Evaluation of feeding different forms of therapeutic diet on the feed intake, digestibility, feed efficiency, and growth of calves experimentally infected with foot-mouth disease virus.

Oral ulcers induce acute weight loss due to anorexia in foot-and-mouth disease virus (FMDV) infected cattle. We hypothesized that providing a palatable form of a therapeutic diet (TD) in different physical forms would increase the feed intake, digestibility and restoration of body weight. A TD was formulated with 19% CP and 2.9 Mcal ME/kg on dry matter basis. Bull calves of 10-12 months with mean body weight of 123 ± 1.3 kg were experimentally infected with FMDV (n = 18) and offered one of the following three forms of the TD (n = 6/group) for 6 weeks post-FMDV infection (WPI): (i) TD in mash form (TDM) (ii) TD in cooked form (TDC) and (iii) TDC + customised nutrient supplement (TDCNS) such as Zn, Cu, Cr, Mn, and Se. The CNS was fed before the TDC. A group of uninfected control (n = 4) was fed TDM. Green fodder was offered in the afternoon. Dry matter intake (DMI) of TD and green fodder were recorded at 24 h interval till WPI 6. Body weight (BW) was recorded at weekly interval. Digestibility trial was conducted at WPI 6. The palatability of the TD was scored from 1- 4 and healing of tongue ulcers was analyzed by Kaplan-Meier survival curve. The results indicated that the physical form of TD increased the total DMI by WPI 3, which was supported by the restoration of BW and higher palatability score. The digestibility of all the proximate principles except EE was significantly higher (P < 0.05) in the groups that were fed TDC. It was concluded that feeding TD irrespective of the physical form, restored the ADG and DMI in the calves by WPI 3. Further, feeding cooked form of TD increased the digestibility in the FMDV infected calves and supplementation of CNS hastened the healing of glossal ulcers.

Biomass and nitrogen fixation dataset of Pisum sativum L. and Vicia faba L. cultivated under elevated CO2 and nitrogen addition.

It is expected that CO2 concentration will increase in the air, thereby stimulating the photosynthesis process and, hence, plant biomass production. In the case of legumes, increased biomass due to higher CO2 concentration can stimulate atmospheric nitrogen (N2) fixation in the nodules. However, N2 fixation is inhibited by external N supply. Thus, biomass production and N2 fixation were analysed in two legumes (Pisum sativum L. and Vicia faba L.) grown at two levels of CO2 and three N levels. P. sativum reduces fixation with high soil N (facultative), while V. faba maintains high fixation regardless of soil N levels (obligate). The N2 fixation and plant and nodule biomass of the two species were evaluated in a pot experiment under controlled conditions using growth chambers with artificial CO2 supply and N addition. The proportion of N derived from the air (%Ndfa) present in the plants' biomass was calculated from the natural abundance of 15N and the N concentration of plant tissues using nonlegumes reference plants. Additionally, N content data are presented for both species growing at two levels of air CO2. The data may be useful for plant physiologists, especially those working on biological N2 fixation with non-model legumes at elevated CO2.

Evolution of drought and frost responses in cool season grasses (Pooideae): was drought tolerance a precursor to frost tolerance?

Frost tolerance has evolved many times independently across flowering plants. However, conservation of several frost tolerance mechanisms among distant relatives suggests that apparently independent entries into freezing climates may have been facilitated by repeated modification of existing traits ('precursor traits'). One possible precursor trait for freezing tolerance is drought tolerance, because palaeoclimatic data suggest plants were exposed to drought before frost and several studies have demonstrated shared physiological and genetic responses to drought and frost stress. Here, we combine ecophysiological experiments and comparative analyses to test the hypothesis that drought tolerance acted as a precursor to frost tolerance in cool-season grasses (Pooideae). Contrary to our predictions, we measured the highest levels of frost tolerance in species with the lowest ancestral drought tolerance, suggesting that the two stress responses evolved independently in different lineages. We further show that drought tolerance is more evolutionarily labile than frost tolerance. This could limit our ability to reconstruct the order in which drought and frost responses evolved relative to each other. Further research is needed to determine whether our results are unique to Pooideae or general for flowering plants.

Validation of the Residual Feed Intake Model in Brangus Heifers: Determination of the Optimal Days on Feed Interval to Estimate Dry Matter Intake and Average Daily Gain.

