Full Growth Period Research Articles

Designing an Interactively Cognitive Humanoid Field-Phenotyping Robot for In-Field Rice Tiller Counting

Field phenotyping is a crucial process in crop breeding, and traditional manual phenotyping is labor-intensive and time-consuming. Therefore, many automatic high-throughput phenotyping platforms (HTPPs) have been studied. However, existing automatic phenotyping methods encounter occlusion problems in fields. This paper presents a new in-field interactive cognition phenotyping paradigm. An active interactive cognition method is proposed to remove occlusion and overlap for better detectable quasi-structured environment construction with a field phenotyping robot. First, a humanoid robot equipped with image acquiring sensory devices is designed to contain an intuitive remote control for field phenotyping manipulations. Second, a bio-inspired solution is introduced to allow the phenotyping robot to mimic the manual phenotyping operations. In this way, automatic high-throughput phenotyping of the full growth period is realized and a large volume of tiller counting data is availed. Third, an attentional residual network (AtResNet) is proposed for rice tiller number recognition. The in-field experiment shows that the proposed method achieves approximately 95% recognition accuracy with the interactive cognition phenotyping platform. This paper opens new possibilities to solve the common technical problems of occlusion and observation pose in field phenotyping.

New Antifungal Compound, 6-Pentyl-α-Pyrone, against the Maize Late Wilt Pathogen, Magnaporthiopsis maydis

6-pentyl-α-pyrone (6-PP) is a powerful Magnaporthiopsis maydis antifungal compound, recently discovered when the potent growth medium of Trichoderma asperellum was analyzed. Despite its high potential in plate assay, it was not inspected for plant treatment prevention. Late wilt disease, caused by the fungus M. maydis, threatens commercial maize production in high-risk areas. Thus, the search for control options against the pathogen is one of the top priorities in Israel, Egypt, and other countries. Disease-resistant maize genotypes can reduce the damages. Yet, aggressive variants of the fungus can overcome host resistance. The current study aimed at inspecting T. asperellum and its secreted metabolite, pure 6-PP, against the pathogen in plants over a full growth period. First, adding T. asperellum directly to seeds with sowing provides significant protection to sprouts (up to 42 days) in a growth room, with more than two-fold growth promotion and reduced pathogen root infection (detected by real-time PCR). The same procedure applied in a commercial field was less beneficial in rescuing the plants’ growth and yield. Still, it reduced the cobs’ symptoms by 11% and resulted in nine-fold lower levels of the pathogen’s DNA in the stem tissue. Second, the T. asperellum purified 6-PP compound (30 µg/seed) was used in seed coating and tested against the T. asperellum secretory metabolites’ crude (diluted to 50%). At the season’s end, these treatments improved plant biomass by 90–120% and cob weight by 60%. Moreover, the treatments significantly (p < 0.05) reduced the symptoms (up to 20%) and pathogen infection (94–98%). The current study’s results reveal the potential of 6-PP as a new fungicide against M. maydis. Such a treatment may protect maize plants from other soil diseases.

Fresh/brackish watering at growth period provided a trade-off between lettuce growth and resistance to NaCl-induced damage

Supply with fresh and brackish water at different growth periods of crops is an effective strategy to alleviate freshwater shortage and ensure food security. However, the potential mechanisms are not well understood. To bridge this gap, comparative physiological, transcriptomic and metabolomic profiling was used to analyze lettuce grown under four treatments [exposure to non-saline (NS) nutrient solution during full growth period, NS-NS; exposure to saline (S, 30 mM NaCl added to NS) nutrient solution during early, later or full growth period, S-NS, NS-S and S-S]. The results showed that after brackish water exposure, lettuce showed growth inhibition and reactive oxygen species accumulation, and the dry weight was significantly reduced under S-NS and S-S but not NS-S. NS-S saved fresh water consumption compared to NS-NS and significantly improved the brackish water use efficiency compared to S-NS and S-S. In addition, brackish water exposure regulated the antioxidant system, and activated the metabolic process related to sugar synthesis. Together, this study provides evidence of the protective roles of exposure to brackish water for only later of the lettuce growth period, and it's a valuable water supply reference for cultivating crops with brackish water in water-scarce regions.

