Marc Tchamitchian

Optimal temperature regimes for a greenhouse crop with a carbohydrate pool: A modelling study

Abstract A simple crop model with two state variables, namely structural biomass and carbohydrate pool, was used to explore the effect of alternative temperature regimes on greenhouse crop production. Assuming a repeated environmental cycle, certain qualitative predictions could be made. (1) The smaller the plants and the higher the light integral and CO2 enrichment, the higher are the temperatures which lead to maximum production. (2) Day temperatures higher than night temperatures usually lead to higher production. On winter days, however, an inverse temperature regime may result in energy saving without loss of production. (3) Temperature variations may often be tolerated, provided that the mean temperature (temperature integral) is maintained at the level appropriate for maximum production. A limited amount of published experimental data was used to fit the model, leading to a satisfactory agreement.

Influence of cultivar, fruit position and seed content on tomato fruit weight during a crop cycle under low and high competition for assimilates

SummaryThe control of tornato fruit weight during a crop cycle may be of commercial benefit. To assess the main causes of variability in the potential and actual fruit weight of mature fruit, both were measured together with the seed content on three tomato cultivars. Potential and actual weight were appraised on plants with single-fruit and seven-fruit trusses, respectively, until maturation of the fifteenth truss. Variability in the potential weight was mainly related to the cultivar, whereas differences between proximal and distal fruits were significant for beefsteak tomatoes only. In the long term, no truss effect on this potential could be detected. Under competitive growth conditions, the weight of distal fruits was reduced more than that of proximal fruits especially for the beefsteak cultivar. All trusses were not equally affected, inducing a large variability along the stem. The relation between fruit weight and seed number was closer as the range of variability in fruit weight was reduced, that...

A Pragmatic Approach to Assess the Exposure of the Honey Bee (Apis mellifera) When Subjected to Pesticide Spray

Plant protection spray treatments may expose non-target organisms to pesticides. In the pesticide registration procedure, the honey bee represents one of the non-target model species for which the risk posed by pesticides must be assessed on the basis of the hazard quotient (HQ). The HQ is defined as the ratio between environmental exposure and toxicity. For the honey bee, the HQ calculation is not consistent because it corresponds to the ratio between the pesticide field rate (in mass of pesticide/ha) and LD50 (in mass of pesticide/bee). Thus, in contrast to all other species, the HQ can only be interpreted empirically because it corresponds to a number of bees/ha. This type of HQ calculation is due to the difficulty in transforming pesticide field rates into doses to which bees are exposed. In this study, we used a pragmatic approach to determine the apparent exposure surface area of honey bees submitted to pesticide treatments by spraying with a Potter-type tower. The doses received by the bees were quantified by very efficient chemical analyses, which enabled us to determine an apparent surface area of 1.05 cm2/bee. The apparent surface area was used to calculate the exposure levels of bees submitted to pesticide sprays and then to revisit the HQ ratios with a calculation mode similar to that used for all other living species. X-tomography was used to assess the physical surface area of a bee, which was 3.27 cm2/bee, and showed that the apparent exposure surface was not overestimated. The control experiments showed that the toxicity induced by doses calculated with the exposure surface area was similar to that induced by treatments according to the European testing procedure. This new approach to measure risk is more accurate and could become a tool to aid the decision-making process in the risk assessment of pesticides.

Lettuce cropping with less pesticides. A review

Agricultural intensification has increased crop productivity but decreased agroecosystem services. Agricultural intensification is occurring notably for horticultural crops such as lettuce. In conventional agriculture, lettuce protection is achieved mostly by preventive applications of pesticides with about eight treatments for a 60–90-day-long cycle in the Mediterranean region. However, new sustainable control strategies are needed due to pesticide impact on environment and human health, emerging pesticide resistance, and stricter policies on levels of pesticide residues in food. Here, we review knowledge and methods allowing to grow lettuce with less pesticides. Advances shown are based on pest ecology and pathogen control by the agroecosystem. The major points are as follows: (1) pest and pathogen community composition depends partly on climatic conditions. The identification of pests and pathogens that can threaten the crop is the first step to design innovative lettuce cropping systems less dependent on pesticides. (2) The numerous alternative techniques currently available should be combined to control lettuce pests and pathogens. The effects of alternative techniques on non-target organisms including non-target pests are poorly known so far. (3) Designing sustainable systems requires taking into account ecological interactions and suitability of different management techniques of low impact.

Agrifood systems and the microbial safety of fresh produce: Trade-offs in the wake of increased sustainability.