Brangus cattle are gaining popularity in the Southeast U.S. due to the desirable heat tolerance from their Brahman influence combined with the superior carcass merit aspects of Angus genetics. However, little is known about the optimal evaluation conditions for this hybrid breed when placed on test for Residual Feed Intake (RFI), a heritable measure of feed efficiency that allows improvement in performance without altering carcass traits. To address this, dry matter intake (DMI) was measured on Brangus heifers for 70-d to determine the optimal days on feed required to estimate feed intake and ADG and assess if inclusion of ultrasound measures of carcass merit into the model impact RFI rankings for this breed. The 56-d test period had a regression coefficient of 0.96 (p < 0.0001), R2 = 0.94, rp = 0.97 (p < 0.0001), and rs = 0.97 (p < 0.0001), indicating little change in rank of cattle for DMI compared to a 70-d test. ADG was the limiting factor in determining test duration. Based upon examining only heifers that calved, ultrasound backfat measures should be included in the RFI model to normalize for differences in heifer maturity. Results from this study indicate that a test duration of 56-d is sufficient to accurately estimate DMI in this population. This data indicates on-test duration can be shortened, enhancing the rate of genetic change by reducing cost and increasing the number of animals that can be tested annually.

The effect of replacing conventional alfalfa hay with lower-lignin alfalfa hay on feed intake, nutrient digestibility, and energy utilization in lactating Jersey cows.

Lower-lignin (LoL) varieties of alfalfa (Medicago sativa L.) have been developed in recent years, and have the potential to positively impact animal performance. The objective of this study was to evaluate the effects of increasing the proportion of LoL alfalfa hay in diets fed to lactating dairy cows. Research plots were planted with a conventional variety (CON; Dairyland Hybriforce 3400), and 2 LoL varieties (LLG; 54HVX42 and LLB; Aflorex HiGest 460). After harvest, the LoL varieties were blended in equal proportions for feeding. Twelve multiparous Jersey cows (100 ± 4 d in milk) were used in a 3 × 3 Latin square with 3 periods of 28 d. Cows were assigned to 3 diets containing 0 (CNTRL), 16.1 (MdLL), and 32.2% (HiLL) of the diet DM as LoL alfalfa hay, which replaced CON. The CON alfalfa had average CP, NDF, and lignin contents (DM basis) of 20.5 ± 1.15, 42.1 ± 1.37, and 6.81 ± 0.57%, respectively, while the LoL alfalfa averaged 19.8 ± 0.75, 39.9 ± 1.56, and 6.07 ± 0.28%, respectively. No difference was observed in DMI (20.4 ± 0.61 kg/d). No difference in milk yield was observed, averaging 31.0 ± 1.02 kg/d across treatments. Similarly, no difference was observed in ECM yield (averaging 36.2 ± 1.43 kg/d). Feed conversion (ECM/DMI) tended to increase linearly with LoL alfalfa inclusion (1.74 to 1.80 ± 0.03). No difference was observed for milk fat yield and content (1.39 ± 0.075 kg/d and 4.51 ± 0.219%) or milk protein yield and content (1.06 ± 0.041 kg/d and 3.43 ± 0.096%). Total methane production quadratically decreased from CNTRL to MdLL then increased to HiLL (441, 389, 412 ± 18.2 L/d, respectively). No differences were observed on total-tract digestibility of DM (averaging 67.2 ± 0.55%) and NDF (averaging 50.9 ± 1.56%). No difference was observed in the concentration of DE, ME or NEL was observed averaging 2.82 ± 0.021, 2.51 ± 0.027, and 1.72 ± 0.030 Mcal/kg respectively. Our results suggest that replacing CON alfalfa with LoL alfalfa has no effects on milk production, milk composition, or nutrient digestibility but may improve feed efficiency.

Nano silica's role in regulating heavy metal uptake in Calendula officinalis.

BACKGROUND: Soil contamination with heavy metals poses a significant threat to plant health and human well-being. This study explores the potential of nano silica as a solution for mitigating heavy metal uptake in Calendula officinalis. RESULTS: Greenhouse experiments demonstrated, 1000 mg•kg- 1 nano silica caused a 6% increase in soil pH compared to the control treatment. Also in 1000 mg. kg- 1 nano silica, the concentrations of available Pb (lead), Zn (zinc), Cu (copper), Ni (nickel), and Cr (chromium) in soil decreased by 12%, 11%, 11.6%, 10%, and 9.5%, respectively, compared to the control. Nano silica application significantly reduces heavy metal accumulation in C. officinalis exposed to contaminated soil except Zn. In 1000 mg.kg- 1 nano silica shoots Zn 13.28% increased and roots Zn increased 13% compared to the control treatment. Applying nano silica leads to increase the amount of phosphorus (P) 25%, potassium (K) 26% uptake by plant, In 1000 mg.kg - 1 treatment the highest amount of urease enzyme activity was 2.5%, dehydrogenase enzyme activity, 23.6% and the highest level of alkaline phosphatase enzyme activity was 13.5% higher than the control treatment. CONCLUSION: Nano silica, particularly at a concentration of 1000 mg.kg - 1, enhanced roots and shoots length, dry weight, and soil enzyme activity Moreover, it increased P and K concentrations in plant tissues while decreasing heavy metals uptake by plant.