Mapping Winter Wheat with Optical and SAR Images Based on Google Earth Engine in Henan Province, China

The timely and accurate acquisition of winter wheat acreage is crucial for food security. This study investigated the feasibility of extracting the spatial distribution map of winter wheat in Henan Province by using synthetic aperture radar (SAR, Sentinel-1A) and optical (Sentinel-2) images. Firstly, the SAR images were aggregated based on the growth period of winter wheat, and the optical images were aggregated based on the moderate resolution imaging spectroradiometer normalized difference vegetation index (MODIS-NDVI) curve. Then, five spectral features, two polarization features, and four texture features were selected as feature variables. Finally, the Google Earth Engine (GEE) cloud platform was employed to extract winter wheat acreage through the random forest (RF) algorithm. The results show that: (1) aggregated images based on the growth period of winter wheat and sensor characteristics can improve the mapping accuracy and efficiency; (2) the extraction accuracy of using only SAR images was improved with the accumulation of growth period. The extraction accuracy of using the SAR images in the full growth period reached 80.1%; and (3) the identification effect of integrated images was relatively good, which makes up for the shortcomings of SAR and optical images and improves the extraction accuracy of winter wheat.

Robust retrieval of soil moisture at field scale across wide-ranging SAR incidence angles for soybean, wheat, forage, oat and grass

Surface soil moisture is estimated by inverting physical scattering models for low- crops using L-band airborne SAR data over the incidence angle range from 30 to 50°. The forward simulation is accurate with 1.7, 1.8, and 2.3 dB rmse for grass, wheat (including oat and forage), and soybean respectively assessed over 38 fields and during the full growth period for soybean. Dominant scattering mechanisms revealed by the model are found consistent across the incidence angle range: surface (VV) and double bounce (HH) for grass, double bounce for both polarization of wheat, and surface (young plant) and volume (mature plant) for both polarization of soybean. The model fidelity is robust across incidence angles between 30 and 50°, benefiting from rigorously simulating the three scattering mechanisms and successfully simulating the effect of vegetation and roughness.The soil moisture estimates are accurate to unbiased rmse of 0.041, 0.059 and 0.060 m3/m3 and correlation of 0.71, 0.83, and 0.69 for grass, wheat, and soybean fields, respectively over the soil moisture dynamic range up to 0.5 m3/m3, and soybean's full growth cycle. Vegetation water content and surface roughness are retrieved simultaneously to the soil moisture solutions, thus constraining the inversion of soil moisture. The retrieval performance is fairly uniform across the incidence angle, partly because of the reliable forward modeling across the incidence angle and also thanks to the reliable retrieval strategy. The robustness against the incidence angle supports frequent global mapping.The use of both HH and VV offers superior soil moisture retrievals than single-channel VV or HH input perfoms, by 0.034 m3/m3 unbiased rmse for grass and by 0.01 m3/m3 for wheat and soybean. The VV-based retrieval performed better than HH for grass and soybean, where surface scattering was important, but either choice resulted in similar retrieval accuracy for double-bounce dominanted wheat. No need for quad-pol and multi-angular observations would allow the retrieval approach to be applicable for spaceborne global mapping.

Crop Cycle and Tillage Role in the Outbreak of Late Wilt Disease of Maize Caused by Magnaporthiopsis maydis.

The destructive maize late wilt disease (LWD) has heavy economic implications in highly infected areas such as Israel, Egypt, and Spain. The disease outbreaks occur near the harvest, leading to total yield loss in severe cases. Crop rotation has long been known as an effective means to reduce plant diseases. Indeed, agricultural soil conservation practices that can promote beneficial soil and root fungi have become increasingly important. Such methods may have a bioprotective effect against Magnaporthiopsis maydis, the LWD causal agent. In this two-year study, we tested the role of crop rotation of maize with either wheat or clover and the influence of minimum tillage in restricting LWD. In the first experiment, wheat and clover were grown in pots with LWD infected soil in a greenhouse over a full winter growth period. These cultivations were harvested in the spring, and each pot’s group was split into two subgroups that underwent different land processing practices. The pots were sown with LWD-sensitive maize cultivar and tested over a whole growth period against control soils without crop rotation or soil with commercial mycorrhizal preparation. The maize crop rotation with wheat without tillage achieved prominent higher growth indices than the control and the clover crop cycle. Statistically significant improvement was measured in the non-tillage wheat soil pots in sprout height 22 days after sowing, in the healthy plants at the season’s end (day 77), and in shoot and cob wet weight (compared to the control). This growth promotion was accompanied by a 5.8-fold decrease in pathogen DNA in the plant stems. The tillage in the wheat-maize growth sequence resulted in similar results with improved shoot wet-weight throughout the season. In contrast, when maize was grown after clover, the tillage reduced this parameter. The addition of commercial mycorrhizal preparation to the soil resulted in higher growth measures than the control but was less efficient than the wheat crop cycle. These results were supported by a subsequent similar experiment that relied on soil taken from commercial wheat or clover fields. Here too, the wheat-maize growth cycle (without permanent effect for the tillage) achieved the best results and improved the plants’ growth parameters and immunity against LWD and lowered pathogen levels. In conclusion, the results of this study suggest that wheat and perhaps other crops yet to be inspected, together with the adjusted tillage system, may provide plants with better defense against the LWD pathogen.