Fresh produce has been a growing cause of food borne outbreaks world-wide prompting the need for safer production practices. Yet fresh produce agrifood systems are diverse and under constraints for more sustainability. We analyze how measures taken to guarantee safety interact with other objectives for sustainability, in light of the diversity of fresh produce agrifood systems. The review is based on the publications at the interface between fresh produce safety and sustainability, with sustainability defined by low environmental impacts, food and nutrition security and healthy life. The paths for more sustainable fresh produce are diverse. They include an increased use of ecosystem services to e.g. favor predators of pests, or to reduce impact of floods, to reduce soil erosion, or to purify run-off waters. In contrast, they also include production systems isolated from the environment. From a socio-economical view, sustainability may imply maintaining small tenures with a higher risk of pathogen contamination. We analyzed the consequences for produce safety by focusing on risks of contamination by water, soil, environment and live stocks. Climate change may increase the constraints and recent knowledge on interactions between produce and human pathogens may bring new solutions. Existing technologies may suffice to resolve some conflicts between ensuring safety of fresh produce and moving towards more sustainability. However, socio-economic constraints of some agri-food systems may prevent their implementation. In addition, current strategies to preserve produce safety are not adapted to systems relying on ecological principles and knowledge is lacking to develop the new risk management approaches that would be needed.

SERRISTE: Daily Greenhouse Climate Set-Point Determination for Tomatoes

Abstract SERRISTE is a decision support system providing suitable climatic setpoints for the production of greenhouse tomatoes. The system is based on an analysis of the practices as they can be defined by expert growers and agronomists, and expressed as a set of constraints. The most significant ones links the day and night temperatures to the forecasted solar radiation, to balance the rates of growth and development with that of the photosynthesis. Additional physical knowledge is used to determine the necessary set-points from the goal mean temperatures. SERRISTE has been tested in southern and western France in extension services and has proven its capability to ensure a good if not better production at a lower cost.

Optimal Control of the Daily Greenhouse Climate: Physical Approach

Abstract A dynamic model of the physical aspects of the greenhouse climate has been set, simulating an empty greenhouse and including a description of the air, cover and floor temperature and the air humidity ratio. An optimal controller, based on Pontryagins maximum principle, is defined. The goal of the criterion is to reach a target mean temperature, while sparing energy. The main behaviour of the controller, due to the formulation of the criterion, is that it tends to apply constant controls, not taking advantage of the a-priori knowledge of the outside weather.

Agroecological Engineering to Biocontrol Soil Pests for Crop Health

Feeding a growing population and ensuring food security whilst protecting ecosystems and natural resources are crucial priorities in times of global changes. Agroecology promotes innovative drivers of change for a smart agriculture that meets the specifications of ecological transition. Managing soil interactions offer largely unexplored potential to increase agricultural yields and reduce pressures on the environment. Crop losses of 10 % are due to soil-borne pests causing root rot, root blackening, wilt, stunting or seedling damping-off. One promising approach is to encourage pest regulation provided by soil interactions to decrease the inputs of pesticides. However, limited success of this approach in field applications raises questions as to how this might be best accomplished.

On the Selection of Appropriate Control System Design Methodologies

High speed conversion of an analog input signal to a digital output signal is performed by applying the analog input to an input of a unity gain amplifier. During a first pass, an output signal produced by the amplifier is applied to inputs of each of a plurality of comparators. A first group of successively larger reference voltages are applied to reference inputs of the comparators, respectively. A plurality of the comparators switch in response thereto to produce output signals indicative of a range within which the output of the amplifier lies. The outputs of the comparators are encoded to effectuate conversion thereof to an analog representation of the amplifier output. The analog representation is compared to the analog input signal and the difference therebetween is applied to the input of the amplifier. During another pass another group of reference voltages, each substantially lower than corresponding values thereof during the previous pass, are applied to the reference inputs of the comparators. Binary representations of the outputs of the comparators during each of the passes are combined into a binary word accurately representing the analog input signal.

DAILY TEMPERATURE OPTIMISATION IN GREENHOUSE BY REINFORCEMENT LEARNING

Abstract The goal of this study is to show the usefulness of reinforcement learning (RL) to solve a common greenhouse climate optimisation problem. The problem is to minimise the daily heating cost while achieving simultaneously two agronomic goals, namely maintaining a good crop growth and an appropriate development rate. The complexity of the problem is due to the very different time constants of these two biological processes. First, a simple model for greenhouse roses is presented that simulates the daily crop growth and development. Second, the RL method is presented, in its application to this problem. Finally, optimisation results are presented and discussed.