Post-Harvest Behavior of Seedless Conical and Mini-Conical Peppers: Weight Loss, Dry Matter Content, and Total Soluble Solids as Indicators of Quality and Commercial Shelf-Life.

This study aimed to assess the post-harvest dynamics of seedless conical and mini-conical pepper cultivars in terms of fruit weight loss, dry matter content, and soluble solid content. The above parameters were demonstrated to be effective commercial pepper shelf-life indicators. The commercial quality of pepper fruit intended for export was evaluated weekly under simulated fruit storage conditions for over 28 d. Results revealed that fruit weight loss, dry matter content, and soluble solid content were affected by cultivar type and storage duration. Additionally, a strong correlation between these variables was observed confirming their linear relationship which was more profound between dry matter and total soluble solid content. Daily changes during storage were similar in both seedless conical and mini-conical peppers, while the fruit weight loss daily rate was greater than that of dry matter. Water loss was identified to be the main factor causing reduced fruit quality. Solid content reduction occurred predominately during the initial storage period. Notably, fruit with lower dry matter content at harvest tended to maintain their commercial quality for a longer time due to their ability to resist water loss without any visible signs of deterioration, which is beneficial during prolonged storage.

Feed intake in housed dairy cows: validation of a three-dimensional camera-based feed intake measurement system.

Measuring feed intake accurately is crucial to determine feed efficiency and for genetic selection. A system using three-dimensional (3D) cameras and deep learning algorithms can measure the volume of feed intake in dairy cows, but for now, the system has not been validated for feed intake expressed as weight of feed. The aim of this study was to validate the weight of feed intake predicted from the 3D cameras with the actual measured weight. It was hypothesised that diet-specific coefficients are necessary for predicting changes in weight, that the relationship between weight and volume is curvilinear throughout the day, and that manually pushing the feed affects this relationship. Twenty-four lactating Danish Holstein cows were used in a cross-over design with four dietary treatments, 2 × 2 factorial arranged with either grass-clover silage or maize silage as silage factor, and barley or dried beet pulp as concentrate factor. Cows were adapted to the diets for 11 d, and for 3 d to tie-stall housing before camera measurements. Six cameras were used for recording, each mounted over an individual feeding platform equipped with a weight scale. When building the predictive models, four cameras were used for training, and the remaining two for testing the prediction of the models. The most accurate predictions were found for the average feed intake over a period when using the starting density of the feed pile, which resulted in the lowest errors, 6% when expressed as RMSE and 5% expressed as mean absolute error. A model including curvilinear effects of feed volume and the impact of manual feed pushing was used on a dataset including daily time points. When cross-validating, the inclusion of a curvilinear effect and a feed push effect did not improve the accuracy of the model for neither the feed pile nor the feed removed by the cow between consecutive time points. In conclusion, measuring daily feed intake from this 3D camera system in the present experimental setup could be accomplished with an acceptable error (below 8%), but the system should be improved for individual meal intake measurements if these measures were to be implemented.

Intake profile, milk production and energy balance of early lactation spring calving Holstein Friesian and Jersey x Holstein Friesian dairy cows in high utilisation pasture-based systems.

Early lactation is a critical period for dairy cows as energy requirements rapidly increase with the onset of lactation, however, early lactation dry matter intakes (DMI) in pasture-based systems are under-measured. The objectives of this study were 1) to measure and profile total DMI (TDMI) and animal performance of dairy cows during early lactation in a pasture-based system 2) to investigate early lactation energy balance in pasture-based systems and 3) to examine production efficiencies including TDMI and milk solids production per 100 kg bodyweight. Eighty spring-calving dairy cows were allocated to a grazing group as they calved over a 2 year period (2021 and 2022). Cows were offered a daily herbage allowance to achieve a post-grazing sward height of 4 cm with silage supplementation when necessary due to inclement weather. Total DMI was measured using the n-alkane technique over a 12 week period from 1st of February to the 23rd of April. Total DMI and daily milk yield were significantly affected by parity with both variables being greatest for third parity animals (17.7 kg DM and 26.3 kg/cow/day, respectively), lowest for first parity (13.2 kg DM and 19.6 kg/cow/day, respectively) and intermediate for second parity animals (16.8 kg DM and 24.1 kg/cow/day, respectively). Peak TDMI was reached on wk 10 for first parity animals (14.6 kg DM), wk 11 for second parity animals (19.3 kg DM) and wk 12 for third parity animals (19.9 kg DM). Parity also had a significant effect on UFL (feed units for milk) feed balance as first parity animals experienced a greater degree of negative energy balance (-3.2 UFL) compared with second and third parity animals (-2.3 UFL). Breed and parity had an effect on production efficiencies during the first 12 weeks of lactation as Jersey x Holstein Friesian cows had greater TDMI/100 kg bodyweight and milk solids/100 kg bodyweight compared with Holstein Friesian cows.