Variation and attribution of water use efficiency in sunflower and maize fields in an irrigated semi‐arid area

AbstractWater use efficiency (WUE) links carbon and water exchanges between farmlands and the atmosphere. Understanding the variation and attribution of WUE is essential to reveal the physiological and ecological adaptation mechanisms of crops to the changing environment, and to better allocate, regulate and conserve water resources. However, few studies on the variation and attribution of WUE have been conducted in irrigated arid or semi‐arid farmlands. Therefore, in this study, water and carbon fluxes were measured using eddy covariance systems in two farmlands (one sunflower field and one maize field) in a semi‐arid irrigation district in China. It was found that the average WUE of sunflower during its full growth period was 1.72 g C kg−1 H2O, much lower than that of maize (4.07 g C kg−1 H2O). At each growth stage, the WUE of both crops were negatively correlated with vapour pressure deficit (VPD), net radiation (Rn) and soil water content (SWC). The negative correlations could be attributed to the arid meteorological condition and the relatively abundant soil moisture due to irrigation and shallow groundwater levels. VPD was the main factor affecting WUE, followed by Rn and SWC. It was also found that the response of WUE to crop leaf area index (LAI) and to canopy conductance (gc) depended on the VPD ranges: when VPD increased, the response of WUE to LAI and to gc decreased. Our findings could improve the understanding of the coupling effect of water and carbon fluxes over farmland ecosystems in arid and semi‐arid irrigation areas and help improve agricultural production and save water resources in such areas.

Spectrum- and RGB-D-Based Image Fusion for the Prediction of Nitrogen Accumulation in Wheat

The accurate estimation of nitrogen accumulation is of great significance to nitrogen fertilizer management in wheat production. To overcome the shortcomings of spectral technology, which ignores the anisotropy of canopy structure when predicting the nitrogen accumulation in wheat, resulting in low accuracy and unstable prediction results, we propose a method for predicting wheat nitrogen accumulation based on the fusion of spectral and canopy structure features. After depth images are repaired using a hole-filling algorithm, RGB images and depth images are fused through IHS transformation, and textural features of the fused images are then extracted in order to express the three-dimensional structural information of the canopy. The fused images contain depth information of the canopy, which breaks through the limitation of extracting canopy structure features from a two-dimensional image. By comparing the experimental results of multiple regression analyses and BP neural networks, we found that the characteristics of the canopy structure effectively compensated for the model prediction of nitrogen accumulation based only on spectral characteristics. Our prediction model displayed better accuracy and stability, with prediction accuracy values (R2) based on BP neural network for the leaf layer nitrogen accumulation (LNA) and shoot nitrogen accumulation (SNA) during a full growth period of 0.74 and 0.73, respectively, and corresponding relative root mean square errors (RRMSEs) of 40.13% and 35.73%.

