed. In SSF, estimation of biomass presents difficulties as generally the fungal mycelium penetrates deep and remains attached with the solid substrate particles. Although many promising methods are available, the evaluation of microbial growth in SSF may sometimes become laborious, impractical and inaccurate. Essentially, this remains another critical issue for monitoring growth. In these studies, measurement of colour changes during SSF are presented as one of the potential techniques that can be used to describe growth, complementary to monitoring metabolic activity measurement, such as CER, OUR and heat evolution, which is directly related to growth. For the growth of Aspergillus awamori and Aspergillus oryzae on wheat bran, soybean hulls and rapeseed meal, it was confirmed that colour production was directly proportional to fungal growth. This colourimetric technique was also proved to be a feasible approach for fungal biomass estimation in SmF. This new approach is an important complementation to the existing techniques especially for basic studies. The key finding is that the colourimetric technique demonstrated and provided information of higher quality than that obtained by visual observation or spores counting. The effect of aeration arrangements on moisture content, oxygen (O2), mass and heat transfer during SSF was investigated. A. awamori and A. oryzae were cultivated on wheat bran in newly designed four tray solid state bioreactor (SSB) systems. The new tray SSB systems were: (1) single circular tray SSB, (2) multi-stacked circular tray SSB, (3) Single rectangular tray SSB and (4) multi-square tray SSB. The purpose was to study the effect, on heat and water transfer, of operating variables, fermentation on the perforated base tray and internal moist air circulation under natural and forced aeration. Temperature, O2 and carbon dioxide were measured continuously on-line. Enzyme activity, moisture content and biomass were also measured. The results suggest that the air arrangements examined have a remarkable effect on the quantity of biomass produced using measurement of spores and enzymes production. The strategy presented in these studies allowed quantitative evaluation of the effect of forced internal moist air circulation on the removal of metabolic heat. With the proposed strategy, it was possible to maintain the bed temperatures at the optimum level for growth. However, the effect on moisture content was very different for the two fungi. It was found that the ability of A. oryzae to retain moisture was much higher than that of A. awamori. This is possibly due to the higher levels of chitin in A. oryzae. Greater spores and enzymes (glucoamylase, xylanase and cellulase) production was observed for A. awamori in multi-stacked circular tray and multi-square tray SSB systems compared to the conventional petri dishes and the other two systems. A. oryzae was excellent in producing protease in the same bioreactors. A direct technique of establishing a correlation between fungal growth and CER, OUR, heat evolved was proven successful in this work. The information obtained from CER and OUR led to the estimation of respiratory quotient (RQ). RQ describes the state of the fungal population in the tray SSB and gives an indication of fungal metabolic behaviour. RQ values < 1 were obtained from 38 experiments using four tray SSB systems for the two fungi. A kinetic model based on CO2 evolution instead of biomass concentration was examined in order to simplify the required experiments for kinetic model development. A Gompertz model was used to fit the integrated CO2 data and predict the quantity of CO2 evolution in all experiments. A correlation was found between the heat evolution and CER. The performances of tray SSB systems can be improved by constructing them as multi-trays. The multi-tray systems improved the mass transfer considerably compared with single tray systems. In addition, the multi-tray systems allowed precise measurement of the gradients of CO2, enzymes, spores and fungal biomass. In addition, the air arrangements using moistened air were successful in maintaining moisture content, adequate O2 supply and control of temperature, and hence, increased the productivity of both fungi. Overall A. awamori and A. oryzae have their own ability and performance to degrade and utilise the complex compositions contained in the solid substrate and fermentation conditions may lead to possible comparisons. In addition, multi-stacked circular tray and multi-square tray SSB systems demonstrated an excellent system for further investigations of mass transfer and possibly for large scale operation, though considerable optimisation work remains to be done, for example the height/diameter ratio and total number of trays should be optimised.

The push for alternatives to petroleum fuels has forced researchers to look for highly productive, renewable, non-food resources. The advantages of using microalgae instead of traditional oil crops for biofuel production include high oil yields, rapid reproductive rates, and versatile growing requirements. In order to reduce the cost of producing microalgae based biofuels, wastewater has been used as a nutrient source instead of specialized plant nutrients. The purpose of this study was to compare the relative effectiveness of different combinations of microalgae strain and dairy wastewater for increasing biomass. The methods for monitoring growth included optical density, cell counting, biomass estimation by chlorophyll-a, and volatile suspended solids. The analyses compared four concentrations of wastewater media as well as four strain treatments: Chlorella vulgaris, Tetraselmis sp., mixed freshwater culture and mixed saltwater culture. Optimum wastewater concentrations for microalgae growth were approximately 0% and 25% for most strain treatments. The results of the wastewater treatments concluded that dairy wastewater could serve as an effective nutrient substitute for plant food at concentrations approximately 25%. Chlorella vulgaris and Tetraselmis sp. prevailed over the mixed cultures for biomass production. Nitrate was the most limiting nutrient and exhibited the greatest reductions, sometimes in excess of 90%. The regression equations derived from the volatile suspended solids data achieved high R2 values and determined that total nitrogen, ammonium, and nitrate were significant in the model. In those equations, increasing either ammonium or nitrate yielded an increase in volatile suspended solids. With regards to comparing biomass quantification methods, the two most useful and reliable biomass quantification methods were optical density and volatile suspended solids.