Investigating relationships between the host genome, rumen microbiome, and dairy cow feed efficiency using mediation analysis with structural equation modeling.

The rumen microbiome is crucial for converting feed into absorbable nutrients used for milk synthesis, and the efficiency of this process directly impacts the profitability and sustainability of the dairy industry. Recent studies have found that the rumen microbial composition explains part of the variation in feed efficiency traits, including dry matter intake, milk energy, and residual feed intake. The main goal of this study was to reveal relationships between the host genome, rumen microbiome, and dairy cow feed efficiency using structural equation models. Our specific objectives were to (i) infer the mediation effects of the rumen microbiome on feed efficiency traits, (ii) estimate the direct and total heritability of feed efficiency traits, and (iii) calculate the direct and total breeding values of feed efficiency traits. Data consisted of dry matter intake, milk energy, and residual feed intake records, SNP genotype data, and 16S rRNA rumen microbial abundances from 448 mid-lactation Holstein cows from 2 research farms. We implemented structural equation models such that the host genome directly affects the phenotype (GP → P) and the rumen microbiome (GM → P), while the microbiome affects the phenotype (M → P), partially mediating the effect of the host genome on the phenotype (G → M → P). We found that 7 to 30% of microbes within the rumen microbial community had structural coefficients different from zero. We classified these microbes into 3 groups that could have different uses in dairy farming. Microbes with heritability <0.10 but significant causal effects on feed efficiency are attractive for external interventions. On the other hand, 2 groups of microbes with heritability ≥0.10, significant causal effects, and genetic covariances and causal effects with the same or opposite sign to feed efficiency are attractive for selective breeding, improving or decreasing the trait heritability and response to selection, respectively. In general, the inclusion of the different microbes in genomic models tends to decrease the trait heritability rather than increase it, ranging from -15% to +5%, depending on the microbial group and phenotypic trait. Our findings provide more understanding to target rumen microbes that can be manipulated, either through selection or management interventions, to improve feed efficiency traits.

Assessing different cross-validation schemes for predicting novel traits using sensor data: an application to dry matter intake and residual feed intake using milk spectral data.

Feed efficiency is important for economic profitability of dairy farms; however, recording daily dry matter intakes (DMI) is expensive. Our objective was to investigate the potential use of milk mid-infrared (MIR) spectral data to predict proxy phenotypes for DMI based on different cross-validation schemes. We were specifically interested in comparisons between a model that included only MIR data (Model M1), a model that incorporated different energy sink predictors, such as body weight, body weight change, and milk energy (Model M2), and an extended model that incorporated both energy sinks and MIR data (Model M3). Models M2 and M3 also included various cow level variables (stage of lactation, age at calving, parity) such that any improvement in model performance from M2 to M3, whether through a smaller root mean squared error (RMSE) or a greater squared predictive correlation (R2), could indicate a potential benefit of MIR to predict residual feed intake. The data used in our study originated from a multi-institutional project on the genetics of feed efficiency in US Holsteins. Analyses were conducted on 2 different trait definitions based on different period lengths: averaged across weeks vs. averaged across 28-d. Specifically, there were 19,942 weekly records on 1,812 cows across 46 experiments or cohorts and 3,724 28-d records on 1,700 cows across 43 different cohorts. The cross-validation analyses involved 3 different k-fold schemes. First, a 10-fold cow-independent cross-validation was conducted whereby all records from any one cow were kept together in either training or test sets. Similarly, a 10-fold experiment-independent cross-validation kept entire experiments together whereas a 4-fold herd-independent cross-validation kept entire herds together in either training or test sets. Based on cow-independent cross-validation for both weekly and 28-d DMI, adding MIR predictors to energy sinks (Models M3 vs M2) significantly (P < 10-10) reduced average RMSE to 1.59 kg and increased average R2 to 0.89. However, adding MIR to energy sinks (M3) to predict DMI either within an experiment-independent or herd-independent cross-validation scheme seemed to demonstrate no merit (P > 0.05) compared with an energy sink model (M2) for either R2 or RMSE (respectively, 0.68 and 2.55 kg for M2 in herd-independent scheme). We further noted that with broader cross-validation schemes, i.e., from cow-independent to experiment-independent to herd-independent schemes, the mean and slope bias increased. Given that proxy DMI phenotypes for cows would need to be almost entirely generated in herds having no DMI or training data of their own, herd-independent cross-validation assessments of predictive performance should be emphasized. Hence, more research on predictive algorithms suitable for broader cross-validation schemes and a more earnest effort on calibration of spectrophotometers against each other should be considered.