Responses of CO2 and N2O emissions from soil-plant systems to simulated warming and acid rain in cropland

Climate warming is anticipated to change the terrestrial carbon/nitrogen cycle through its impact on the fluxes of greenhouse gases such as CO2 and N2O. This study investigated the effect of diurnal warming and acid rain on CO2 and N2O emissions from soil-plant systems in a winter wheat–soybean rotation cropland. Field rotational experiments of winter wheat and soybean were conducted by simulating diurnal warming and acid rain. Manipulated experiments included the control (CK), diurnal warming (T, + 2 °C), acid rain (AR, pH = 2.5), and the combined treatment (TAR, + 2 °C and acid rain). CO2 and N2O fluxes from soil-plant systems were measured using a static chamber-gas technique. The results showed that in the winter wheat and soybean growing seasons, compared with CK treatment, T, AR, and TAR treatments did not change the accumulative amount of CO2 emission (AAC) across the full growth period (p ˃ 0.05), although T treatment significantly increased soil AAC (p < 0.05) at the grain filling-maturity stage. On the contrary, T and AR treatments significantly increased the accumulative amount of N2O emission (AAN) in winter wheat and soybean croplands (p < 0.05), which was attributed to leaf nitrate reductase activity, total biomass, and soil NO3−–N content. In addition, there was a significant interaction between warming and acid rain on N2O flux. The AAN from the winter wheat cropland under treatments was in the order: TAR ˃ AR ˃ T ˃ CK. Our findings suggest that diurnal warming and acid rain had no significant effect on CO2 emissions from soil-plant systems, but significantly increase N2O emissions in winter wheat and soybean growing seasons. Moreover, diurnal warming would strengthen the positive effect of acid rain on N2O emissions from soil-plant systems in winter wheat farmland.

Key Stage of As Accumulation in Rice Under As Stress at Different Growth Stages

The absorption and accumulation of As at different stages of rice growth are significantly different. To study the key growth stages of As accumulation in brown rice and to determine the contribution of As accumulation at different growth stages to As contribution in brown rice, a rice hydroponics experiment was carried out by adding external As during the different rice growth stages: tillering stage (30 d), jointing stage (16 d), booting stage (13 d), filling stage (17 d), dough stage (15 d), maturity stage (13 d), and full growth period (104 d). The results showed that: ① As stress at different growth stages had a significant effect on the biomass of rice plants. In comparison with the control CK, the treatments of As stress with five single-stages decreased the rice biomass, except during the tillering stage. Among these treatments, although the As stress at booting stage had the lowest rice biomass, the biomass of all the rice plants were higher than that for As stress in the full growth period. ② The content of As in brown rice for all the treatments of As stress at six single-stages, ranging from 0.08-0.24 mg ·kg-1, was higher than that of CK. Among these six treatments, the As stress at booting stage had the highest As content in brown rice, accounting for 64.9% of the As content in the full growth period. ③ The accumulation of As in brown rice for all the treatments of As stress at six single-stages was higher than that of CK, and ranged from 1.4-1.5 μg ·plant-1. Among these six treatments, the As stress at booting stage had the highest As accumulation, followed by filling stage. The accumulation of As in brown rice treated with As stress was highest in the full growth period with a value of 5.7 μg ·plant-1. ④ The relative contribution of As stress at the booting stage was the highest for the As accumulation in brown rice and reached to 40.3%, followed by filling stage with 26.0%. Therefore, the rice growth stages of the booting stage and filling stage were the key stages of As accumulation in brown rice.

Effects of biodegradable mulch on soil water and heat conditions, yield and quality of processing tomatoes by drip irrigation

To combat the problem of residual film pollution and ensure the sustainable development of agriculture in oasis areas, a field experiment was carried out in 2019 at the Wuyi Farm Corps Irrigation Center Test Station in Urumqi, Northwest China. Four types of biodegradable mulches, traditional plastic mulchs and a control group (bare land; referred to as CK) were compared, including a total of six different treatments. Effects of mulching on soil water and heat conditions as well as the yield and quality of processing tomatoes under drip irrigation were examined. In addition, a comparative analysis of economic benefits of biodegradable mulches was performed. Principal component analysis and gray correlation analysis were used to evaluate suitable mulching varieties for planting processing tomatoes under drip irrigation. Our results show that, compared with CK, biodegradable mulches and traditional plastic mulch have a similar effect on retaining soil moisture at the seedling stage but significantly increase soil moisture by 0.5%–1.5% and 1.5%–3.0% in the middle and late growth periods (P<0.050), respectively. The difference in the thermal insulation effect between biodegradable mulch and plastic mulch gradually reduces as the crop grows. Compared with plastic mulch, the average soil temperature at 5–20 cm depth under biodegradable mulches is significantly lowered by 2.04°C–3.52°C and 0.52°C–0.88°C (P<0.050) at the seedling stage and the full growth period, respectively, and the water use efficiency, average fruit yield, and production-investment ratio under biodegradable mulches were reduced by 0.89%–6.63%, 3.39%–8.69%, and 0.51%–6.33% (P<0.050), respectively. The comprehensive evaluation analysis suggests that the black oxidized biological double-degradation ecological mulch made from eco-benign plastic is the optimal film type under the study condition. Therefore, from the perspective of sustainable development, biodegradable mulch is a competitive alternative to plastic mulch for large-scale tomato production under drip irrigation in the oasis.