This study aimed at developing allometric equations for the estimation of aboveground biomass of black willow and eastern cottonwood and determine biomass production by these species under several planting spacing and harvest frequency combinations. Logarithmic model with dbh and tree height was the best fitting model for individual tree aboveground biomass estimation of both species. At area level, logarithmic models with stand age, dominant height, and planting density produced the best results. Mixed-effects modeling showed statistically significant effects of harvest frequency for eastern cottonwood but not for black willow. Overall, we conclude that, biomass production of black willow and eastern cottonwood would play a critical role in the fulfillment of the wood energy demands and biomass yields can be enhanced by considering management factors during plantation. These findings will be useful to forest owners in Lower Mississippi Alluvial Valley for estimating biomass without destructive sampling and have optimal biomass production.

Although much emphasis has been given to the analysis of continuous forest conversion in tropical regions, our understanding in detecting, mapping and interpreting the spatial pattern of woodland deforestation and degradation is still limited. This thesis focuses on two factors contributing to this limitation: uncertainties in retrieving woodland change from remote sensing imagery, and the complex processes that may cause woodland deforestation and degradation. Firstly, I investigate approaches to minimising uncertainty in ALOS PALSAR-derived biomass maps by modifying a widely used processing chain, with the aim of provide recommendations for producing radar-based biomass maps with reduced uncertainty. Secondly, to further improve the retrieval of woody biomass from ALOS PALSAR imagery, the semi-empirical Water Cloud Model (WCM) is introduced to account for backscattering from soil. In wooded areas with low canopy (such as the miombo woodland which dominates the study area) the effect from soil moisture on the received backscattered signal is critical. Thirdly, based on the biomass maps retrieved from the refined radar-remote-sensing-based methodology discussed above, the influence of driving variables of the woodland deforestation and degradation, and how they alter the spatial patterns of these two processes, are analysed. The threshold for defining woodland deforestation and degradation in terms of biomass loss intensity is generated through integration of radar-based biomass loss maps, an optical forest cover change map and fieldwork investigation. Multi-linear model simulations of the spatial variation of deforestation and degradation events were constructed at a district and 1 km resolution respectively to rank the relative importance of driving variables. Results suggest that biomass-backscatter relationships based on plots of approximately 1 ha, and processed with high resolution DEMs, are needed for low uncertainty biomass maps using ALOS PALSAR data. Although plots sizes of 0.1 - 0.5 ha lead to large uncertainties, aggregating 0.1 ha plots into larger calibration sites shows some promise even in hilly terrain, potentially opening up the use of common forest inventory data to calibrate remote-sensing-based biomass retrieval models. Such relationships appear to hold across the miombo woodland ecoregion, which implies that there is a consistent relationship at least in the miombo woodland. From this I infer that random error, different processing methods and fitting techniques, and data from small plots are the source of the differences in the savanna biomass-backscatter relationships seen in the literature. The interpreted WCM presented in this study for L-band backscatter at HV polarisation improves biomass retrieval for areas with a biomass value less than 15 tC/ha (or 0.025 m2/m2 in backscatter). Use of the WCM also results in better quality regional biomass mosaics. This is because the WCM helped to improve the correlation of biomass estimation for overlay areas by reducing bias between adjacent paths, especially the bias introduced by changes in soil moisture conditions between different acquisition dates for different paths. Result shows that active and combined soil moisture datasets (from the Climate Change Initiative Soil Moisture Dataset) can be used as effective soil moisture proxies in the WCM for biomass retrieval. This quantitative analysis on the driving variables of woodland deforestation and degradation suggests that large uncertainty exists in modelling the occurrence of deforestation and degradation, especially at a 1 km scale. The spatial patterns of woodland deforestation and degradation differ in terms of shape, size, intensity, and location. Agriculture-related driving variables account for most of the explained variance in deforestation, whereas for degradation, distance to settlements also plays an important role. Deforestation happens regardless of the original biomass levels, while degradation is likely to happen at high biomass areas. The sizes of degradation events are significantly smaller than those of deforestation events, with 90% of deforestation events sharing boundaries with degradation events. This thesis concludes by outlining the importance and difficulties in integrating 'distal' (underlying) drivers in modelling the spatial dynamics of deforestation and degradation. Further work on the causal connection between deforestation and degradation is also needed. The processing chain and biomass retrieval models presented in this study could be used to support monitoring and analysis of biomass change elsewhere in the tropics, and should be compatible with data derived from ALOS-2 and the future SAOCOM and BIOMASS satellite missions.

The automation in the aquaculture is proving to be more and more effective these days. The economic drain on the aquaculture farmers due to the high mortality of the shrimps can be reduced by ensuring the welfare of the animals. The health of shrimps can decline with even barest of changes in the conditions in the farm. This is the result of increase in stress. As shrimps are quite sensitive to the changes, even small changes can increase the stress in the animals which results in the decline of health. This severely dampens the mortality rate in the animals. Also, human interference while feeding the shrimps severely induces the stress on the shrimps and thereby affecting the shrimp’s mortality. So, to ensure the optimum efficiency of the farm, the feeding of the shrimps is made automated. The underfeeding and overfeeding also affects the growth of shrimps. To determine the right amount of food to provide for shrimps, Biomass is a very helpful parameter. The use of artificial intelligence (AI) to calculate the farm's biomass is the project's primary area of interest. This model uses the cameras mounted on top of the tank at densely populated areas. These cameras monitor the farm, and our model detects the biomass. By doing so, it is possible to estimate how much food should be distributed at that particular area. Biomass of the shrimps can be calculated with the help of the number of shrimps and the average lengths of the shrimps detected. With the reduced human interference in calculating the biomass, the health of the animals improves and thereby making the process sustainable and economical.