Dynamic plant spacing in tomato results in high yields while mitigating the reduction in fruit quality associated with high planting densities.

High planting densities achieve high light interception and harvestable yield per area but at the expense of product quality. This study aimed to maintain high light interception without negative impacts on fruit quality. Dwarf tomato was grown at four densities in a climate-controlled room-at two constant densities (high and low) and two dynamic spacing treatments (maintaining 90% and 75% ground coverage by decreasing planting density in 3-4 steps)-resulting in ~100, 19, 54, and 41 plants/m2 averaged over 100 days of cultivation, respectively. Constant high density resulted in the highest light use efficiency (LUE; 7.7 g fruit fresh weight per mol photons incident on the canopy) and the highest harvestable fruit yield (11.1 kg/m2) but the lowest fruit size and quality. Constant low density resulted in the lowest LUE and yield (2.3 g/mol and 3.2 kg/m2, respectively), but higher fruit size and quality than high density. Compared to low density, maintaining 90% ground coverage increased yield (9.1 kg/m2) and LUE (6.4 g/mol). Maintaining 75% ground coverage resulted in a 7.2 kg/m2 yield and 5.1 g/mol LUE. Both dynamic spacing treatments attained the same or slightly reduced fruit quality compared to low density. Total plant weight per m2 increased with planting density and saturated at a constant high density. Assimilate shortage at the plant level and flower abortion lowered harvestable fruit yield per plant, sweetness, and acidity under constant high density. Harvestable fruit yield per plant was the highest under dynamic spacing and low density. Under constant high density, morphological responses to lower light availability per plant-i.e., higher specific leaf area, internode elongation, and increased slenderness-coincided with the improved whole-plant LUE (g plant dry weight per mol photons). We conclude that a constant high planting density results in the highest harvestable fruit yield per area, but with reduced fruit quality. Dynamic spacing during cultivation produces the same fruit quality as constant low density, but with more than double the harvestable yield per area.

Methane output across life stages in sheep, how it differs from lambs to adult ewes using portable accumulation chambers.

Methane (CH4) produced from enteric fermentation is a potent greenhouse gas produced by ruminant animals. Multiple measurements are required across life stages to develop an understanding of how CH4 output changes throughout the animal's lifetime. The objectives of the current study were to estimate CH4 output across life stages in sheep and to investigate the relationship between CH4 output and dry matter (DM) intake (DMI). Data were generated on a total of 266 female Suffolk and Texel animals. Methane and carbon dioxide (CO2) output, estimated using portable accumulation chambers, and DMI, estimated using the n-alkane technique outdoors and using individual penning indoors, were quantified across the animal's life stage; as lambs (<12 mo), nulliparous hoggets (12 to 24 mo) and ewes (primiparous or greater; > 24 mo). Ewes were further classified as pregnant, lactating, and dry (non-pregnant and non-lactating). Multiple measurements were taken within and across the life stages of the same animals. A linear mixed model was used to determine if CH4 and CO2 output differed across life stages and using a separate linear mixed model the factors associated with CH4 output within each life stage were also investigated. Methane, CO2 output, and DMI differed by life stage (P < 0.05), with lactating ewes producing the greatest amount of CH4 (25.99 g CH4/d) and CO2 (1711.6 g CO2/d), while also having the highest DMI (2.18 kg DM/d). Methane output differed by live-weight of the animals across all life stages (P < 0.001). As ewe body condition score increased CH4 output declined (P < 0.05). Correlations between CH4 output measured across life stages ranged from 0.26 (SE 0.08; lambs and lactating ewes) to 0.59 (SE 0.06; hoggets and pregnant ewes), while correlations between CO2 output measured across life stages ranged from 0.12 (SE 0.06; lambs and hoggets) to 0.65 (SE 0.06; hoggets and lactating ewes). DMI was moderately correlated with CH4 (0.44; SE 0.04) and CO2 output (0.59; SE 0.03). Results from this study provide estimates of CH4 output across life stages in a pasture-based sheep production system and offer valuable information for the national inventory and the marginal abatement cost curve on the optimum time to target mitigation strategies.