Predicting copper contamination in wheat canopy during the full growth period using hyperspectral data.

The rapid and efficient determination of heavy metal content in food crops is essential for human health and environmental protection. The use of hyperspectral data has become a popular way to predict heavy metal content in plants; however, many challenges remain. One challenge is that lab conditions differ from actual agricultural production conditions. Another challenge is that spectral data characteristics are not universally applicable to all situations. Therefore, in this study, the field test method was adopted to conduct experiments during the full growth period of wheat, and the spectrum data of wheat canopy were processed by the first derivative method to screen-sensitive spectral bands as the basis for the prediction model of the copper content in wheat. The results showed that the copper content increased with an increase in the soil copper content, and there were dissimilar subtle differences in the spectral reflectance of wheat canopy under different stressed soil copper concentrations; sensitive spectral indices and wavelengths were screened based on good correlation with the copper content in the wheat canopy. Different optimal predicting models in different periods were built and verified. The established linear regression models, which were based on NDVI/SIPI and W728, were the most suitable predicting models during the tillering stage with R2 = 0.669 and 0.818; Rg, W741, and multiple bands were the most suitable predicting models during the jointing stage with R2 = 0.548, 0.830, and 0.868; the optimal model during the heading stage was based on W480 (R2 = 0.625). This study demonstrated that the constructed models had good potential for estimating the copper content in wheat leaves during full growth periods, and this method had the potential to be applied to the actual agricultural production process.

An Improved Photosynthesis Prediction Model Based on Artificial Neural Networks Intended for Cucumber Growth Control

Abstract. The existing photosynthetic rate prediction models consider only a single growing season. However, a photosynthetic rate prediction model intended for full growth of crops is needed. Therefore, a photosynthetic rate prediction model based on artificial neural networks (ANN), which establishes the prediction of the entire photosynthetic process, is presented in this article. The proposed model was developed using the multi-factor photosynthetic rate data obtained by experiments on cucumber seedlings and flowering stage. The ANN model was trained with the Levenberg-Marquardt (LM) training algorithm. In contrast to the single-phase photosynthetic rate prediction models, in the proposed model a fusion of parameters of all growing stages was applied, whereat all growing parameters were merged into one six-dimensional input signal (temperature, CO2 concentration, light intensity, relative humidity, chlorophyll content, and growth stage). Verification of model accuracy and performance has shown that merging of growing parameters has obvious advantage. Moreover, the proposed model satisfied the requirement in terms of training error. In addition, the determination correlation between measured and estimated values was 0.9517, thus, good correlation and estimation were achieved. Besides, the test average absolute error was 1.1454, which proves a high accuracy of the proposed model. Therefore, the proposed prediction model can provide the theoretical basis for the facilities light regulation and technical support. Keywords: Artificial neural networks, Cucumber, Full growth period, Photosynthetic rate, Prediction model.

Cadmium phytoextraction from loam soil in tropical southern China by Sorghum bicolor

ABSTRACTThe cadmium (Cd) uptake characteristics by Sorghum bicolor cv. Nengsi 2# and Cowley from the acidic sandy loam soil (pH = 6.1) during the entire growth period (100 days) were investigated in pot outdoors in a tropical district of southern China, Hainan Island. The Cd-spiked levels in soil were set as 3 and 15 mg/kg. Correspondingly, the available Cd levels in soil extracted by Mehlich III solution were 2.71 and 9.41 mg/kg, respectively. Basically, two varieties in a full growth period (100 days) did not show a significant difference in their growth and Cd uptake. Under high Cd stress, the plant growth was inhibited and its biomass weight and height decreased by 38.7–51.5% and 27.6–28.5%, respectively. However, S. bicolor showed higher bioaccumulation capability of Cd from soil to plant [bioconcentration factor (BCF)>4], and higher transfer capability of Cd from roots to shoots [translocation factor (TF)>1] under high Cd stress; Cd contents in the roots, stems, and leaves of S. bicolor reached 43.79–46.07, 63.28–70.60, and 63.10–66.06 mg/kg, respectively. S. bicolor exhibited the potential phytoextraction capability for low or moderate Cd-contamination in acidic sandy loam soil.

A novel Brassica-rhizotron system to unravel the dynamic changes in root system architecture of oilseed rape under phosphorus deficiency.

An important adaptation of plants to phosphorus (P) deficiency is to alter root system architecture (RSA) to increase P acquisition from the soil, but soil-based observations of RSA are technically challenging, especially in mature plants. The aim of this study was to investigate the root development and RSA of oilseed rape (Brassica napus L.) under low and high soil P conditions during an entire growth cycle. A new large Brassica-rhizotron system (approx. 118-litre volume) was developed to study the RSA dynamics of B. napus 'Zhongshuang11' in soils, using top-soils supplemented with low P (LP) or high P (HP) for a full plant growth period. Total root length (TRL), root tip number (RTN), root length density (RLD), biomass and seed yield traits were measured. TRL and RTN increased more rapidly in HP than LP plants from seedling to flowering stages. Both traits declined from flowering to silique stages, and then increased slightly in HP plants; in contrast, root senescence was observed in LP plants. RSA parameters measured from the polycarbonate plates were empirically consistent with analyses of excavated roots. Seed yield and shoot dry weights were closely associated positively with root dry weights, TRL, RLD and RTN at both HP and LP. The Brassica-rhizotron system is an effective method for soil-based root phenotyping across an entire growth cycle. Given that root senescence is likely to occur earlier under low P conditions, crop P deficiency is likely to affect late water and nitrogen uptake, which is critical for efficient resource use and optimal crop yields.

Experimental investigation of frost formation on a parallel flow evaporator

This paper experimentally studied the frosting process of a folded–louvered-fin, parallel flow microchannel evaporator in a heat pump central air-conditioning system under three conditions, in which three open states of two capillaries were adopted. Surface temperature distribution on evaporator was measured by 16 thermocouples buried on the leeward side. Mesoscale frost formation processes on its front view surface for three different test conditions were observed using a Charge Coupled Device (CCD) camera. The results showed that the surface temperature distribution on the parallel flow evaporator was uneven and initial frost formation generally started on some partial surface areas of the louvered fins whose surface temperature was lowest after the heat pump system running 6 min later under conditions B and C, while the evaporator began to frost after 8 min under condition A. The non-uniform surface temperature distribution caused by the unequal distribution of the refrigerant flux in the flat tubes’ microchannels resulted in uneven distribution of frost. The ice crystals distribution and frost thickness in frost period could be obtained by the digital image processing method in which the initial pictures were converted into binary image. The results indicated that in a thin layer near fins’ surface, ice crystals had relatively high occupancy rate in the frost growing period and full growth period; the occupancy rate of ice crystals decreased almost linearly with the increasing of the frost thickness (frost height), where the decreasing rate in the frost full grown period was less than that in the frost growing period (in 0.1 mm frost thickness condition, the occupancy rate of ice crystals decreased to 58% in the frost growing period, while in the frost full grown period occupancy rate of ice crystals decreased to 90%; and in 0.25 mm frost thickness, they were 0%, 45% respectively). Furthermore, it can be found that the frost thickness increased as the time increasing and then finally reached maximum values of 0.3 mm, 0.35 mm, and 0.32 mm respectively at three conditions.

Mercury uptake by Silene vulgaris grown on contaminated spiked soils

Mercury is a highly toxic pollutant with expensive clean up, because of its accumulative and persistent character in the biota. The objective of this work was to evaluate the effectiveness of Silene vulgaris, facultative metallophyte which have populations on both non-contaminated and metalliferous soils, to uptake Hg from artificially polluted soils. A pot experiment was carried out in a rain shelter for a full growth period. Two soils (C pH = 8.55 O.M. 0.63% and A pH = 7.07 O.M. 0.16%) were used, previously contaminated with Hg as HgCl(2) (0.6 and 5.5 mg Hg kg(-1) soil). Plants grew healthy and showed good appearance throughout the study without significantly decreasing biomass production. Mercury uptake by plants increased with the mercury concentration found in both soils. Differences were statistically significant between high dosage and untreated soil. The fact that S. vulgaris retains more mercury in root than in shoot and also, the well known effectiveness of these plants in the recovering of contaminated soils makes S. vulgaris a good candidate to phytostabilization technologies.