Obtaining accurate estimates of methane (CH4) output across life stages is important to assess how CH4 output changes throughout the production cycle in pasture-based sheep production systems. This study investigated the factors associated with CH4 output at each life stage (lambs, hoggets, pregnant, lactating, and dry ewes), the relationship between CH4 output measured across life stages and the relationship between CH4 output and dry matter intake (DMI) in an Irish lowland sheep production system. Methane and carbon dioxide (CO2) output and DMI were measured on 266 purebred Suffolk and Texel females across their lifetime. Lactating ewes produced the highest CH4 and CO2 output, along with having the highest DMI. Across all life stages, CH4 output increased with increasing live weight while CH4 output decreased as body condition score increased. Weak to moderate relationships were found between CH4 output measured across life stages, with the strength of the relationship decreasing as the time between life stages increased. A positive relationship was found between DMI and CH4 output. Results from this study lead to the development of a profile of CH4 output across the production cycle of a pasture-based sheep system.

Aeration Alleviated the Adverse Effects of Nitrogen Topdressing Reduction on Tomato Root Vigor, Photosynthetic Performance, and Fruit Development.

To explore the compensation effect of aeration on tomato vegetative and reproductive growth in arid and semi-arid areas, a two-year field experiment was conducted with four micro-nano aeration ratios (0%, 5%, 10%, and 15%) and three nitrogen topdressing levels (80, 60, and 40 kg·ha-1) during the tomato growth period in Ningxia, China. The results showed that increasing the aeration ratio in the range of 0-15% was conducive to the enhancement of tomato root vigor (the ability of triphenyltetrazolium chloride to be reduced, 3-104%) and the leaf net photosynthetic rate (14-63%), favorable to the facilitation of plant dry matter accumulation (3-59%) and plant nitrogen accumulation (2-70%), and beneficial to the improvement of tomato yield (12-44%) and fruit quality. Interestingly, since the aeration ratio exceeded 10%, the increase in the aeration ratio showed no significant effects on the single-fruit weight, tomato yield, and fruit quality. Moreover, with aerated underground drip irrigation, properly reducing the traditional nitrogen topdressing level (80 kg·ha-1) by 25% was favorable for enhancing tomato root vigor (5-31%), increasing tomato yield (0.5-9%), and improving fruit soluble solid accumulation (2-5%) and soluble sugar formation (4-9%). Importantly, increasing the aeration ratio by 5% could compensate for the adverse effects of reducing the nitrogen topdressing level by 25% by improving the leaf photosynthetic rate, promoting plant dry matter accumulation, increasing tomato yield, and enhancing the soluble solid and soluble sugar accumulation in tomato fruits. Synthetically considering the decrease in the nitrogen topdressing amount, leading to plant growth promotion, a tomato yield increase, and fruit quality improvement, a favorable nitrogen topdressing level of 60 kg·ha-1 and the corresponding proper aeration ratio of 10% were suggested for tomato underground drip irrigation in the Yinbei Irrigation District of Ningxia.

The Synergistic Production Effect of Water and Nitrogen on Winter Wheat in Southern Xinjiang.

Water and nitrogen management are crucial for food security and the efficient use of water and fertilizer, especially in arid regions. Three irrigation levels, namely, 80% crop water requirement (ETC) (W1), 100% ETC (W2), and 120% ETC (W3), and three nitrogen application levels, namely, 0 kg/ha (N1), 207 kg/ha (N2), and 276 kg/ha (N3), were used as the experimental treatments, and a control group, denoted as CK, was created. The results show that the maximum height achieved was 82.16 cm under W3N3. There was a single-peak variation trend throughout the growth stages of SPAD. It peaked at 58.44 under W3N3 and then at 27.9 under W2N2. The net photosynthetic and transpiration rates displayed bimodal peaks and the phenomenon of a "photosynthetic midday depression". And the prominent peaks in leaf water use efficiency occurred at 14:00 and 18:00, alongside noteworthy enhancements observed under the W3 treatment. Water and nitrogen and their interactions significantly affected the dry matter (DM) of winter wheat, with the spike accounting for the highest percentage. The W2N2 treatment demonstrated superior effectiveness in enhancing winter wheat water use efficiency, offering the potential to decrease irrigation requirements by 20% and nitrogen application by 25%. Moreover, the maximum PFPN attained under W2N2 reached 60.13, representing a noteworthy 35.25% increase compared to the control group (CK), but the HI of the W2N2 treatment only reached 0.56. The highest HI was achieved with W3N2 (0.73), and the nitrogen application of 207 kg/ha was more conducive to obtaining a higher HI. The highest yield was achieved under W3N3 (13.599 t/ha), followed by W2N2 (12.447 t/ha), and the spike proportion exceeded 60% with W2N2, and its production cost and economic benefit ratio of under 0.31 were superior to those for other treatments. Multiple regression analysis revealed that the maximum yield reached 12.944 t/ha with an irrigation amount of 3420.1 m3/ha and a nitrogen application of 251.92 kg/ha. Overall, our study suggests using an optimal water-nitrogen combination, specifically an irrigation level of 2829 m3/ha and a nitrogen application rate of 207 kg/ha, leading to increased winter wheat yields and economic benefits. These research results provide a pragmatic technique for improving winter wheat production in southern Xinjiang.

Difference in Cd accumulation among varieties with different growth duration corresponding to typical agro-climate condition in rice ratooning system.

Introduction: The ratoon rice planting area is gradually expanding, but there has been relatively little research on ratoon rice grains contaminated with Cd. Methods: In this study, five ratoon rice varieties were selected and divided into three groups according to early-maturity (growth duration: 100-110 days), mid-maturity (growth duration: 110-120 days) and late-maturity (growth duration: 120-130 days) varieties. Field experiments were done to study the differences in Cd accumulation among ratoon rice varieties with different growth duration. Results: The results showed that the Cd accumulation and concentration of grains spikelet at each growth stage in the main crop were in the order of late-maturity > mid-maturity > early-maturity varieties. However, the trends in Cd concentration and accumulation in grains spikelet during the ratoon crop were the opposite. Analysis found that as the growth duration of the variety extended, the accumulated temperature and daily average temperature in the main crop increased, which significantly increased the translocation factors of Cd from root, stem, and leaf to grains spikelet, and increased the daily average Cd accumulation rate in grains spikelet. The daily average temperature in the ratoon crop increased as the growth duration shortened. The early-maturity variety had higher Cd accumulation in stubble, which promoted the translocation of Cd from the root, stem, and leaf of the plant to the grains spikelet. Discussion: Therefore, appropriately shortening the growth duration of the main crop and extending the growth duration of the ratoon crop are important ways to reduce Cd accumulation in ratoon rice in areas with mild Cd pollution.

Comparative near Infrared (NIR) spectroscopy calibrations performance of dried and undried forage on dry and wet matter bases.

The application of Near Infrared (NIR) spectroscopy for analyzing wet feed directly on farms is increasingly recognized for its role in supporting harvest-time decisions and refining the precision of animal feeding practices. This study aims to evaluate the accuracy of NIR spectroscopy calibrations for both undried, unprocessed samples and dried, ground samples. Additionally, it investigates the influence of the bases of reference data (wet vs. dry basis) on the predictive capabilities of the NIR analysis. The study utilized 492 Corn Whole Plant (CWP) and 405 High Moisture Corn (HMC) samples, sourced from various farms across Italy. Spectral data were acquired from both undried, unground and dried, ground samples using laboratory bench NIR instruments, covering a spectral range of 1100 to 2498 nm. The reference chemical composition of these samples was analyzed and presented in two formats: on a wet matter basis and on a dry matter basis. The study revealed that calibrations based on undried samples generally exhibited lower predictive accuracy for most traits, with the exception of Dry Matter (DM). Notably, the decline in predictive performance was more pronounced in highly moist products like CWP, where the average error increased by 60-70%. Conversely, this reduction in accuracy was relatively contained (10-15%) in drier samples such as HMC. The Standard Error of Cross-Validation (SECV) values for DMres, Ash, CP, and EE were notably low, at 0.39, 0.30, 0.29, 0.21% for CWP and 0.49, 0.14, 0.25, 0.14% for HMC, respectively. These results align with previous studies, indicating the reliability of NIR spectroscopy in diverse moisture contexts. The study attributes this variance to the interference caused by water in 'as is' samples, where the spectral features predominantly reflect water content, thereby obscuring the spectral signatures of other nutrients. In terms of calibration development strategies, the study concludes that there is no significant difference in predictive performance between undried calibrations based on either 'dry matter' or 'as is' basis. This finding emphasizes the potential of NIR spectroscopy in diverse moisture contexts, although with varying degrees of accuracy contingent upon the moisture content of the analyzed samples. Overall, this research provides valuable insights into the calibration strategies of NIR spectroscopy and its practical applications in agricultural settings, particularly for on-farm forage analysis.

Dynamic Simulation of the Leaf Mass per Area (LMA) in Multilayer Crowns of Young Larix principis-rupprechtii.