CLIMATIC CONDITIONS DURING GROWTH RELATE TO RISK OF PINK LADY™ APPLES DEVELOPING FLESH BROWNING DURING STORAGE

Climactic conditions during two distinct periods of the growth and development of Pink Lady™ apples may be associated with the development of two expressions of flesh browning (FB) symptoms. The expression of symptoms has been linked to certain seasonal and storage conditions, growing district and several other factors have been implicated in the development of the disorder over the last two seasons. The variation between districts could be related to climatic conditions, for example low temperatures during the 50 days after full bloom growth period are speculated to increase the risk of CO 2 injury during storage as the cooler growing conditions result in more dense fruit with reduced gas diffusivity. Such fruit may accumulate high internal levels of CO 2 resulting in a predisposition to develop CO 2 related FB known as radial FB. Pink Lady™ apples grown in districts experiencing <1200 cumulative growing degree days from full bloom to harvest are at an increased risk of diffuse FB. Another climatic risk is if there is a low diurnal temperature variation during the 60 days prior to harvest maturity which is associated with reduced blush colour development. This situation results in growers delaying harvest in order to maximise the development of blush in order to meet strict quality guidelines designed for marketing of the cultivar under the trademark. Such fruit have an increased risk of developing both types of FB. Our results also show that the risk of developing both types of FB is higher with advanced fruit maturity at harvest. The atmospheric conditions and length of time of storage have also been shown to influence the severity of the disorder.

Identification and mapping of a major gene (Ft1) involved in fructification time in the interspecific cross Coffea pseudozanguebariae x C. liberica var. Dewevrei: impact on caffeine content and seed weight.

Fructification time was studied in the interspecific cross Coffea pseudozanguebariae x C. liberica var. Dewevrei (PSE x DEW). Parental species, F(1) hybrids and offspring of the first backcross generation (BC(1)), consisting of F(1) x PSE (BCPSE) and F(1) x DEW (BCDEW) plants, were observed. Fructification time can be split into two independent visual phases: the full-growth period, from blooming up to the end of fruit growth, and the maturation phase, defined by the green to red color change. Fructification time was found to be an additive trait. The full-growth period showed a bimodal distribution in the BCDEW hybrid, suggesting the involvement of Ft1, a major gene that was mapped on linkage group E. The main effects of Ft1 were to lower caffeine content and 100-seed weight, without any impact on chlorogenic acid, trigonelline and sucrose contents. Two molecular markers were identified that bracket Ft1 and which could be used for early marker-assisted selection.

Automated Weighing of Group-housed, Growing-finishing Swine

A system for automated acquisition of the mean pig weight from a group of growing-finishing animals was developed and tested. Each time an animal entered a crate to obtain a drink of water, a time series of weights was recorded. A state machine representation was implemented to capture weight events and to put time series weight recordings into a queue. Three algorithms (mean, histogram, and median) were devised and evaluated to extract animal weight from the time series recording. Four tests were performed—short-term tests included test 1 with 12 animals of 64.5 to 96.4 kg initial weight; test 2 with 8 animals of 70.9 to 75 kg; test 3 with 3 individual animals of 45, 68, and 93 kg; and test 4 was for a full growth period with 10 animals. The first three experiments were used to develop and refine the system, and test 4 was used to assess the long-term performance and feasibility. Comparisons between estimated weight and “spot checks” with a mechanical scale were typically within about ±1% over test 4. The histogram algorithm was found to be the best for estimating average weight. Accuracy was not affected by variation in animal weight (tests 1 and 2); however, different length data windows affected accuracy and a 4-h window was best. A time series queue of at most 150 s of data was found to be adequate and the histogram algorithm was successful with as few as 10 data points. Locating the sole water supply within the weigh crate did not affect growth rate compared to a control group. A change rate (CR) index was devised to compare daily activity and to flag pen health problems