Leaf mass per area (LMA) is a key structural parameter that reflects the functional traits of leaves and plays a vital role in simulating the material and energy cycles of plant ecosystems. In this study, vertical whorl-by-whorl sampling of LMA was conducted in a young Larix principis-rupprechtii plantation during the growing season at the Saihanba Forest Farm. The vertical and seasonal variations in LMA were analysed. Subsequently, a predictive model of LMA was constructed. The results revealed that the LMA varied significantly between different crown whorls and growing periods. In the vertical direction of the crown, the LMA decreased with increasing crown depth, but the range of LMA values from the tree top to the bottom was, on average, 30.4 g/m2, which was approximately 2.5 times greater in the fully expanded phase than in the early leaf-expanding phase. During different growing periods, the LMA exhibited an allometric growth trend that increased during the leaf-expanding phase and then tended to stabilize. However, the range of LMA values throughout the growing period was, on average, 40.4 g/m2. Among the univariate models, the leaf dry matter content (LDMC) performed well (adjusted determination coefficient (Ra2) = 0.45, root mean square error (RMSE) = 13.48 g/m2) in estimating the LMA. The correlation between LMA and LDMC significantly differed at different growth stages and at different vertical crown whorls. The dynamic predictive model of LMA constructed with the relative depth in the crown (RDINC) and date of the year (DOY) as independent variables was reliable in both the assessments (Ra2 = 0.68, RMSE = 10.25 g/m2) and the validation (absolute mean error (MAE) = 8.05 g/m2, fit index (FI) = 0.682). Dynamic simulations of crown LMA provide a basis for elucidating the mechanism of crown development and laying the foundation for the construction of an ecological process model.

Agronomic performance of forage corn for cattle feeding in Amazonas, Peru.

Corn (Zea mays) silage is an important and popular feed for dairy production in the Amazon region, so it is necessary to evaluate the agronomic performance of forage varieties of corn for cattle feeding in Amazonas. For this purpose, three corn varieties were evaluated (variety 1: Yellow Starchy Corn, variety 2: Chuska INIA 617, and variety 3: DOW 2B710), with two planting densities (density 1: 30 × 80 cm and density 2: 35 × 75 cm) and two fertilization conditions: with fertilization (F1) and without fertilization (F2). The parameters evaluated were plant height, number of leaves, leaf length and width, stem diameter, fresh forage, and dry matter. Student t-tests, correlation analysis of variables, and principal component analysis using R software version 4.1.3 were used for data analysis. The results indicated that variety 2 obtained the best values for the variables leaf width (12.33 cm) and stem diameter (3.25 cm), fresh forage (17.77 kg/m2), and dry matter (4.8 kg/m2), which would explain the directly proportional correlation found between leaf width and stem diameter with fresh forage and dry matter. The principal component analysis showed constant height and leaf length increases, and the best-evaluated parameters were associated with applying fertilizer. The variety that showed the best agronomic performance under Chachapoyas conditions was Chuska INIA 617, emerging as a potential feed for cattle.

Intraspecific variation in fine-root traits is larger than in aboveground traits in European herbaceous species regardless of drought.

Differences within species (Intraspecific trait variation - ITV) contribute substantially to overall trait variability and environmental harshness can reduce among-species variation. While aboveground traits have received considerable attention, knowledge about ITV in fine-root traits and how it differs from ITV in aboveground traits remains limited. This study examined the partitioning of trait variation aboveground and fine-root traits in 52 European herbaceous species and how such proportions change in response to drought, offering valuable insights for accurate functional species characterization and inter-species comparisons. We studied seven morphological aboveground and fine-root traits under drought and well-watered conditions in a greenhouse experiment. Linear mixed effect models and permutational multivariate analysis of variance (PERMANOVA) were employed to decompose trait variation, ensuring the robustness of our results. We also calculated variance partitioning for the combination of aboveground traits and the combination of fine-root traits, as well as pairs of analogous leaf and fine-root traits (i.e., traits that fulfill similar functions) for each treatment (control and drought). Among-species trait differences explained a greater proportion of overall variance than within-species variation, except for root dry matter content (RDMC). Height and leaf area stood out, with species' identity accounting for 87-90% of total trait variation. Drought had no significant effect on the proportions of variation in any of the traits. However, the combination of fine-root traits exhibited higher intraspecific variability (44-44%) than aboveground traits (19-21%) under both drought and control. Analogous root traits also showed higher ITV (51-50%) than analogous leaf traits (27-31%). Our findings highlight substantial within-species variation and the nuanced responses of fine-root traits, particularly RDMC, suggesting root traits' flexibility to soil heterogeneity that fosters less differentiation among species. Among-species trait differences, especially aboveground, may underscore distinct strategies and competitive abilities for resource acquisition and utilization. This study contributes to elucidate the mechanisms underlying the multifunctionality of the above- and belowground plants compartments.